# Bold BI Support
## Documentation
# How to Import Users and Groups from Azure AD
[Bold BI](https://www.boldbi.com/) provides an
option to import users and groups from Azure Active Directory. To import users
from Azure Active Directory, we need to configure the registered app in Bold BI
and log in to [Azure Portal](https://portal.azure.com/) then
follow the [steps](https://help.boldbi.com/site-administration/user-directory-settings/azure-active-directory/#steps-to-register-bold-bi-application-in-azure-active-directory-to-import-users-and-groups) to
register Bold BI Application in Azure Active Directory. After registering the
App in Azure Active Directory, [configure](https://help.boldbi.com/site-administration/user-directory-settings/azure-active-directory/#configure-azure-active-directory-details-in-bold-bi-to-import-users-and-groups) the
details in Bold BI to import users and groups.
**NOTE:** Only users under the **SystemAdministrator** and users with **permission** to manage
user and group can import users and group from Azure AD into Bold BI.
Importing Users from Azure AD
Follow the steps
below to import users from Azure AD
1. Open
“**Bold BI**” application
2. Click
on **Users icon**on the left pane of the Bold BI application.
3. Click
on **New User** for the drop-down list to show.
4. On
the drop-down list click **Import from Azure AD.**
5. **Searchfor the user to import and select the users from the list and click Import buttonat the top right corner. **
6. **BoldBI will import the chosen users and a confirmation message willbe displayed as shown below. **
7. **Provideaccess permission to users to access the dashboards on the site byfollowing this [link](https://help.boldbi.com/managing-resources/manage-users/#steps-to-add-permission-to-the-user).**
8. Bold
BI provides an option to synchronize the imported Azure AD users details from
Azure AD, follow this [link](https://help.boldbi.com/managing-resources/manage-users/synchronize-azure-active-directory-users/) to
achieve.
Importing groups from Azure AD
Follow these steps to
import groups from azure AD
1. Open **“BoldBI”** application
2. Click
on **Users’ icon**on the left pane of the bold bi application.
3. Click
on **Groups** on the left pane of the application page.
4. Click
on **New Group** for the drop-down list to show.
5. Choose
the Groups from the list and click **Import** button at the top
right corner.
6. Bold
BI will import the chosen group and a **confirmation message** will
be displayed as shown below.
7. Provide
access permission to groups to access the dashboards on the site by following
this [link](https://help.boldbi.com/managing-resources/manage-groups/#steps-to-add-permission-to-the-group).
8. Bold
BI provides an option to synchronize the imported Azure AD groups details from
Azure AD, follow this[link](https://help.boldbi.com/managing-resources/manage-groups/synchronize-azure-active-directory-groups/) to
achieve.
**Related links**
- [How to manage
users in Bold BI](https://help.boldbi.com/managing-resources/manage-users/)
- [How to configure
database settings in Bold BI](https://help.boldbi.com/site-administration/user-directory-settings/existing-database/database-settings/)
- [How to schedule
synchronization of new users in existing database in Bold BI](https://help.boldbi.com/site-administration/user-directory-settings/existing-database/imported-database-users-synchronization-schedule/)
# How to Import Users from a Database into Bold BI
Bold BI provides an option to import new users from an existing database.
:::Info
NOTE: Only users under the System Administrator can import users from the database into Bold BI.
:::
Importing new users from an existing database to Bold BI
Follow these steps to import new users from an existing database into Bold BI.
Open the “Bold BI” application.
Click on users on the left pane of the Bold BI application.
Bold BI Server Page
Click on New User, and the drop-down list will open.
Users Page
On the drop-down list, click Import from Database.
Import Users from Database
From the database retrieved data, select the users to be imported, then click Import Users.
Users list to import
A confirmation message will be displayed as follows to confirm the successful import of the users into Bold BI.
Users Imported
The Import Users page appears as follows.
Imported Users list
Mapping the imported users to an existing database
After importing users from an existing database, Bold BI provides an option to synchronize the imported existing database users’ details with the existing database.
Follow these steps to synchronize the imported users from the existing database.
Navigate to the user synchronization page from the user page, click Synchronize, and the drop-down list will open. Then click Database Synchronization from the drop-down list.
To Synchronize Users
From the Database User Synchronization page, select the users to be synchronized, then click Synchronize at the top. The Imported User details will be synchronized with the existing database users in Bold BI.
Users Synchronization page
:::Info
NOTE: Bold BI will delete the user if the user has been deleted from the existing Database.
:::
A confirmation message will be displayed that shows the number of users modified, deleted, or duplicated as shown in the success message box in the following figure to confirm the successful Database Synchronization.
Database Synchronization Notification
:::Info
NOTE: The existing database users with the same username or email address as the Bold BI users will be marked as duplicate users and will not be synchronized with the imported existing database users.
:::
Providing permissions to the imported user
Follow these steps to provide permissions to the users imported to the application.
Click the action menu on the right side of the users’ page to manage the users’ permission on the application.
Users Page
Navigate to the selected users’ page and click Add Permission.
To provide permission
Select the permissions to be added on the pop-up permission window, then click Add Permission list
# How to host Angular with ASP.NET Core application in IIS?
Bold BI users can embed Bold BI dashboards using Angular with ASP.NET Core applications. This article explains how to host an Angular with .NET Core application in IIS.
Follow these steps to host an Angular with .NET Core application in IIS.
Download the .NET 6.0 SDK file from here, then download and install the .net windows hosting bundle from here.
Once IIS is enabled, create a site in it for the net core application by providing the path of the published folder of the asp.net core as follows.
Provide the port number of the asp.net core site as a value of the apiHost in app.component.ts.
```js
@Injectable()
Export class AppComment {
//ASP.NET Core application would be run on http://localhost:61377/, which needs to be set as `apiHost
public apiHost = “http:/localhost:61377”;
//Your Bold BI application environment. (If Cloud, you should use ‘cloud’, if enterprise, you should use `enterprise`) public environment= “enterprise”;
//Dashboard server BI URL (ex: http://localhost:5000/bi, http://demo.boldbi.com/bi )
public rooturl= “http:localhost;53623/bi”;
//For Bold BI Enterprise edition, it should be like `site/site1`. For Bold BI cloud, it should be empty string.
public siteIdentifier= “site/site1”;
//Url of the GetDetails action in ValuesController of the ASP.NET core application
public authorizationUrl= “/api/bolbiembed/getdashboards”;
//Url of the GetDashboards action in ValuesController of the ASP.NET core application
public getDashboardUrl= “/api/bolbiembed/getdashboards”;
public dashboards: any;
public baseUrl: any;
public dashboardServerApiUrl: string;
constructor(private_app: appservice){
}
```
Publish an angular application by running the command ng build, then create a site for angular in IIS and provide its respective path as follows.
:::Info
NOTE: If ng build command is not recognized in an angular application, use npm install -g @angular/cli@latest in an angular application in the vs code terminal.
:::
Provide the portnumber which doesn’t exist on other sites. Click on the Application Pools and the respective application pool, then click Advancedsetting to change the identity to LocalSystem.
Proceed to run the application using a similar step for the net core site. First, open the asp.net core hosted site in the browser, then open the angular hosted site. The dashboard will be rendered in the angular hosted site.
# How to Embed IFrame Embedding Using SSO
Bold BI provides the support to embed dashboards in any application using Iframe based embedding. This article explains Iframe based embedding using Single Sign On (SSO). User could be able to embed dashboard without login prompt while trying to embed using iFrame URL with valid embedSignature.
Prerequisites
You need the mentioned prerequisites to run the sample. For the cloud version, you should have an active Bold BI Cloud application and for On-Premise, you should Install the latest Bold BI Enterprise build.
Set the following embed properties in Program.cs file as follows.
| Parameter | Description |
| --- | --- |
| dashboardUrl | URL of the dashboard to be embed |
| secretCode | Authorized key for the dashboard to be embed |
| userInfo | The email id of the user |
```js
>> namespace EmbedDashboardUsingSSO
>> {
>> class Program
>> {
>> static void Main(string[] args)
>> {
>> // Variable declaration to form the embed URL
>>
>> string secretCode = "7tFaq2zidmxJN8Pid6IMYhHFqAUwMfK"; // secret code generated in the Bold BI application
>> var dashboardUrl = "https://demo.boldbi.com/bi/en-us/dashboards/af43fb72-1e4e-45d5-9783-2a905a928792/Sales/Northwind%20Traders%20Sales%20Analysis(114)?viewid=3988a564-57c9-416e-b645-f6cc50ce5c0b&"; // URL of the dashboard to be embedded. Add '? or &' at the end of the URL based on your dashboard URL
>>
>> // Variable declaration to form the signature for the embed URL
>>
>> var nonce = Guid.NewGuid().ToString(); // random string
>> var userInfo = "demo@boldbi.com"; // email address of the user
>> bool canSaveView = true; // enable or disable permission to create, open, update, delete view
>> bool hasViews = true; // enable or disable the permission to check the views of the dashboard
>> bool hasExport = true; // enable or disable the permission to export the dashboards and widgets
>> bool hasDashboardComments = true; // enable or disable the permission to comment related actions to dashboards
>> bool hasWidgetComments = true; // enable or disable the permission to comment related actions to widgets
>> bool isMarkFavorite = true; // enable to disable the permission to make the dashboard favorite
>> double timeStamp = DateTimeToUnixTimeStamp(DateTime.UtcNow); // current time as UNIX time stamp
>> var expirationTime = "100"; // alive time of the token
```
In Bold BI Server, you can get your Embed Secret key from the administrator setting section using help link.
In the cs file, set the URL of the dashboard in the variable dashboardUrlthat you want to render. Please refer this link to get dashboard URL
```js
>> var dashboardUrl = "https://demo.boldbi.com/bi/en-us/dashboards/af43fb72-1e4e-45d5-9783-2a905a928792/Sales/Northwind%20Traders%20Sales%20Analysis(114)?viewid=3988a564-57c9-416e-b645-f6cc50ce5c0b&"; // URL of the dashboard to be embedded. Add '? or &' at the end of the URL based on your dashboard URL
>>
```
Based on provided Embed Properties, we are making Iframe URL with mandatory parameters as below then proceeded to run the sample.
```js
>> string signature = SignURL(embedMessage.ToLower(), secretCode);
>> string embedSignature = embedMessage.ToLower() + "&embed_signature=" + signature;
>> var embedUrl = dashboardUrl + embedSignature;
>> var iframe = "";
>> var filePath = @"..\..\..\embed.html"; // file named embed will be created in the extracted location in which the embed URL will be maintained
>> File.WriteAllText(filePath, iframe);
>> string url = filePath;
>> Process.Start("chrome.exe", url); // By default, the embed dashboard will be rendered in Google Chrome. Can update the browser as you wish
>> }
```
# How to Create a Dashboard and Update It with Production Data in Bold BI
Creating data source with test data
Open the “BoldBI” application.
Click “Data Sources” on the left panel of the application.
Click “Create Data Source” at the top right corner and select “Excel” data source.
Choose the file path of the test data and click “Connect.”
Click on “Update” to see the preview of the data and test data.
Click “Save and Exit” at the top right corner.
Created data source will be listed on the data source listing page.
Creating a dashboard with test data
To create a dashboard page, click the plus (+) icon, select “Start from Scratch” and give the dashboard's name.
To import an existing data source and use widgets, click “Data Source” below the settings icon.
Click “USE EXISTING” and add the data source. Drag and drop the appropriate widget.
Assign data to the widget by dragging and dropping the data to columns in the settings of widgets.
Click “Publish” to publish the dashboard with test data.
Steps to replace test data with production data
After publishing the dashboard, edit the data source of the dashboard by selecting the edit icon on the dashboard toolbar.
It will navigate the data source designer page by clicking edit and do changes by clicking “Edit Connection”.
In the “Edit Connection” window, upload the Excel file with production data and connect it.
After Saving new tables, the values on the widget are replaced by new table values, which can be seen.
:::Info
NOTE: To avoid data loss while replacing production data, ensure the column name and sheet name of the production data is the same as test data.
:::
# Install Bold BI as a WordPress Subsite using Nginx
Bold BI site can be installed and configured as a sub application of WordPress site on Linux using Nginx web server. This article explains the steps to Install Bold BI as a sub-application of WordPress on Linux using the Nginx web server
Follow the steps below to Install Bold BI as a WordPress Subsite using Nginx:
We have added some commented lines for SSL configuration. If you want to configure the Bold BI with SSL, refer to the link.
To eliminate the Bold BI application static file loading issue, the location of browser caching rules is changed from ~* to /var/www/html/wordpress/public_html.
By default, the sub path name is /dashboard, to access the site using any other name replace the /dashboard with /your-sub-pathname.
Restart the Nginx, to access the Bold BI site using http://domain-name/dashboard with a 404 page not found error as shown below.
Modify the InternalAppUrls with the /dashboard sub path in both config.xml and product.json file present in the location /var/www/bold-services/application/app_data/configuration as shown in the following screenshot, then restart the application by running the sudo systemctl restart bold-* command.
After restarting the application, you can access the Bold BI using http://domain-name/dashboard. Refer this link for application startup.
# How to Transform Excel Rows into Columns and Use Them in a Bold BI Dashboard
In the Bold BI application, users can use the PostgreSQL crosstab function to convert row data into columns and then bind the data to widgets. There is no direct option to bind a specific cell value from a Google sheet or Excel as a column name. Because when you connect the file data source in Bold BI, the data from the file gets extracted and moved to an intermediate SQL database. Later, the query is issued to the PostgreSQL server to process every dashboard interaction.
:::Info
NOTE: In Bold BI, we have support for an intermediate database such as MySQL, PostgreSQL, and SQL, but the crosstab function to convert row data into columns is only supported on PostgreSQL databases.
:::
How to change row data to a column using the PostgreSQL crosstab function
The following excel sheet with sample data explains how to change row data to the column using the PostgreSQL crosstab function.
The following steps explain how to change row data to the column using the PostgreSQL crosstab function:
We need to enable the crosstab function. The crosstab function is part of the PostgreSQL extension called tablefunc. Execute the following query in PostgreSQL to enable the tablfunc module for the configured database.
```js
create extension tablefunc;
```
Use the following custom PostgreSQL query in code view to convert row to column.
```js
SELECT "Month", "Target"::int, "Profit"::int FROM (
SELECT * FROM crosstab(
$ct$ SELECT u.attnum, t.rn, u.val FROM (
SELECT row_number() OVER () AS rn, * FROM "Datasource_862ecc48-c089-4aee-b760-70c5594dbbd5"."Sheet1") t
, unnest(ARRAY["bcfe34e9-eead-4054-90c3-df815baddedd"::text,
"6c0cfeec-cf5f-9ac0-a895fd44b887"::text,
"b51b3937-1c84-4c96-b737-ed751d21ea01"::text,
"151b20bf-045b-4a96-bcc9-72cfeafb623"::text,
"5abddaf8-1a9f-49997-8b5f-ee13ad6ac97d"::text,
"5abddaf8-1a9f-49997-8b5f-ee13ad6ac97d "::text,
"6559cbed-ca5e-4f10-a386-cea6-1b48a36"::text ]) WITH ORDINALITY u(val, attnum)
ORDER BY 1,2$ct$
) t(attnum bigint,"Month" text,"Target" text,
"Profit" text))t
```
:::Info
NOTE: Replace column names (Column2, Column3, etc..) and database schema name according to your data source.. In the above query above, the database schema name is highlighted.
:::
To get the database schema name, drag and drop the table (extracted Excel data stored in PostgreSQL table) in the design canvas.
Switch to code to get the schema and table names.
```js
SELECT
[Sheet].[Column1]AS [Column1],
[Sheet].[Column2]AS [Column2],
[Sheet].[Column3]AS [Column3],
[Sheet].[Column4]AS [Column4],
[Sheet].[Column5]AS [Column5],
[Sheet].[Column6]AS [Column6],
[Sheet].[Column7]AS [Column7],
[Sheet].[Column8]AS [Column8],
FROM [Datasource_3e296336-ea19-472d-a175-a2f37a91e381].[Sheet] AS [Sheet]
```
After getting the database schema name, use it in the PostgreSQL crosstab query and run it to see the result in the preview panel.
# How to Connect to SQL Server Using a Custom Port Number in a Bold BI Dashboard
By default, the SQL server uses 1433 as a port number. In this case, you can connect your SQL server as a data source in Bold BI by providing the server’s name, username, password, and database details as in the following image.
Bold BI Server:
:::Info
NOTE: SQL Server can also be connected to Bold BI in the designer as explained in this link: How to create Data sources in Bold BI
:::
But if your SQL server uses a different port number, then you cannot connect your SQL server using the previously mentioned details, it will throw “A network-related instance error”. In case of a different port number, you must specify your port number along with the server’s name.
How to specify port number along with the server’s name
In the server’s name text box, enter your port number along with the server’s name by using the comma separator symbol.
Example: Server name, port number
By using the port number along with your server’s name, you can connect your SQL server successfully in the Bold BI and design your dashboards using the established connection.
:::Info
Note: To identify your port number, follow these steps:
:::
Go to SQL Server Configuration Manager -> Network Configuration.
Right click TCP/IP and select Properties.
In the IP Address tab, you can see the port number.
GraphQL is an open-source data query and manipulation language for APIs, and a runtime for fulfilling queries with existing data. It is a new API standard that provides a more efficient, powerful, and flexible alternative to REST API. It allows clients to define the structure of the data required, and the same structure of the data is returned from the server, therefore preventing excessively large amounts of data from being returned.
Steps to create a data source using the GraphQL
Follow these steps to create a new RESTful Web services data source using GraphQL in the Bold BI platform dashboards.
Click on the data source icon to open the DATA SOURCES pane.
# How to Connect MongoDB Using Direct Query Mode in Bold BI
In Bold BI, we have a direct option to connect and design dashboards with data fetched from the MongoDB database. However, this requires an intermediate database to extract the required databases and collections from MongoDB. For MongoDB databases with huge collections, this is a tiresome process and may take more time to extract the data into the intermediate database.
MongoDB provides a BI connector tool that lets you connect MongoDB servers directly through an ODBC connector or MySQL connector without any intermediate database involved. The MongoDB BI connector provides access to MongoDB data by abstracting rich, hierarchical document structure and presenting it as a tabular, relational schema using a MySQL interface.
Connecting through an ODBC driver
Bold BI (on-premises) provides support to import data from ODBC drivers(32-bit). This BI connector can be connected to a MySQL ODBC driver or MongoDB ODBC driver and these ODBC DSNs can then be accessed within Bold BI. MongoDB has its own ODBC driver available in the market.
Follow the quick start guide to set up BI connector with MongoDB server and MySQL ODBC connector. After connecting your BI connector with MongoDB server successfully, you will get the list of available schemas in your server as follows.
Then, provide these connector details in MYSQL ODBC driver. Test and save the DSN.
Afterwards, load this ODBC driver into Bold BI to create live connection with MongoDB server.
How to connect ODBC driver in Bold BI
Open the “Bold BI” application.
Click data source on the left panel of the Bold BI application page as shown below.
Click create data source on the top right corner as shown below.
Select the ODBC connection in the connection panel to proceed to connect.
Choose the configured DSN from the list and enter the credentials. Click Connect.
Your database and collections from MongoDB will now be available in Bold BI. This is a direct connection from MongoDB.
:::Info
NOTE: You can also use the MySQL connection panel to directly connect to the MongoDB BI connector without the help of an ODBC driver.
:::
Connecting MongoDB through MySQL
We can have a direct connection to a MongoDB server in Bold BI by providing the MongoDB BI connector details directly into the MySQL connection panel. Refer to the following snapshots.
On the Bold BI page, select the Data Sources option and click Create Data Source for the Select Connector page to pop up.
Select the MySQL Connector to connect to MySQL.
Fill the needed information to connect to MySQL.
:::Info
NOTE: MongoDB BI connector can also be connected directly to Bold BI cloud as shown in this link: How to connect MongoDB to Bold BI data source.
:::
Ensure that the MongoDB BI connector is reachable from outside networks and there are no firewall rules that block the connection.
An alternate way to establish a direct connection with MongoDB is through CData Connect Cloud. Using CData, you can access MongoDB live connection through an intermediate database. Refer to Connect Cloud documentation for more details.
# How to Sort a Column Independently of Sorting in Other Columns
Bold BI users can customize the sorting behavior of dimension fields in each widget. They can order them based on alphabetical order, the data source (default), and the field. Additionally, users can sort specific columns while ignoring sorting in other columns, as explained in this article.
Use Case
In this instance, the user would like to apply sorting to a specific column while ignoring sorting on other columns. This can be achieved by applying Alphabetic sorting on the `players` column and Data source order sorting on other columns to ignore sorting.
Sorting specific columns in the widget
By default, the sort is applied based on the first column in the grid. To apply sorting, the user must select a specific column. Only the selected column will be sorted on the widget.
Follow these steps to sort specific columns:
Click the Settings icon on the Columns, Rows, or Series section.
Navigating to sorting
On the context menu of the setting icon, select Sort. Navigating to advanced sorting option
Select the Alphabetic order in the advanced sorting options to sort the specific column.
Configuring Alphabetic Order
Click Apply to update the sorting on the widget.
Applying Alphabetic Order
The specific column sorting will be updated, as shown in the following image.
Specific sorted column
Ignoring sort in other columns in the widget
You can ignore sorting on the other columns by applying the Data source order in the Advance Sorting Options.
Follow these steps to achieve this:
Select the Data source order in the advanced sorting options to ignore any sort to the specific column.
Configuring data source order sorting
Click Apply to update the Data source order in the other columns.
Applying data source order sorting
Here the Alphabetic order is updated on the Player Name, while sorting is ignored on the Team Name and Goals, as shown in the following image.
Sorted column
# How to Change a Widget Title Dynamically Based on Label Parameters
Bold BI Application allows users to change the name of the widget’s title based on the label parameters. Users can also be able to apply the label parameter on the text widget, as explained in this article.
Using label parameters in Widgets title
This Patient Experience Analysis dashboard shows the average waiting time, the number of patients, and the average stay of a patient in the canvas with different widgets. Also, the filter widgets are added to filter the dashboard based on the department, date, and gender. So, users can include the department as the label parameter in all the applicable widgets.
Follow the steps below to add label parameters on the widget title.
Choose the column to show as a label parameter then open the properties tab and go to the Name section in the properties tab.
Widget Title Section
:::Info
Note: Label parameters can also be added to the subheading section.
:::
Specify the syntax for the label parameter as {{: Column_Name}}.If the same column name is available in more than one data source, mention the data source name before the column with the following syntax.{{:DataSourceName.Column_Name}}.
:::Info
Note: In the Bold BI application, if the valid label parameter is used, the text block will be highlighted in the widget preview.
:::
Change the widget title with the syntax mentioned above, and it will show as below.
Label Parameter Update
Add the required titles to the label parameters.
Dashboard Label Parameters
Preview the dashboard to ensure the changes.
Dashboard Preview Page
Filter the dashboard based on the department to dynamically update the widget title.
Filtered Label Parameters
:::Info
Note: In the above example, the dimension fields are used as label parameters. Users can also show the measure and date dimensions fields with various functions in the label parameter. For example, users can show the maximum number of patients or minimum waiting time in widgets using the available functions like Minimum, and Maximum. Refer to the UG documentation for more details on the available list of functions and their syntaxes for measure and dimension fields.
:::
Using label parameters in Text widget
Text widget allows users to edit and visualize the content of the formatted texts, tables, hyperlinks, and source code. Users can therefore insert label parameters on the text widget on the Bold BI application.
To add label parameters in the text widgets, follow the given steps:
Drag and drop a text widget to the Dashboard Designer as shown below:
Dashboard Designer Page
In the Patient Experience Analysis dashboard, a text widget is added to showcase the overview report for a day as shown in the following screenshot. The syntax for mentioning the label parameters in the text widget is like the syntax for using the label parameters in the widget’s title section.
Text widget
Now, the overall dashboard layout will be as follows.
Dashboard Designer Page
:::Info
Note: The text widget is configured as the slave widget to the filter widgets.
:::
Now, preview the dashboard to ensure the changes.
Dashboard Preview Page
Apply the filter in the dashboard master widgets. The content in the text widget will be dynamically changed with respect to the applied filter.
Filtered Label Parameters
# How to Configure Mail Settings in Bold BI to Receive Notifications Via Email
Users can get notifications about scheduled actions in Bold BI by email. To send email, you need to configure email settings in Bold BI. This topic explains how to configure email settings in Bold BI and get confirmation of the activities on the mail report.
Configure email settings in Bold BI
You need to configure SMTP details in the Bold BI Server to send emails, as explained on this link. Users can also track whether the email was sent to the recipients or not using the email activity logs. Logs contain information about each email, including the sender and recipient, date and time, status, and any associated error messages.
Create schedules in Bold BI
Dashboards can be configured to run at scheduled times, exported as images, and then mailed to the users in the dashboard server. Follow this link to check how to add, edit, and delete the schedules in the Bold BI.
Making schedules to run on demand
Dashboard export can be made to run on demand by using the Run Now option in the schedule grid context menu. Dashboards get exported in the format specified and sent to the recipients along with the link to the dashboard in the Bold BI by emails.
:::Info
NOTE: Dashboard export can also be scheduled to occur at selected time intervals, as explained here.
:::
Follow these steps to make schedules run on demand:
Click Schedules to navigate to the schedule listing page.
Click Actionsin the grid context menu of the schedule item, which needs to be exported, and select Run Now.
Click Run History to view the corresponding schedule status information in the schedule grid context menu.
:::Info
NOTE: Failure information can also be seen by clicking the failed link in the run history dialog box.
:::
How to get confirmation on an email sent
The email activity logs only show the status of whether the email was sent from the Bold BI server to your SMTP-configured server or not. If an email is sent from the Bold BI to your SMTP server, but the SMTP server is unable to deliver the email to the recipient, then the logs will not be shown.
Follow these steps to view the email sent status:
Click Settings icon to navigate to the settings page.
On the settings page, click Email to proceed to email settings.
Click Logs to view information on each event in the mail.
Steps to view email logs for a specific date and Dashboard Export
Open the Email Event drop-down and select Dashboard Export. The default event is All Event.
Open the Date Picker Calendar to select a specific date range. Select the certain date range that you want to filter.
Click Apply to apply the date range, as shown in the following image.
Finally, click Apply link to see the email activity logs for the selected date range and event.
Click View to check the email information which was sent and the failure reason for the failed items.
# How to Change the Branding of Bold BI
Bold BI provides a RESTful web API for Cloud and Embedded applications that allows other third-party applications to interact with Bold BI programmatically. Users can be able to customize the branding of the Bold BI Application by use of an API. Customizing Bold BI branding includes actions of changing site values.
API will support customizing branding of below items:
OrganizationName
LoginScreenLogo
EmailLogo
FavIcon
ShowCopyrightInformation
ShowPoweredBySyncfusion
Use24HourFormat
DisableUserPreference
DateFormat
TimeZone
SiteUrl and DataLanguage are only available on Embedded BI.
:::Info
NOTE: Only users who have admin rights to the site or manage site settings permission can update the site settings and make all the applicable changes to the site.
:::
Steps to customize the branding of Bold BI
:::Info
NOTE: When you sign into the Bold BI, an authentication token is provided that should be attached in the request header (Authorization) for all subsequent API calls to authenticate the requests.
:::
Follow the steps below to apply the customization branding of Bold BI:
Set up and use the Bold BI URL as below:
Embed BI:
If https:///bi/site/ is your Bold BI Embed site URL, then the API end of this site will be accessed by https://{yourdomain}/bi/api/site/
Cloud BI:
If https:///bi is your Bold BI cloud site URL, then the API end of this site will be accessed by https://{yourdomain}/bi/api
Add the following endpoint (/v4.0/settings/site) to the site URL and use the request HTTP method PUT in request Postman to update the settings. Set up the URL as shown below:
Add authorization header with a generated access token and content-type header as application/json then prepare request body with the desired branding using key and value items as shown in the following example:
```js
[
{
"Key": "OrganizationName,”
"Value": "Bold BI"
},
{
"Key": "LoginScreenLogo,”
"Value": "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",
"FileFormat": "png"
}
]
```
[
{
"Key": " SiteUrl",
"Value": "" //Include site URL here
}
]
DataLanguage
String
N/A
[
{
"Key": "DataLanguage",
"Value": "en-us"
}
]
Successful status code of 200 confirms successful settings update with a status message as shown below:
```js
{
"ApiStatus": true,
"Status": true,
"StatusMessage": "Site settings have been updated successfully"
}
```
# How to Transform Data Using Aunsight Golden Record and Create a Dashboard in Bold BI
Aunsight Golden Record is an ETL tool that can connect to any data sources like data lake and warehouses and move the data to any target databases like Microsoft SQL Server,MySQL, PostgreSQL, and more. Once the data is transferred to the target application using the Aunsight Golden Record connector, you can connect to the target application using Bold BI.
STEP 1 : In this case, you will be using a Microsoft SQL Server as a target application. You can connect to the Microsoft SQL server to fetch data using the Bold BI application with the following link.
https://help.boldbi.com/cloud-bi/working-with-data-source/data-connectors/sql-data-source/STEP 2 : After connecting to the Microsoft SQL Server data source, drag and drop the required table from the table schema in the data design view page.
Data Design pageSTEP 3 : You can preview the table data by clicking the Update button as follows.
Data previewSTEP 4 : Click Save to save the data source with a relevant name to design a dashboard.
Save Data viewSTEP 5 : You can create a dashboard using Bold BI, with the fetched data from the Microsoft SQL Server.
:::Info
Note: You can create multiple data sources to work with the single dashboard in Bold BI.
:::
STEP 6 : Once the dashboard is created, you can preview the dashboard by clicking the Preview button.
Patient Health Monitor Dashboard
# How to Hide Selected Dashboard Parameters in View Mode in Bold BI
Dashboard parameter allows users to execute the custom query or stored procedure dynamically based on the parameter while viewing the dashboard. Users can also use the parameter in the expression columns. In Bold BI, when two or more dashboard parameters are used, we can be able to hide some parameters and not editable from the design view.
Follow the steps below to execute this process
Open the Bold BI
Click the Data Sources icon to navigate to the data source page.
Dashboard Page
Select the data source with multiple dashboard parameters to edit.
Data sources Page
Click the parameter icon on the data source to navigate to the parameter dialog.
Data source Creation Page
Uncheck the Show in Viewer checkbox in the Dashboard Parameters dialog as shown below:
Dashboard Parameter Page
Click update to apply the changes.
Dashboard Parameter Page
:::Info
NOTE: The parameters with the Show in Viewer check box checked will be visible to the users in view mode while the unchecked parameter is not visible in view mode.
:::
Click the dashboard parameters icon in dashboard preview/publish mode to view the updated parameters.
# How to Use the LAG Function in a Query to Create a Dashboard in Bold BI
Bold BI allows you to create the calculated fields using SQL queries such as Excel calculated fields. Calculated fields also known as Expression will also be used to create your dashboard in Bold BI.
Calculating percentage with the previous field
In Excel
To calculate percentage value by comparing the current month value with previous month value, you need to use the following formula in Excel sheet.
You can calculate the same percentage value in Bold BI using the Custom query.
How to calculate LAG Function in Bold BI
Bold BI application uses an intermediate database to store your Excel data in the backend. So, it is possible for you to create a custom query for your dashboard which uses the Excel connection. Follow the below steps to recreate the pre-calculated KPIs of Excel in the Bold BI application.
:::Info
NOTE: We have supported intermediate databases such as SQL/Azure SQL, MySQL, and PostgreSQL.
:::
Create an Excel data source. While connecting the data source, your Excel data will be extracted and created as a table in the Intermediate database which you have used in the Data Store Settings.
Drag and drop your table in Design canvas and switch to Code View.
```js
SELECT
[Sheet1].[Metric],] AS [Metric],
[Sheet1].[Visits],AS [Visits],
[Sheet1].[Visits vs Prev Visits], AS [Visits vs Prev Visits]
[Sheet1].[Pages per visit] AS [Pages per visit],
[Sheet1].[Page per visit vs Prev page per visit] AS [Page per visit vs Prev page per visit],
[Sheet1].[Users] AS [Users],
[Sheet1].[Users vs prev users] AS [Users vs prev users],
[Sheet1].[Comments] AS [Comments],
[Sheet1].[Comments Vs Prev comments] AS [Comments Vs Prev comments],
[Sheet1].[Total] AS [Total],
[Sheet1].[Total vs Prev total] AS [Total vs Prev total],
[Sheet1].[Search engines] as [Search engines]
```
Use LAG analytic function to access the data from the previous row and add it as a virtual column using the queries as follows:
SQL:
```js
SELECT
[Sheet1].[Metric],] AS [Metric],
[Sheet1].[Visits],AS [Visits],
LAG([Sheet1].[Visits], 1,null) over (order by [sheet1].[Metric] as Prevvisits,
[Sheet1].[Pages per visit] AS [Pages per visit],
LAG([Sheet1].[Pages per visit], 1,null over (order by [sheet1].[Metric] as [PrevPagesPerVisit],
[Sheet1].[Users] AS [Users],
LAG([Sheet1].[Users], 1,null over (order by [sheet1].[Metric] as [PrevUsers],
[Sheet1].[Comments] AS [Comments],
LAG([Sheet1].[Comments], 1,null over (order by [sheet1].[Metric] as [PrevComments],
[Sheet1].[Total] AS [Total],
LAG([Sheet1].[Total] 1,null over (order by [sheet1].[Metric] as [PrevTotal],
[Sheet1].[Search engines] AS [Search engines],
[Sheet1].[Referring sites] AS [Referring sites],
[Sheet1].[Direct] AS [Direct],
[Sheet1].[Other] AS [Other],
[Sheet1].[Desktop] AS [Desktop],
LAG([Sheet1].[Desktop] 1,null over (order by [sheet1].[Metric] as [PrevDesktop],
```
MySQL:
```js
SELECT
‘Sheet1’.’48f140d2=005e-4585-ac38-783123b9c45a’ AS ‘ Metric’
‘Sheet1’.’1e9952a6-cof4-4ab6-b4da-43c3c587e79a’ AS ‘ Visits’
LAG(‘Sheet1’.’1e9952a6-cof4-4ab6-b4da-43c3c587e79a’,1,null) over (order by ‘sheet1’. ‘48f140d2=005e-4585-ac38-783123b9c45a’) as ‘PrevVisits’,’Sheet1’,’effc9b10-6259-4529-8139-4d0de4220f52’ AS ‘ Pages per visit’,
LAG(‘Sheet1’.’effc9b10-6259-4529-8139-4d0de4220f52’,1,null) over (order by ‘sheet1’. ‘48f140d2=005e-4585-ac38-783123b9c45a’) as ‘PrevPagesPerVisit’,’Sheet1’,’02959d00-8072-44f2-97a5-0c99b6a9b367’ AS ‘Users’,
LAG(‘Sheet1’.’02959d00-8072-44f2-97a5-0c99b6a9b367’,1,null) over (order by ‘sheet1’. ‘48f140d2=005e-4585-ac38-783123b9c45a’) as ‘PrevUsers’
FROM ‘Datasource_ba0286b2-313-4e02-bcdc-f497df462a19’.’Sheet1’ AS ‘Sheet1’
```
PostgreSQL:
```js
SELECT
“Sheet1”.”48f140d2=005e-4585-ac38-783123b9c45a” AS “ Metric”
“Sheet1”.”1e9952a6-cof4-4ab6-b4da-43c3c587e79a” AS“ Visits”
LAG(“Sheet1”.”1e9952a6-cof4-4ab6-b4da-43c3c587e79a”,1,null) over (order by “sheet1”. “48f140d2=005e-4585-ac38-783123b9c45a”) as “PrevVisits”,”Sheet1”,”effc9b10-6259-4529-8139-4d0de4220f52” AS “ Pages per visit”,
LAG(“Sheet1”.”effc9b10-6259-4529-8139-4d0de4220f52”,1,null) over (order by “sheet1”. “48f140d2=005e-4585-ac38-783123b9c45a”) as “PrevPagesPerVisit”,”Sheet1”,”02959d00-8072-44f2-97a5-0c99b6a9b367” AS “Users”,
LAG(“Sheet1”.”02959d00-8072-44f2-97a5-0c99b6a9b367”,1,null) over (order by “sheet1”. “48f140d2=005e-4585-ac38-783123b9c45a”) as “PrevUsers”
FROM “Datasource_ba0286b2-313-4e02-bcdc-f497df462a19”.”Sheet1” AS “Sheet1”
```
Configure the added virtual column in widgets as follows.
Go to the Properties tab of the Grid widget and added KPI columns to show the computed values. Click Add button under Columns Settings to add the KPI columns to your widgets.
Add the KPI Expression as follows.
You can add N number of KPI Expression column by clicking Add button.
The following grid widget is the sample widget which shows the comparison of the current month and previous month values in percentage, and they are equivalent to the Excel data.
You can also configure more widgets to show overall percentage of a column, the number of new visits count, page visits, new users count, new comments count, and more to create your dashboard.
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this widget, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Selecting the Column Chart Widget
Once you have chosen a data source, you can start selecting widgets. I am going to create one of the most popular widgets, a column chart.
After I drag and drop the column chart from the “Comparison” section of the widget menu to my dashboard, it looks like this.
Assigning the Data to Column Chart Widget
Now that I have moved the widget to my dashboard, I can assign data to it and customize its appearance. Resizing the widget is a good first step. Simply grab the edge of the box and drag it until it is the size you would like.
When you are ready to assign data to the widget, select it; then, click the “Properties” icon in the upper right corner of the widget.
Two tabs will appear: “Properties” and “Assign Data.” I want my widget to display the top goal scorers from the World Cup, so under the “Properties” tab. Hence, I am going to change the name of my widget from the default “Chart1” to “Top Goal Scorers.”
For my purposes, a single title is sufficient, but you can add a subtitle and even a description of the widget if you like.
Then, I will click the “Assign Data” tab. You can drag different pieces of data to different parts of the widget (in this case, its columns) to display the statistics that interest you. I would like my column chart to display the top goal scorers, so I need to figure out how to make my widget show that information.
First, I will drag the “PlayerName” field to the “Columns” box. This ensures that each column will represent a player name.
Next, I will drag the “Goals” field to the “Values” box. This ensures that the value being displayed is the number of goals scored by each player.
My widget was created successfully, but as you can see, it is a bit unwieldy and difficult to read because it contains so much information. It would be helpful if I narrowed down the data that I would like to display.
Narrowing Down the Data for Column Chart Widget
With Bold BI’s Dashboard, it is easy to filter data by virtually any criteria you like. In the “Assign Data” tab, select the “Options” button that appears beside the relevant field. In this case, I want my widget to display fewer player names, so that is the field I need to work with.
After you click the “Options” button, click “Filter(s).” This will allow you to filter the data according to your desired criteria.
In order to display the top six goal scorers, I simply need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Goals.”
This ensures that my data will be filtered such that the widget will only display the top six goal scorers.
The Finished Column Chart Widget
As you can see, my widget now displays only the number of goals scored by each of the top six goal scorers.
It is also worth noting that hovering over each individual bar will display the player’s full name and the total number of goals they scored. Though this data is easy to read because the numbers are fairly low, this feature is very helpful when you are looking at larger numbers (such as sales figures).
If you would like the bars of your widget to be displayed horizontally rather than vertically, you can build a bar chart widget using exactly the same steps that are outlined above.
The bar chart and column chart widgets both compare values for a set of items; the only difference between them is that the column chart uses vertical bars while the bar chart uses horizontal bars.
# How to Create a Stacked Bar or Column Widget
Getting Started with Stacked Bar or Column Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Selecting the Stacked Bar Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a stacked bar widget. These kinds of widgets are particularly useful because they allow you to compare multiple pieces of information in the same widget.
Assigning the Data to Stacked Bar Widget
In this widget, I would like to be able to see the total number of goals scored by teams compared to the total number of shots they took. In order to make my widget easy to read, I am going to display the information of only the top six goal-scoring teams.
First, I need to drag the stacked bar widget from the “Comparison” section of the widget menu onto my dashboard. I am going to resize it by dragging its edges so that it will be easy to read. This is what my stacked bar widget looks like before I have assigned data to it.
Now that I have moved the widget to my dashboard, I can assign data to it and customize its appearance. First, I will click the “Properties” icon in the upper right corner of the widget.
Next, I will click the “Properties” tab and rename the widget “Goals and Shots by Team.”
Finally, I will click the “Assign Data” tab. I know that I want my data to be organized according to the different teams that played in the World Cup, so I am going to drag the “TeamName” field over to the “Columns” box.
I also know that there are two pieces of data I want to compare: the number of goals each team scored and the number of shots they took. To achieve this, I need to drag those two fields to the “Values” box.
My widget has now been created, but I am going to customize it further.
Customizing the Stacked Bar Widget
First, I want to narrow the scope of my widget so that it only displays the top six goal-scoring teams. To achieve this, I simply need to filter the data.
In the “Assign Data” tab, I will click the “Options” button that appears beside the relevant field. In this case, I want to filter the data that relates to teams, so I will select the “Options” button for the “TeamName” field. After clicking the “Options” button, I will click “Filter(s).” This will allow me to filter the data according to my desired criteria.
In order to display the top six goal-scoring teams, I simply need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Goals.”
This ensures that my data will be filtered such that the widget will only display the top six goal-scoring teams.
After I have filtered the data using the “TeamName” field, my widget looks like this.
Remember that the “Goals” measure is currently placed above the “Shots” measure in the “Values” box. However, the widget’s appearance will change depending on where you place the fields in the “Values” box.
For example, if I move the fields in the “Values” box so that the “Shots” measure appears above the “Goals” measure, my widget looks like this.
As you can see, changing the order of the fields in the “Values” box changes the way the data is displayed on the widget. In the first screenshot, goals are represented by the color blue, and they appear first in the bar. In the second screenshot, goals are represented by the color red, and they appear second in the bar.
I would like goals to display first in my widget’s bars, so I am going to move the “Goals” value so that it sits above the “Shots” value as it originally did. However, this is just another example of how customizable Bold BI’s widgets are.
Finally, I am going to add one more customization to my stacked bar widget: a multi-level drill down option. As the name implies, this option will allow me to drill down my data even further by displaying another level of information.
In this case, I would like to modify my widget so that if I click on a team’s bar (which shows the team’s total number of goals and shots), I can see a breakdown of which players on the team took shots and scored goals.
Making this customization will require me to change the data that is associated with my bars, so I need to navigate to the “Columns” box under the “Assign Data” tab. Currently, the only field in the “Columns” box is the “TeamName” field. If I would like my widget to display individual players’ statistics, I need to add the “PlayerName” field.
When I drag the “PlayerName” field to the “Columns” box, a pop-up appears asking if I want to enable multi-level drill down.
After I click “Yes,” my “Columns” box looks like this.
My widget has not changed its appearance; it still looks the same as it did before. However, because I have enabled multi-level drill down and have added the “PlayerName” field beneath the “TeamName” field, the functionality of my widget has changed. I can test the widget by clicking the “Preview” button in the upper right corner of my dashboard and navigating to the stacked bar widget.
Previously, the bars on my widget were not clickable. If I hovered over a bar, I could see the team’s number of goals or shots, but nothing happened if I clicked the bar itself.
Now that I have enabled multi-level drill down, I can click each bar of the widget to display additional information. In this case, I added the “PlayerName” field, so I will be able to see additional information about individual players.
As you can see, when I hover over a bar on the widget, I am still able to see the team’s number of goals or shots. Now, though, diagonal lines appear, indicating that I can click the bar to view additional information.
For example, if I click Belgium’s bar, I am able to see statistics for all six of the Belgian players who have taken shots and scored goals.
My drilled-down widget display has the same functionality as the main widget. If I hover over a bar, I am able to see the player’s full name, along with the total number of shots they took or goals they scored.
The drill up feature allows you to return to the previous view by clicking on the **“TeamName”** in the above widget.
As you can see, the multi-level drill down feature is extremely useful if you need to see multiple pieces of big-picture data (such as the sales numbers from several divisions) but also need access to more detailed information (such as the numbers for individual sales reps or a breakdown of the different products that each division has sold).
Multi-level drill down is available with 15 different Bold BI widgets. All of the widgets in the Comparison, Proportion, and Distribution sections of the widget menu offer this feature, allowing you endless customization options.
# How to Create a Bubble Map Widget
Getting Started with Bubble Map Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Bubble Map—South America Census Data” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Bubble Map Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a bubble map widget.
These widgets allow you to display quantitative values that are encoded through bubble size. They use different bubble sizes to represent differences in the data being displayed.
Assigning the Data to Bubble Map Widget
First, I need to drag the bubble map widget from the “Relationship” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my bubble map widget looks like before I have assigned data to it.
I would like my widget to display population data for the continent of South America, and now that I have moved the widget to my dashboard, I can assign data to it. First, I will click the “Settings” icon in the upper right corner of the widget.
Next, I will click the “Properties” tab and change the widget’s name from “BubbleMap1” to “South America Population Data.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the population of each country in South America, so I will drag the “Population” field to the “Values” box and the “Country” field to the “Shapes” box.
My widget now shows a bubble map of South America, and if I hover over a particular country, I can view its population data.
Customizing the Bubble Map Widget
Now that my widget displays the information I want it to display, I am going to click the “Properties” tab to customize my map.
If I scroll down to the “Basic Settings” section, I see that I have the option of changing my bubble color. I can click the arrow in the “Bubble Color” box to change the color scheme of my map. I can choose a preselected color, or I can click the “Switcher” box in the lower left corner to create a custom color.
In this case, I have changed my bubble color to a custom shade of teal.
The “Basic Settings” section also offers me the option of changing my map’s appearance. A map of the world (“WorldMap Countries”) is selected by default; however, if I click the “Map” drop-down list box, I can choose from a variety of different national and continental maps.
Because I am only looking at data for South America, I am going to select the South America map option. My widget’s map immediately changes from a map of the world to a map of South America.
Now that my widget looks the way I want it to look, I can test its functionality by hovering over a few countries to see their population data.
# How to Create a Choropleth Map Widget
Getting Started with Choropleth Map Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Choropleth Map—South America Census Data” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Choropleth Map Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a choropleth map widget.
These widgets allow you to display quantitative values that are encoded through a color scale. They use different colors or shades to represent differences in the data being displayed.
Assigning the Data to Choropleth Map Widget
First, I need to drag the choropleth map widget from the “Relationship” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my choropleth map widget looks like before I have assigned data to it.
I would like my widget to display population data for the continent of South America, and now that I have moved the widget to my dashboard, I can assign data to it. First, I will click the “Settings” icon in the upper right corner of the widget.
Next, I will click the “Properties” tab and change the widget’s name from “ChoroplethMap1” to “South America Population Data.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the population of each country in South America, so I will drag the “Population” field to the “Values” box and the “Country” field to the “Shapes” box.
My widget now shows a color-coded map of South America, and if I hover over a particular country, I can view its population data.
Customizing the Choropleth Map Widget
Now that my widget displays the information I want it to display, I am going to click the “Properties” tab to customize my map.
If I scroll down to the “Basic Settings” section, I see that I have the option to add a legend to my widget. The legend illustrates the color shades that correspond with certain numbers. I have decided not to add a legend to my widget, but you can see what it looks like here.
The “Basic Settings” section also offers me the option of changing my map’s appearance. A map of the world (“WorldMap Countries”) is selected by default; however, if I click the “Map” drop-down list box, I can choose from a variety of different national and continental maps.
Because I am only looking at data for South America, I am going to select the South America map option. My widget’s map immediately changes from a map of the world to a map of South America.
Finally, if I continue scrolling to the “Range Color Settings” section of the “Properties” tab, I can click the arrow in the “Monochromatic” box to change the color scheme of my map.
I can choose a preselected color, or I can click the “Switcher” box in the lower left corner to create a custom color.
If I change my map’s color to a custom color, it immediately changes its appearance.
Now that my widget is complete, I can hover over each country on the map to see its population data.
# How to Create a Heat Map Widget
Getting Started with Heat Map Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Heat Map-Weather Report” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Heat Map Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a heat map widget.
These widgets allow you to visualize large amounts of data as clustered rectangles with a color scale.
Assigning the Data to Heat Map Widget
First, I need to drag the heat map widget from the “Relationship” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my heat map widget looks like before I have assigned data to it.
Next, I will click the “Settings” button in the upper right corner of the widget. I will then click the “Assign Data” tab.
I would like my heat map to display the average temperature for five states in the southeastern US: Mississippi, Alabama, Florida, Georgia, and South Carolina.
Thus, I will drag the “Avg Temperature” field to the “Value” box.
I am going to leave the “Size” box empty for now, but we will return to it later.
Finally, I will drag the “Date” field to the “X-Axis” box and the “State” field to the “Y-Axis” box.
My heat map has now been created, but it is clear that I need to filter my data to make the widget display the information I would like to see.
Customizing the Heat Map Widget
In order to modify the data that my widget displays, I need to adjust the settings of the fields that I dragged to the “X-Axis” and “Y-Axis” boxes.
The “Values” box already contains the information I need (the states’ average temperatures), so I do not need to alter it.
However, I do need to modify the settings of the “X-Axis” and “Y-Axis” boxes because they affect the dates and states that the widget displays, and this is the information I would like to change.
I will begin by looking at the “Date” field in the “X-Axis” box. After I dragged this field to the “X-Axis” box, its name changed to “Year(Date)” as the widget will display the data in this format by default.
However, I want my widget to show all of the months of the year, so I am going to click the “Options” button and select the “Month” option.
Now, the field’s name has changed to “Month(Date).”
Next, I will adjust the “State” field in the “Y-Axis” box by clicking the “Options” button and then clicking “Filter(s).”
At the top of the box that appears, I see a drop-down list box called “List.” Currently, every state in the US is selected; however, I can uncheck the “Check All” button and then manually select the states for which I would like to see data.
I am going to check the boxes beside Alabama, Florida, Georgia, Mississippi, and South Carolina, ensure that the “Include” button is selected, and click “Apply.”
After I click “OK” to exit the “Filters” box, my widget looks like this, and if I hover over a rectangle, I can see the average monthly temperature for that state. I am definitely on the right track, but there are a few additional modifications I would like to make.
To do this, I will click over to the “Properties” tab. First, I am going to rename my widget. I will call it “Average Monthly Temperatures—Southeastern US.”
Next, I am going to scroll down to the “Color Settings” section. This section contains two options for my widget’s color scale. The “Min Color” box determines which color is associated with lower values, and the “Max Color” box determines which color is associated with higher values.
Because I am working with temperatures, and because I would like to see a stark contrast between the lowest and highest values on my heat map, I am going to change these colors so that blue is my Min Color and red is my Max Color.
To do this, I need to click the down arrow in the Min Color box and then select the shade of blue I would like to use.
It is worth noting that you can click the “Switcher” button in the lower left corner of the box to create your own custom colors, but I am going to choose a shade of blue from the default options that appear and then click “Apply.”
Next, I will click the down arrow in the Max Color box, select a shade of red, and then click “Apply.”
I would also like to change the name of my heat map’s X-Axis. If I scroll down past the “Color Settings” section, I see a section titled “X-Axis Settings.” Currently, my axis title is “Month(Date),” which is the name of the field that I dragged to the “X-Axis” box in the “Assign Data” tab.
I am going to revise the text in this box so that it says “2017,” which is the year for which I am displaying data. I can immediately see this change reflected in my widget.
Now that my widget looks the way I want it to look, I am going to take a moment to explore its functionality.
As you can see, the heat map’s rectangles are shaded in different hues of red and blue. The hottest months are bright red, and the coldest months are bright blue. Months with temperatures in between the highest and lowest temperatures are a mix of the colors, with warmer months having more red and cooler months having more blue.
I can hover over any individual rectangle to see a state’s average monthly temperature. For example, I can see that Alabama’s average temperature in December was 46°F and that Florida’s average temperature for the same month was 66°F.
Finally, I would like to explore the functionality of the “Size” box that appears under the “Assign Data” tab. I left this box empty when I created my widget because I wanted my widget to display clustered rectangles. However, it is worth noting that adding a field to the “Size” box will allow you to change the appearance and functionality of your heat map.
If you drag a field to the “Size” box, the heat map’s rectangles will disappear, and the map will instead display dots of different sizes; these dots represent your data, and the field that you drag to the “Size” box determines the criteria for the dot sizes.
For example, if I drag the “Avg Temperature” field to the “Size” box, larger dots will represent higher average temperatures, and smaller dots will represent lower average temperatures.
The dots are still color-coded; the hottest months are still bright red, the coldest months are still bright blue, and months with temperatures in between the highest and lowest temperatures are a mix of the colors, with warmer months having more red and cooler months having more blue. Now, though, my widget does not merely display information through the dots’ colors; it also conveys information through the dots’ sizes.
Here is a final example. If I drag the “Avg Precipitation” field to the “Size” box, then larger dots will represent higher amounts of precipitation, and smaller dots will represent lower amounts of precipitation. The colors red and blue still indicate which months had the highest and lowest temperatures. Now, however, I am also able to quickly see which states and months had the highest and lowest precipitation numbers by looking at the widget’s dot sizes.
As you can see, this functionality can be very useful as it provides a quick visual reference for not one but two pieces of data simultaneously (in this case, the states’ average temperatures and average precipitation, with the average temperature represented by color and the average precipitation represented by dot size).
# How to Create a Grid Widget
Getting Started with Grid Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Selecting the Grid Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a grid widget. These widgets allow you to display and sort tabular data in a straightforward, easy-to-read manner.
Assigning the Data to Grid Widget
First, I need to drag the grid widget from the “Relationship” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my grid widget looks like before I have assigned data to it.
I would like my widget to display the number of goals scored by each player in the World Cup, and now that I have moved the widget to my dashboard, I can assign data to it. First, I will click the “Settings” icon in the upper right corner of the widget.
Next, I will click the “Properties” tab and change the widget’s name from “Grid1” to “Goals Scored by Player.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the number of goals scored by each player in the World Cup, so I will drag the “PlayerName” and “Goals” fields over to the “Columns” box.
Changing the order of the fields in the “Columns” box will change the order of the columns on the widget. I would like the players’ names to display in the first column on my widget, so I will leave the fields in their current positions in the “Columns” box.
Now that my widget displays the desired information, I will customize it further and test its functionality.
Customizing the Grid Widget
If I click over to the “Properties” tab of the widget settings menu, I will find several widget customization options.
In the “Basic Settings” section, I can choose whether I would like to allow sorting (this option is selected by default, and we will explore it in more detail later). I can also choose whether I would like my widget to allow me to click through multiple pages and whether I would like the horizontal and vertical lines of my table to be visible. In the “Header Settings” section, I can even change the background color and font color of my header.
After experimenting with these settings, I have decided to change my header background color to a custom shade of green by clicking the down arrow in the “Background” color box, selecting the “Switcher” box in the bottom left corner, and moving the cursor around the color swatch. I have also decided to remove the horizontal lines from my widget.
My widget now looks like this.
I would like to test the widget’s sorting functionality, but before I do, there is one more thing I would like to change. Currently, the columns of my widget display the names of the fields that I dragged to the “Columns” box (“PlayerName” and “Sum Of Goals”).
The column names accurately reflect the data they display, but they are field names—they are not the titles I would ordinarily give to my columns.
To revise my column names, I can scroll down to the “Column Settings” section of the “Properties” tab and click the “Edit Column Names” button. I can then type in the new column names and click “OK,” and the column names on my widget immediately change.
Now, I would like to test my widget’s sorting functionality. If I choose to allow sorting in the “Basic Settings” section of the “Properties” tab, I can sort my data according to either of the columns in my widget.
I can sort by the players’ names in ascending or descending order, or I can sort by the number of goals that were scored in ascending or descending order. To do this, I simply need to click anywhere in the header for the column by which I would like to sort.
For example, if I want the widget to display the most goals scored in descending order, I can click the “Goals” header. My first click displays the goals in ascending order, which is not what I want.
However, if I click the “Goals” header again, the goals will be displayed in descending order.
If you prefer to sort your data by player name, you can click the “Player” heading to display the names in ascending or descending alphabetical order.
As you can see, the simple but powerful grid widget allows you to easily display and sort key pieces of data, and you can even filter the data itself to customize the information the widget displays.
For example, if I want my widget to display only the top ten goal scorers in the World Cup, I can navigate back to the “Assign Data” tab, click the “Options” button that appears beside the “PlayerName” field, and click “Filter(s).”
Then, I can click the “Rank” checkbox, select “Top” from the “Mode” drop-down list box, change the “Count” option to 10, change the “Column” drop-down list box to “Goals,” and click “OK.”
Now, my widget will display only the top ten goal scorers from the World Cup. However, filtering the data has changed my sorting settings, so I will once again click the “Goals” header to sort by the number of goals that were scored in descending order.
# How to Create a Tree Map Widget
Getting Started with Tree Map Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Comparison Chart—Olympic Medals” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Tree Map Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a tree map widget.
These widgets allow you to display large amounts of data as clustered rectangles with a color scale.
Assigning the Data to Tree Map Widget
First, I need to drag the tree map widget from the “Relationship” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my tree map widget looks like before I have assigned data to it.
Next, I will click the “Settings” button in the upper right corner of the widget and click the “Assign Data” tab.
I would like my widget to display the gold and silver medals earned by each country, so I will drag the “Gold” and “Silver” fields to the “Values” box and the “Country” field to the “Columns” box.
My tree map has now been created, but it is a bit difficult to read due to the sheer amount of data it displays. Thus, I am going to filter my data to make my widget more manageable.
Customizing the Tree Map Widget
I would like my tree map to display data for the 15 countries that earned the most gold medals. To filter my data, I need to click the “Options” button that appears beside the “Country” field in the “Columns” box. I can then click “Filter(s).”
Next, I need to click the “Rank” checkbox, select the “Top” option from the “Mode” drop-down list box, change the “Count” option to 15, select the “Gold” option from the “Column” drop-down list box, and click “OK.” Now, my tree map only displays data for the 15 teams that earned the most gold medals.
:::Info
Note: As you create your tree map, you may notice that some rectangles are not displaying the information they should. For example, in the screenshot to the right, five of the rectangles are not displaying countries’ names.
:::
At the widget’s current size, there is not room in these rectangles to display the countries’ names. To fix this issue, simply resize your widget by dragging its edges.
As you can see, each rectangle displays a country name in the resized widget.
Now that my tree map displays the data I want it to display, I can click the “Properties” tab to further customize the widget. First, I am going to change the widget’s name from “TreeMap1” to “Top 15 Gold Medal Countries.”
Then, I am going to scroll down to the “Range Color Settings” section to explore my color scheme options.
The “Color Type” drop-down list box offers two options: “Monochromatic” (which is selected by default) and “Range Color.”
If the color type is set to monochromatic, I can click the arrow in the “Monochromatic” box to change the tree map’s color. I can choose a preselected color, or I can click the “Switcher” box in the lower left corner to create a custom color.
For example, I could change my tree map color to a custom shade of green.
Alternatively, I can change the “Color Type” drop-down list box to “Range Color.” Now, the widget will assign different colors to different ranges of data in the tree map.
By default, the rectangle with the highest value will be yellow. Rectangles in the middle of the value range will be red, and rectangles at the low end of the value range will be blue.
You can easily change the colors for the low, middle, and high value ranges by clicking the arrows in their respective boxes (just as I did when I changed the tree map’s color from blue to green when the color type was set to monochromatic).
Finally, I am going to test my widget’s functionality. Whether I set the “Color Type” drop-down list box to “Range Color” or “Monochromatic,” I will be able to see the data for any given country by hovering over it with my mouse.
# How to Create a Card Widget
Getting Started with Card Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Card—Product Sales” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Card Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a card widget.
These widgets allow you to measure trends through key performance indicators, such as actual values and target values.
Assigning the Data to Card Widget
First, I need to drag the card widget from the “Deviation” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read. This is what my card widget looks like before I have assigned data to it.
I know that card widgets allow me to quickly and easily compare certain pieces of data (such as my sales goal versus my actual sales for the month). I also know that, while I obviously want to sell as many of my products as possible, those sales do not do me much good if my customers are not paying for their orders.
Thus, in this widget, I would like to contrast the total dollar amount of my overall sales with the total dollar amount of payments I have received. This will allow me to see how much money I have actually received from customers and how much I still need to collect.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Actual Values,” “Target Values,” and “Series” boxes in the right column.
I want to compare the total dollar amount of payments I have received with the total dollar amount of payments I am owed. To do this, I need to drag the “Amount Paid” field to the “Actual Values” box and the “Amount” field to the “Target Values” box.
Finally, I am going to drag the “Sales Type” field to the “Series” box (we will explore what happens if you add the “Product Name” field to the “Series” box later).
In this case, all of my sales are online, but it is still useful to add this field. For one thing, my widget now specifically notes that these numbers represent online sales, and for another, if I ever add another type of sale to my data source, my widget will be updated accordingly.
Customizing the Card Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “Sum of Amount Paid vs Sum of Amount” to “Payments Received vs Total Sales.”
Next, I will scroll down to the “Basic Settings” section and locate the “Secondary Value Type” drop-down list box. Selecting the “Variation” or the “Target Value” option will change my widget’s appearance.
“Variation” is selected by default. When this option is selected, the widget shows the following information:
The dollar amount of payments I have received ($37,122)
The dollar amount of payments I have not received ($5,500)
The percentage of total sales dollars for which I have received payment (87.1%)
If I select “Target Value,” the widget shows the following information:
The dollar amount of payments I have received ($37,122)
The dollar amount of total sales ($42,622)
The percentage of total sales dollars for which I have received payment (87.1%)
For this example, I am going to select the “Variation” secondary value type.
As I continue to scroll down the “Properties” column, I see a section titled “Behavior.” In this section, I can choose whether I would like a high value to be a positive or negative indicator. The box is checked by default, but if I uncheck it, some of the numbers in my widget will change from red to green.
In this case, a high value would initially seem to be positive; after all, I want to receive payment for my sales, so if I have received payment for 87% of my sales, that is a good thing. Even so, because I have not received payment for 100% of my sales, I want this number to stay red. Thus, I will leave the box checked.
The “Behavior” section also contains a drop-down list box called “Primary Value Type.” By default, the “Percent of Target” option is selected, but selecting different options from this drop-down list box will allow me to further customize my widget by either changing the information it displays or changing the order in which certain pieces of data are arranged.
We will now explore each of the five options in this drop-down list box to see how they alter the card widget’s appearance.
Absolute Difference
If I select the “Absolute Difference” option in the “Primary Value Type” drop-down list box, my widget displays the following information:
The dollar amount of payments I have received ($37,122)
The percentage of total sales dollars for which I have not received payment (12.9%)
The dollar amount of payments I have not received ($5,500)
This option highlights the total dollar amount of payments that I have yet to receive, which is $5,500.
Percent of Difference
If I select the “Percent of Difference” option in the “Primary Value Type” drop-down list box, my widget displays the following information:
The dollar amount of payments I have received ($37,122)
The dollar amount of payments I have not received ($5,500)
The percentage of total sales dollars for which I have not received payment (13.79%)
This option emphasizes the fact that I have not received payment for 13.79% of my total sales.
Percent of Target
If I select the “Percent of Target” option in the “Primary Value Type” drop-down list box, my widget displays the following information:
The dollar amount of payments I have received ($37,122)
The dollar amount of payments I have not received ($5,500)
The percentage of total sales dollars for which I have received payment (87.1%)
This option highlights the fact that I have received payment for 87.1% of my total sales.
Actual Value
If I select the “Actual Value” option in the “Primary Value Type” drop-down list box, my widget displays the following information:
The percentage of total sales dollars for which I have not received payment (13.79%)
The dollar amount of payments I have not received ($5,500)
The dollar amount of payments I have received ($37,122)
This option clearly illustrates that I have received a total of $37,122 in payments.
Percent of Change
If I select the “Percent of Change” option in the “Primary Value Type” drop-down list box, my widget displays the following information:
The dollar amount of payments I have received ($37,122)
The dollar amount of payments I have not received ($5,500)
The dollar amount of payments I have not received ($5,500) divided by the dollar amount of payments I have received ($37,122), which is 12.90%.
This percentage value represents the difference between the “Sum(Amount)” and the “Sum(Amount Paid)” fields divided by the “Sum(Amount Paid)” field. Though it is not particularly useful for my purposes, it is worth keeping in mind in case you would like to use it in the future.
Now that I have seen the five different display options that are available for my card widget, I need to choose the one that is the best fit for my needs. I know that the “Percent of Change” option is not the best fit for the information I want to present, so I essentially have four options.
I can choose to emphasize the total amount of outstanding payments as either a numeric value or a percentage value ($5,500 or 12.9%). The “Absolute Difference” and “Percent of Difference” options would allow me to do this.
Alternatively, I can choose to highlight the total amount of payments I have received as either a numeric value or a percentage value ($37,122 or 87.1%). The “Percent of Target” and “Actual Value” options would allow me to do this.
I have decided to use the “Percent of Target” primary value type as I would like to easily see the percentage value of sales for which I have received payment. My completed card widget looks like this.
It is also worth noting that no matter which customization options you choose, you can always hover over your widget to obtain the key pieces of information you have chosen to display.
In this case, I can hover over my widget to see the dollar amount of payments I have received, the dollar amount of total sales, the dollar amount of payments I have not received, and the percentage of sales for which I have received payment.
Though my card widget now displays the information I want to highlight, there is one additional customization I can make so that the information will be even more detailed.
Right now, the widget shows my total sales numbers. This is because when I assigned data to the widget, I moved the “Sales Type” field into the “Series” box. Thus, my data is technically sorted by sales type, but as all of my sales are online sales, there is only one category. This means that the card widget simply shows the total amount of all of my sales.
However, if I add the “Product Name” field to the “Series box,” my data will be sorted according to the different products I offer.
After I drag the “Product Name” field to the “Series” box, my card widget immediately changes its appearance. It still displays the same information (the information I selected when I chose the “Percent of Target” primary value type). Now, however, the widget sorts the data by product.
I can now see the dollar amount of payments received, the dollar amount of outstanding payments, and the percentage values of sales dollars for which I have received payment for each product category.
If I would like to change anything else about my widget’s appearance—if I would like to change the color of high values from red to green, for example, or if I would like to update the primary or secondary value type drop-down list boxes to change the information that the widget displays—I need only click the “Properties” tab and follow the steps that we previously reviewed.
As a final example, let us say that I would like to change the “Primary Value Type” field from “Percent of Target” to “Percent of Difference.”
After I select “Percent of Difference” from the “Primary Value Type” drop-down list box, I am going to resize my widget by dragging its edges so that I can see all of my data without having to scroll.
In each product’s rectangle, I can see the dollar amount of payments received, the dollar amount of outstanding payments, and the percentage values of sales dollars for which I have not received payment for each product category.
# How to Create a Doughnut or Pie Chart Widget
Getting Started with Doughnut or Pie Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Selecting the Doughnut Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a doughnut widget.
These widgets allow you to highlight the proportional distribution of certain pieces of data in the form of doughnut slices.
Assigning the Data to Doughnut widget
First, I need to drag the doughnut widget from the “Proportion” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my doughnut widget looks like before I have assigned data to it.
Next, I am going to click the “Settings” button in the upper right corner of the widget. I would like my doughnut widget to display assist data for the World Cup, so I am going to click the “Properties” tab and rename my widget. I want my widget to show data for both teams and individual players (I can achieve this by using the multi-level drill down option, which we will explore later), so I will call it “Assists by Team and Player.”
Now, I am ready to assign data to my widget by clicking the “Assign Data” tab. If I would like to see teams’ assist data, I need to drag the “Assists” field to the “Values” box and the “TeamName” field to the “Columns” box.
After I drag the “TeamName” field to the “Columns” box, my widget is created, but it looks cluttered because it contains so much information. I will now customize the widget to make its data easier to read.
Customizing the Doughnut Widget
I know that this widget offers the multi-level drill down option, so now that I have organized the data by team, I would like to add a drill-down option that will allow me to see specific players’ data.
However, before I add the drill-down option, I would like to filter the existing data to make my widget easier to read.
To do this, I simply need to click the “Options” button for the “TeamName” field and click “Filter(s).”
Then, I need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to the desired number. Finally, I need to change the “Column” drop-down list box to “Assists.”
Now, my widget only shows the six teams with the most assists in the World Cup.
Next, I am going to add the multi-level drill down option to my widget. As its name suggests, this function allows me to add another layer of data to my widget.
In this case, I would like to modify my widget so that if I click on a team’s doughnut segment, I can see a breakdown of which players on the team had assists.
Making this customization will require me to change the data that is associated with my doughnut segments, so I need to navigate back to the “Columns” box under the “Assign Data” tab. If I want my widget to display information for players as well as teams, I need to drag the “PlayerName” field to the “Columns” box.
When I try to do so, a pop-up appears asking if I want to enable multi-level drill down.
After I click “Yes,” my “Columns” box displays the “PlayerName” field beneath the “TeamName” field, and multi-level drill down has been enabled. We will explore this feature’s functionality soon, but before doing so, I want to ensure that my widget looks the way I want it to look.
Right now, my doughnut’s segments are each associated with a percentage value. Though percentage values can be useful in many situations, they do not really suit my purposes, so I would like to replace them. I would also like to display a key or guide of some sort so that I know which team each color represents without hovering over each segment.
To achieve this, I can click the “Properties” tab. If I scroll down to the “Basic Settings” section, I can click the “Show Legend” option. My doughnut widget immediately displays a guide demonstrating which segment colors are associated with which teams.
I would still like to remove the percentage values from the widget, and in the “Basic Settings” section, I see a drop-down list box called “Data Label.” Currently, the “Percentage” option is selected.
If I select the “Value” option instead, my widget will replace the percentage value with the number of assists that each team has. It is worth noting that you can display both the numeric value and percentage value if you wish, but for this widget, I would only like to display the numeric value.
Now, my widget looks like this.
Now that my widget looks the way I want it to look, I would like to explore the multi-level drill down feature to ensure that it functions properly.
I can test the widget’s functionality by clicking the “Preview” button in the upper right corner of my dashboard and navigating to the doughnut widget. If I hover over a doughnut segment, I see the name of the team and the team’s total number of assists. The diagonal lines indicate that I can click the segment to view additional information.
If I click on Belgium’s segment, I can see individual Belgian players’ total numbers of assists. The drilled-down widget display also contains a legend demonstrating which segment color is associated with which player.
Multi-level drill down is available with 15 different Bold BI widgets. All of the widgets in the Comparison, Proportion, and Distribution sections of the widget menu offer this feature, allowing you endless customization options.
The drill up feature allows you to return to the previous view by clicking on the **"TeamName"** in the above widget.
Finally, it is worth noting that if you would like to create a pie chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the doughnut widget and the pie chart widget is that the pie widget does not have a white circle in its center, so its segments have a slightly different appearance (as you can see in the screenshot to the right). However, the widgets’ functionalities are the same.
# How to Create a Pyramid or Funnel Chart Widget
Getting Started with Pyramid or Funnel Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Selecting the Pyramid Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a pyramid widget.
These widgets allow you to highlight the proportional comparison between values in a progressively increasing manner.
Assigning the Data to Pyramid Widget
First, I will drag the widget from the “Proportion” section of the widget menu to my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my pyramid widget looks like before I have assigned data to it.
Next, I will click the “Settings” button in the upper right corner of the widget and navigate to the “Properties” tab to rename my widget. I want my pyramid to display each player’s number of attempts on target, so I will call the widget “Most Attempts on Target.”
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Attempts On Target” field to the “Values” box. I want to see the data for individual players (rather than teams), so I will drag the “PlayerName” field to the “Columns” box.
My widget has been created, but given the sheer amount of information it displays, it is clear that I need to filter my data to make the widget easier to read.
Customizing the Pyramid or Funnel Chart Widget
To filter my data, I will click the “Options” button that appears beside the “PlayerName” field and click “Filter(s).”
In order to show the six players with the most attempts on target, I need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Attempts On Target.”
Now, my widget’s data is far easier to read; however, I would like to make a few additional changes.
First, I would like to replace the percentage values on my widget with numeric values. Second, I would like to make my widget display a legend so I can see which color represents which player without hovering over the player’s pyramid segment. I can make both of these modifications in the “Properties” tab.
After I click the widget’s “Options” button and navigate to the “Properties” tab, I see a section titled “Basic Settings.”
In this section, I can click the checkbox beside the “Show Legend” option to make my widget display a guide demonstrating which segment color is associated with which player.
I can also change the “Data Label” drop-down list box option to “Value” in order to make my pyramid display numeric values instead of percentages.
Now, my pyramid widget looks the way I want it to look; it displays the numeric value of each player’s assists, and it contains a color-coded legend demonstrating which pyramid segment represents each player.
It is worth noting that if you would like to create a funnel chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the pyramid widget and the funnel widget is that the pyramid widget displays values in a progressively increasing manner while the funnel widget showcases values in a progressively decreasing manner.
# How to Create an Area Chart Widget
Getting Started with Area Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Distribution-Weather Details” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Area Chart Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create an area chart widget.
These widgets allow you to compare values for a set of items through filled vertical curves.
Assigning the Data to Area Chart Widget
First, I need to drag the area widget from the “Distribution” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my area widget looks like before I have assigned data to it.
Next, I am going to click the “Settings” button in the upper right corner of the widget. I would like my area chart to display the maximum temperature for each day of August 2018, so I am going to rename my widget accordingly. To do this, I will click the “Properties” tab and type in my area chart’s new name.
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Max Temp” field to the “Values” box and the “Date” field to the “Columns” box.
Customizing the Area Chart Widget
My widget has now been created, but it looks a bit odd. This is because my data source only contains temperature data for one month, August 2018, but my widget is displaying the date in a year format (rather than showing each individual day of August as I intended).
You may have noticed that though the “Dimensions” box contains a field called “Date,” the field’s name changed to “Year(Date)” when you dragged it over to the “Columns” box. This is because the widget shows data for the entire year by default.
This format would be helpful if I were comparing data across multiple years, but since I am only looking at one month of data, I need to revise my date display criteria. It does not make sense for my widget to supposedly display data for all of 2018 if I am only examining one month of temperature data.
To change the date settings for my widget, I need to navigate back to the “Columns” box and click the “Options” button beside the “Year(Date)” field. When I do, I see a list of different date display options: Date Time, Date, Year, Quarter, Month, Day, and More (clicking the “More” button will provide you with additional options).
As we noted earlier, the “Year” option is selected by default. In order to see the maximum temperature data for each individual day of the month, I am going to click the “Day” option.
After I click “Day,” I can see that the name of the date field in the “Columns” box has been changed to “Day(Date),” and my widget’s appearance has been updated accordingly.
I can change the date increments along the bottom of my area chart by dragging the chart’s edges to resize it. For example, if I make the widget smaller, it will display the dates in increments of six.
However, if I make the widget larger, it will display the dates in increments of four.
It is also worth noting that I can hover over any dot on the widget to see the maximum temperature data for that date. For example, I can see that the high on August 6 was 29°C and that the high on August 7 was 33°C.
# How to Create a Stacked Area Chart Widget
Getting Started with Stacked Area Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Distribution-Weather Details” data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Stacked Area Chart Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a stacked area chart widget.
These widgets allow you to compare multiple measures through filled curves that are stacked vertically.
Assigning the Data to Stacked Area Chart Widget
First, I need to drag the stacked area widget from the “Distribution” section of the widget menu onto my dashboard. Then, I am going to resize it by dragging its edges so that it will be easy to read. This is what my stacked area widget looks like before I have assigned data to it.
Next, I am going to click the “Settings” button in the upper right corner of the widget. I would like my stacked area chart to display the minimum and maximum temperatures for each day of August 2018, so I am going to rename my widget accordingly. To do this, I will click the “Properties” tab and type in my stacked area chart’s new name.
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Max Temp” and “Min Temp” fields to the “Values” box and the “Date” field to the “Columns” box.
Customizing the Stacked Area Chart Widget
My widget has now been created, but it looks a bit odd. There are two reasons for this.
The first is that the minimum temperature value is displayed in red while the maximum temperature value is displayed in blue. I would like to reverse this, so I need to navigate back to the “Values” box.
I can see that the “Max Temp” field currently sits atop the “Min Temp” field, and if I would like to reverse their appearance in the widget, I need to reverse their order in the “Values” box.
To do this, I am going to click the red “X” beside the “Min Temp” field to remove it. Then, I will drag the “Min Temp” field back over to the “Values” box, but this time, I will position it above the “Max Temp” field.
My widget has now changed its appearance so that the maximum temperature value is red and the minimum temperature value is blue.
Now, I need to address the second reason that my widget looks a bit odd. My data source only contains temperature data for one month, August 2018, but my widget is displaying the date in a year format (rather than showing each individual day of August as I intended).
You may have noticed that though the “Dimensions” box contains a field called “Date,” the field’s name changed to “Year(Date)” when you dragged it over to the “Columns” box. This is because the widget shows data for the entire year by default.
This format would be helpful if I were comparing data across multiple years, but since I am only looking at one month of data, I need to revise my date display criteria. It does not make sense for my widget to supposedly display data for all of 2018 if I am only examining one month of temperature data.
To change the date settings for my widget, I need to navigate back to the “Columns” box and click the “Options” button beside the “Year(Date)” field. When I do, I see a list of different date display options: Date Time, Date, Year, Quarter, Month, Day, and More (clicking the “More” button will provide you with additional options).
As we noted earlier, the “Year” option is selected by default. In order to see the maximum and minimum temperature data for each individual day of the month, I am going to click the “Day” option.
After I click “Day,” I can see that the name of the date field in the “Columns” box has been changed to “Day(Date),” and my widget’s appearance has been updated accordingly.
I can change the date increments along the bottom of my stacked area chart by dragging the chart’s edges to resize it. For example, if I make the widget smaller, it will display the dates in increments of six.
However, if I make the widget larger, it will display the dates in increments of four.
It is also worth noting that you can hover over any dot on the widget to see the minimum and maximum temperature data for that date. For example, I can see that on August 3, the high was 36°C and the low was 28°C.
# How to Create a Spline or Line Chart Widget
Getting Started with Spline or Line Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “Add.”
Selecting the Spline Chart Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a spline chart widget.
These widgets allow you to showcase trends for analysis over time with data points that are connected using splines.
Assigning the Data to Spline Chart Widget
First, I will drag the widget from the “Distribution” section of the widget menu to my dashboard. Then, I will resize the widget by dragging its edges so that it will be easy to read. This is what my spline chart looks like before I have assigned data to it.
Next, I will click the “Options” button, navigate to the “Properties” tab, and change the name of my widget. I want my widget to show the most penalty goals scored by players in the World Cup, so I will call the spline widget “Most Penalties Scored by Player.”
Finally, I will click the “Assign Data” tab. I want my widget to display the number of penalty goals that were scored in the World Cup, so I need to drag the “Penalties Scored” field to the “Values” box.
I want to see the data for individual players (not teams), so I need to drag the “PlayerName” field to the “Columns” box.
My widget has now been created, but given the sheer amount of information it displays, I would like to filter my data to make the widget easier to read
Customizing the Spline or Line Chart Widget
In order to make my widget easier to read, I am going to narrow down the data it displays. I have decided that instead of seeing the statistics for all of the players in the World Cup, I would only like to see data for the six players with the most penalty goals.
In order to achieve this, I need to click the “Options” button that appears beside the “PlayerName” field in the “Columns” box and click “Filter(s).”
Then, I need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Penalties Scored.”
Now, I am happy with my spline widget’s appearance, but I would like to customize it so that if I click on a player’s name, I am able to see the name of their team.
To do this, I will enable the multi-level drill down feature. As the name implies, this option will allow me to drill down my data even further by displaying another level of information.
To enable multi-level drill down, I will navigate back to the “Assign Data” tab. Making this customization will require me to modify the data that is associated with players’ names, so I need to locate the “Columns” box.
Currently, the only field in the “Columns” box is the “PlayerName” field. If I would like my widget to display the names of the players’ teams, I need to add the “TeamName” field to the “Columns” box.
Thus, I will drag the “TeamName” field to the “Columns” box and place it underneath the “PlayerName” field. When I do this, a box will pop up asking me if I want to enable multi-level drill down.
After I click “Yes,” the “Columns” box displays the “PlayerName” field on top of the “TeamName” field. The widget’s appearance has not changed, but multi-level drill down is now enabled. This means that I can click the data points on my spline widget to obtain additional information (in this case, the name of the team that each player represented in the World Cup).
I can test the widget’s functionality by clicking the “Preview” button in the upper right corner of my dashboard, navigating to the spline widget, and hovering over a player’s dot on the widget. White diagonal lines appear within the blue dot, which indicates that I can click the dot to view additional information.
After I click the dot, the player’s data is displayed, and the name of their team appears at the bottom of the widget.
The drill up feature allows you to return to the previous view by clicking on the **"PlayerName”** in the above widget.
Finally, it is worth noting that if you would like to create a line chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the spline widget and the line widget is that the spline widget uses smooth curves to connect data points while the line widget uses straight lines to connect data points. However, the widgets’ functionalities are the same.
# How to Add a List Box Filter
Selecting the List Box Filter
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
In this post, I am going to add a list box filter to an area chart widget.
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
First, I need to drag the list box filter from the “Filters” section of the widget menu onto my dashboard.
Assigning the Data and Customizing the List Box Filter
After I drag the list box onto my dashboard, I need to rename it and assign data to it.
I would like my list box to filter data by date, so I will click the “Settings” button in the upper right corner of the filter, click the “Properties” tab, and type “Select Date” into the list box’s name field.
Next, I will click the “Assign Data” tab and will drag the “Date” field to the “Column” box.
The “Date” field sorts data by year by default, but I would like to be able to filter data by the individual days of the month. To update my filter, I need to click the “Options” button that appears beside the “Date” field and select “Day.”
Now, my filter has been created, and I can select any date from the list box in order to see the maximum temperature data for that day.
To test my filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the list box.
I can select a date from my list box, and my widget will show me the maximum temperature for that day.
If I would like to clear the filter, I need only click the “Clear Master Filter” button that appears in the upper right corner of my list box, and the widget will return to its original appearance.
# How to Add a Combo Box Filter
Selecting the Combo Box Filter
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
In this post, I am going to add a combo box filter to an area chart widget.
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
First, I need to drag the combo box filter from the “Filters” section of the widget menu onto my dashboard.
Assigning the Data and Customizing the Combo Box Filter
After I drag the combo box onto my dashboard, I need to rename it and assign data to it.
I would like my combo box to filter data by date, so I will click the “Settings” button in the upper right corner of the filter, click the “Properties” tab, and type “Select Date” into the combo box’s name field.
Next, I will click the “Assign Data” tab and will drag the “Date” field to the “Column” box.
The “Date” field sorts data by year by default, but I would like to be able to filter data by the individual days of the month. To update my filter, I need to click the “Options” button that appears beside the “Date” field and select “Day.”
Now, my filter has been created, and I can select any date from the combo box in order to see the maximum temperature data for that day.
To test my filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the combo box.
I can select a date from my combo box, and my widget will show me the maximum temperature for that day.
If I would like to clear the filter, I need only click the “Clear Master Filter” button that appears in the upper right corner of my combo box, and the widget will return to its original appearance.
# How to Add a Range Slider Filter
Selecting the Range Slider Filter
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
In this post, I am going to add a range slider filter to an area chart widget.
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
First, I need to drag the range slider filter from the “Filters” section of the widget menu onto my dashboard.
Assigning the Data and Customizing the Range Slider Filter
After I drag the range slider onto my dashboard, I need to rename it and assign data to it.
I would like my range slider to filter data by date, so I will click the “Settings” button in the upper right corner of the filter, click the “Properties” tab, and type “Select Date” into the range slider’s name field.
Next, I will click the “Assign Data” tab and will drag the “Date” field to the “Column” box.
The “Date” field sorts data by year by default, but I would like to be able to filter data by the individual days of the month. To update my filter, I need to click the “Options” button that appears beside the “Date” field and select “Date.”
Now, my filter has been created. To test my filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the range slider.
I can select a date or date range by dragging the sliders. For example, if I want to see data for the second week of August, I can drag the sliders accordingly, and my widget will change its appearance.
If I would like to clear the filter, I need only click the “Clear Master Filter” button that appears in the upper right corner of my range slider, and the widget will return to its original appearance.
# How to Add a Date Picker Filter
Selecting the Date Picker Filter
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
In this post, I am going to add a date picker filter to an area chart widget.
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
First, I need to drag the date picker filter from the “Filters” section of the widget menu onto my dashboard.
Assigning the Data and Customizing the Date Picker Filter
After I drag the date picker onto my dashboard, I need to rename it and assign data to it.
First, I will click the “Settings” button in the upper right corner of the filter, click the “Properties” tab, and type “Select Date” into the name field.
Next, I will click the “Assign Data” tab and will drag the “Date” field to the “Column” box.
Now, my filter has been created. To test my filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the date picker.
I can then click the date picker’s calendar icon to select a date, and my widget will show me the maximum temperature for that day.
If I would like to clear the filter, I need only click the “Clear Master Filter” button that appears in the upper right corner of my date picker, and the widget will return to its original appearance.
# How to Create a KPI Card Widget
Getting Started with a KPI Card Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Card-Product Sales” data source.
Simply select the data source you would like to use and click “Add”.
Selecting the KPI Card Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a KPI Card widget.
KPI Cards allow you to measure trends by comparing values and goals. For example, you could compare revenue vs investment, target vs current value, or stock vs demand.
Assigning Data to the KPI Card Widget
First, I need to drag the KPI Card widget from the “Card” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I know that KPI Card widget allows me to quickly and easily compare certain pieces of data (such as my sales goal versus my actual sales for the month). I also know that, while I obviously want to sell as many of my products as possible, those sales do not do me much good if my customers are not paying for their orders.
Thus, in this widget, I would like to contrast the total dollar amount of my overall sales with the total dollar amount of payments I have received. This will allow me to see how much money I have received from customers and how much I still need to collect.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Actual Value,” “Target Value,” and “Series” boxes in the right column.
I want to compare the total dollar amount of payments I have received with the total dollar amount of payments I am owed. To do this, I need to drag the “Amount Paid” field to the “Actual Value” box and the “Amount” field to the “Target Value” box.
Finally, I am going to drag the “Sales Type” field to the “Series” box. In this case, all my sales are online, but it is still useful to add this field. For one thing, my widget now specifically notes that these numbers represent online sales, and for another, if I ever add another type of sale to my data source, my widget will be updated accordingly.
Customizing the KPI Card Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “Sum of Amount Paid vs Sum of Amount” to “Payments Received vs Total Sales”.
Now, the widget shows the following information:
My Sales type (online)
The dollar amount of payments I have received ($37,122)
The dollar amount of total sales ($42,622)
The dollar amount of payments I have not received ($5,500)
Configuring the KPI Card Widget with a KPI Value
Under the “KPI Value” column in the “Properties” panel, we can change the KPI formula to compare actual and target values. The available formulas are:
Absolute Difference
Percent of Target
Percent of Change
Percent of Difference
I have decided to use the “Percent of Target” type as I would like to easily see the percentage value of sales for which I have received payment. My completed card widget looks like this.
As I continue to scroll down the “Properties” column, I see a section titled “Indicator”. In this section, I can choose the type of indicator, along with its placement, position, and color.
Then, I can apply the above KPI formulas to the left and right values and can customize them by changing the font size, color, and caption properties.
Showcasing Trends and Patterns
In the “Assign Data” tab, there is a column named “Sparkline”. This section allows you to identify many trends at once according to more narrow criteria.
For example, I would like to see the payments I have received for each product category, so I am going to drag and drop the “Product Name” column in the Sparkline section.
Here is my widget showing the payment variations based on the product category.
Adding Images to the KPI Card
Now, I am going to configure image data for the KPI Card widget. I can add an image using several different methods that are outlined below.
In the “Assign Data” tab under the Image and Background Image boxes, I can bind an image field from my data source.
In the “Properties” tab, I can browse images from my local system, bind a URL from my data, or build a parameterized URL.
Now, I am going to bind an image field in the image box. I can see the image for the sales type “online” in my widget.
I can also add the image by using the “Properties” tab. Further, this option allows me to add an image to my widget even if I do not have it in my data source. So, let me see how this can be achieved.
When I scroll down the “Properties” window, I find the Image section. Here, the “Parameterized URL” image type was selected since we added the field in the Image section. In my data source, I have a single parameter for an image URL. Also, we can add multiple parameters by binding the proper image field with respect to the URL in the Image section.
Now, I am going to browse for an image from my local storage by selecting the image type “Local”. Selecting the “Show Image” option will allow me to display the selected image in my widget.
Now, I am going to choose the image type “URL”. Then, I will paste my URL in the text box, and my widget will show the image accordingly.
The Background Image configuration is also the same as the image; thus, my widget will show the image in its background.
Now my widget shows the percentage value of sales for which I have received payment with an interactive image.
Conditional Formatting in the KPI Card
Now, I would like to explore conditional formatting in the KPI Card. With this feature, I can modify various properties such as colors, icons, and images based on certain conditions.
The conditional formatting option is available in the Formatting section of the “Properties” panel. Enable Advanced Setting and add conditions and formatting in the dialog.
The conditional formatting dialog even allows me to add a condition based on a completely different field than the one already configured. I can also choose various condition types and formatting options as shown in the following image.
The following example shows a KPI card configured in a series to show the weather forecast for the week. The images are dynamically configured based on weather conditions.
# How do I create a Number Card Widget
## Getting Started with a Number Card Widget
If you are a Bold BI Cloud user, log in to your [cloud site](https://www.boldbi.com/account "https://www.boldbi.com/account") account. Else if you have Bold BI installed in your server, open the Bold BI application from there.
Click the "Plus" icon in the left side banner as shown in the following image.
After clicking on it, the "Create Dashboard" menu will open. Click on the "Start from Scratch" option.
Enter the dashboard's name and click "Add and Design" to navigate to the dashboard designer.
Now, the dashboard designer page will be open as follows.
A new window will open to add a new data source. To do so, click "Data sources" on the right side of the designer page.
Bold BI offers a wide range of sample data sources to choose from.
The "Northwind Traders Sales Analysis" data source has been selected for this dashboard
. To add your preferred data source, select it and click on "Add."
## Adding the Number Card Widget
Once you have chosen a data source, start selecting widgets. One of the widgets available in Bold BI is the "Number Card" widget. For this article, a number card widget is going to be created.
The Number Card widget allows you to display a single numeric value or a series of measure values from a dataset. The widget offers customization options for appearance, such as font, color, style, Background image and color, and more.
Locate the "Card" section in the widget menu, usually on the dashboard designer's left side. After finding the Number Card widget, drag it onto your dashboard canvas. Position the widget wherever you want it on the canvas. To resize the widget, hover your cursor over one of the edges or corners of the widget until you see a resized cursor. Click and drag the edge or corner to adjust the widget's size, making it easier to read. Release the mouse button when you're satisfied with the widget's size.
## Assigning Data to the Number Card Widget
To assign data to the Number Card widget in Bold BI Widget, follow these steps:
- Select the Number Card widget on your dashboard designer.
- Click "**Settings**" in the upper right corner of the widget to open the widget configuration panel.
- In this panel, you will see different tabs. Click on the "**Assign Data**" tab.
- On the left column of this tab, you will find a list of available fields categorized as "**Measures**" and "**Dimensions**."
- Select the desired field(s) from the left column by clicking and dragging them.
- Next, drag the selected field(s) to the "**Measure**" section and the "**Series**" section in the right column, depending on the type of data you want to display.
- If you want to display a single numeric value, drag a measure field from the "**Measures**" section to the "**Measure**."
- If you want to display a summarized value based on different categories or series, drag a field from the "Dimensions" section to the "Series."
- Once the field(s) are assigned to the appropriate section, the Number Card widget will be rendered with the data you configured.
## Customizing the Number Card Widget
To customize the Number Card widget in Bold BI, utilize the configuration options available in the widget settings. Here are some common customization options that can be explored.
- **Widget Appearance:** The visual appearance of the Number Card widget can be modified, including font size, font color, background color, border style, and more.
- **Number Formatting**: The displayed number can be formatted according to personal preferences. This includes options to specify decimal places, apply currency symbols, add a thousand separators, and choose different number formats (such as percentage, Currency, and Number).
- **Conditional Formatting:** Conditional formatting can be applied to the Number Card widget to change the appearance based on a specific condition. For instance, different font colors or background colors can be set based on particular threshold values or data ranges. 
For more information on the Number card widget, refer to the following help documentation links:
- [KPI Card](https://help.boldbi.com/embedded-bi/visualizing-data/visualization-widgets/kpi-card/ "https://help.boldbi.com/embedded-bi/visualizing-data/visualization-widgets/kpi-card/")
- [Number Card](https://help.boldbi.com/embedded-bi/visualizing-data/visualization-widgets/number-card/ "https://help.boldbi.com/embedded-bi/visualizing-data/visualization-widgets/number-card/")
# How to Create a Range Navigator Widget
Getting Started with a Range Navigator Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Distribution-Weather Details” data source.
Simply select the data source you would like to use and click "Add".
Selecting the Range Navigator Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a range navigator widget.
Range Navigator controls allow you to select a smaller range from a large collection. They are commonly used to filter the date range for which the data is visualized.
Assigning Data to the Range Navigator Widget
First, I need to drag from the “Filters” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read. This is what my range navigator widget looks like before I have assigned data to it.
I know the range navigator widget allows me to select a range of data from a series, and this can also be used as a filter for other controls.
Thus, in this widget, I would like to see the maximum temperature recorded in August 2018.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Max Temp” field to the “Values” box and the “Date” field to the “Argument” box.
Customizing the Range Navigator
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “RangeNavigator1” to “Select Date Range”.
Then, I can change the range chart type to Area, Line, or Step Line by using the dropdown list in the “Properties” tab. Here, I will use the default type “Area”.
My widget has now been created, but it looks a bit odd. This is because my data source only contains temperature data for one month, August 2018, but my widget is displaying the date in a year format (rather than showing each individual day of August as I intended).
You may have noticed that though the “Dimensions” box contains a field called “Date,” the field’s name changed to “Year(Date)” when you dragged it over to the “Argument” box. This is because the widget shows data for the entire year by default.
This format would be helpful if I wanted to compare data across multiple years, but since I am only looking at one month of data, I need to revise my date display criteria. It does not make sense for my widget to supposedly display data for all of 2018 if I am only examining one month of temperature data.
To change the date settings for my widget, I need to navigate back to the “Argument” box and click the “Options” button beside the “Year(Date)” field. When I do, I see a list of different date display options: Date, Year, and More (clicking the “More” button will provide you with additional options).
You can set “Range” and “Period” options from the Relative Date Filter menu. You can also set a specific date by enabling “Link to Specific Date”.
As we noted earlier, the “Year” option is selected by default. In order to see the maximum temperature data for each individual day of the month with the year, I am going to click the “Day Month Year” option.
After I click “Day Month Year,” I can see that the name of the date field in the “Argument” box has been changed to “DayMonthYear(Date),” and my widget’s appearance has been updated accordingly.
Adding a Range Navigator Filter to an Area Chart
Here, I am going to add a range navigator filter to an area chart widget.
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
To test my already customized range navigator filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the range navigator.
I can select a date range by dragging the sliders. For example, if I want to see data for the last 10 days of August, I can drag the sliders accordingly, and my area chart widget will show data for the selected date range.
If I would like to clear the applied filter, I just need to click the “Clear Filter” button that appears in the upper right corner of my range navigator, and the widget will return to its original appearance.
# How to Create a Pivot Grid Widget
Getting Started with a Pivot Grid Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Pivot Grid-Orders” data source.
Simply select the data source you would like to use and click “Add”.
Selecting the Pivot Grid Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a pivot grid widget.
Pivot grid widgets summarize business data and display the results in a cross-table format. They allow the creation of multidimensional views and make it easy for business users to analyze their data.
Assigning Data to the Pivot Grid Widget
First, I need to drag the pivot grid widget from the “Relationship” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I know that pivot grid widgets allow me to display data in multidimensional views for easy analysis.
In this widget, I would like to see the unit price of each product shipped by year so I can see how much money I earned yearly for each product.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of the widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Value(s),” “Row(s),” and “Column(s)” boxes in the right column.
Now, I am going to drag “UnitPrice (Products)” to the “Value(s)” box, “ProductName” to the “Column(s)” box, and “ShippedDate” to the “Row(s)” box.
Customizing the Pivot Grid Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “PivotGrid1” to “Unit price of each product”.
I would like to see the value in dollars, so I am going to apply this format in the “Value(s)” box under the “Settings” menu.
Now I am going to click the “Format” option, and the “Measure Formatting” dialog will be opened. In that dialog, I will choose “Currency” as “Type.” I can then see a preview.
Now, my widget looks like the grid below.
The pivot grid widget has many unique features, and I would like to explore the features below to further customize my widget.
Adding one or more rows and columns
Grand totals and subtotals of columns and rows
Preserving Node States
Showing No Data Item
Conditionally formatting in the pivot grid
Linking URLs for field values
Adding One or More Rows and Columns
In the pivot grid widget, we can group the data for better analysis by adding one or more rows, columns, or both.
Each row or column value acts as a group with respective aggregated values while grouping. In multiple groups, each row or column value is arranged as a nested level, forming a hierarchy.
Here, I am going to drag and drop one more field, “ShipName,” to the “Row(s)” box, and “ShipRegion” to the “Column(s)” box.
Now, my widget looks like the grid below with grouping.
I would like to expand each node in a row and column, so I am going to enable the “Expand Nodes by Default” option in “Basic Settings” under the “Properties” column.
Grand Total and Subtotal Fields in Pivot Table
Totals are the sum of row or column values in the pivot table. I know that the pivot grid widget allows me to get the grand totals of rows and columns. Similarly, it allows me to get the subtotals of each row group and each column group.
Here, the grand totals for rows are displayed at the bottom of the pivot table below all rows.
Show Row Grand Totals Text property enables users to change the text displayed for row grand totals. The default text is "Grand Total." Modifying the text in the designated text box will update the display accordingly.
Grand totals for columns are displayed at the right of the pivot table at the end of all columns.
Show Column Grand Totals Text property enables users to change the text displayed for column grand totals. The default text is "Grand Total." Modifying the text in the designated text box will update the display accordingly.
Here, subtotals for rows are displayed at the bottom of each row group.
Subtotals for columns are displayed at the right of each column group.
These rows and columns are enabled by default, but I can disable them in Grand Totals Settings under the “Properties” column.
:::Info
NOTE: The row and column grand totals text boxes are set to Auto by default, which uses the localized Grand Total text from the locale file for display. This allows us to modify the column grand totals text in multiple pivot grids simultaneously using localized text and [localization](https://help.boldbi.com/localization/){target="_blank"}.
:::
Preserving Node States
By default, the expanded state of nodes in a pivot table will not be maintained while viewing the dashboard.
But with the pivot grid widget in Bold BI, this is possible through enabling Save Nodes State in Basic Settings in the Properties column.
Using this feature, you can focus on specific categories, expand only specific nodes, and perform dynamic operations like sorting and filtering.
Showing No Data Items
By default, the pivot table shows a row or column item only if there is data in that specific row and column combination. However, I would like to see the row and column items without data.
Here, the pivot grid widget allows me to enable Show No Data Item for corresponding fields in the Edit Field Settings under the “Properties” column.
Conditional Formatting in the Pivot Grid
Conditional formatting in the pivot grid allows me to customize the font style, text representation, font color, and fill color based on certain conditions.
The conditional formatting option is available in the Formatting section of the “Properties” column. Enable Advanced Setting, and the formatting dialog will open.
The conditional formatting dialog even allows me to add a condition based on a completely different field than the one already configured. I can also choose various condition types and formatting options as shown in the following image.
Now, I would like to highlight the “UnitPrice” which is greater than 1000 with respect to “ShipCity.” I added the condition as you can see below.
Now, my widget highlights the value based on this condition.
Linking URLs and Parameters to Fields
Linking plays an important role in interactive data visualization for analysis. With this functionality, a row or column header cell or value cell in a pivot grid can be linked to relevant content hosted at a URL.
Here, I can click the “Enable Link” check box under Link settings in the “Properties” column. I would like to add the URL for “ShipCity,” so I am going to enter “https://www.google.com/search?q={{:ShipCity}}” in the “URL” text box.
Now, “ShipCity” is linked with the URL in my widget. I can check this by clicking on the city name.
Sorting Values in a Pivot Grid
In the pivot grid widget, we can sort the values by clicking the value column header. It will display the values in ascending or descending order.
This option can be disabled through the “Allow Value Sorting” option under “Group Bar Settings” in the “Properties” Column.
# How to Create a Radar Polar Chart Widget
Getting Started with Radar Polar Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Image Widget-FIFA world cup 2018 top scores” data source.
Simply select the data source you would like to use and click “Add”.
Selecting the Radar Polar Chart Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a Radar Polar Chart widget.
Radar Polar Chart allows you to display multivariate data in the form of a two-dimensional chart using three or more quantitative variables represented on axes starting from the same point.
Assigning data to the Radar Polar Chart Widget
First, I need to drag the Radar Polar widget from the “Comparison” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I know that Radar Polar chart allows me to quickly and easily visualize certain pieces of data in the form of two-dimensional chart.
Thus, in this widget, I would like to compare the performance of each player based on the matches that the players played and attained goals in world cup.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Value(s)” “Column” and “Tooltip” boxes in the right column.
To compare the performance of each player, I need to drag the “Goals” and “Matches” fields to the “Value(s)” box and the “PlayerName” field to the “Column” box.
Customizing the Radar Polar Chart Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “RadarPolarChart1” to “Performance of players in World Cup”.
I would like to visualize the performance of the players who comes under Top 5 Ranking. To achieve this, I can “Edit” Filter(s) option in Column “Settings” menu.
When I click the “Edit” option, a dialog will open and in that I am going to enable “Rank” and choose the Count as ’5’ for the Rank Column.
After clicking “OK”, my widget will show the Top 5 Players performance in world cup.
With the help of properties column, I can make few additional changes to my widget. First, I would like to change my widget draw type as “Radar”. Second, I would like to see the medals received by each country without hovering over the Country name. This can be achieved by choosing the Draw Type as “Radar” and by enabling the “Show Value Label” under the “Basic Settings”.
Now, my widget looks the way I want it to look; it displays the player’s performance with Radar visualization.
Under the “Properties” column, I can change the color of the Legend name by changing it in a “Series Palette” section.
Also, I can customize the name and position of the Legend under “Legend Settings” in the “Properties” column.
# How to Create a Radial Gauge Widget?
Getting Started with a Radial Gauge Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Card-Product Sales” data source.
Simply select the data source you would like to use and click “Add”.
Selecting the Radial Gauge Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a Radial Gauge widget.
Radial Gauge widget allows you to measure the processing efficiency through the key performance indicator (KPI) like value and goal.
Assigning data to the Radial Gauge Widget
First, I need to drag the Radial Gauge widget from the “Deviation” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I know that Radial Gauge widget allows me to quickly and easily compare certain pieces of data with the percentage efficiency for my value and goal.
Thus, in this widget, I would like to know the percentage difference of Current Month and Previous Month Expense for my product sales. This will allow me to see how much money I have spent for each product in previous and current month.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Actual Value,” “Target Value,” and “Series” boxes in the right column.
I want to compare the Current Month and Previous Month expenses of each product. To do this, I need to drag the “Previous Month Expense” field to the “Actual Value” box and the “Current Month Expense” field to the “Target Value” box and “Product Name” field to the “Series” box.
Customizing the Radial Gauge Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “RadialGauge1” to “Expense of Previous Month vs Current Month”.
In the “Properties” column, I can change the type of widget by changing the type as “Half Circle”under the “Basic Settings”.
Now my widget looks like below and show the Variation and Percent of Target with the sum of Previous Month and Current Month Expenses. Here, I can see the values by hovering over the widget.
In the “Properties” column, I can customize the value pointer with available types and colors under the “Pointer Settings”.
Here, I am choosing the “Value Pointer” as “Range with Needle” and changed the color of Range Pointer and my widget looks like below.
In the “Properties” column, I can enable the “Show Range” to show the selected range of values with selected range color under the “Range Settings”.
Now my widget will show the range of values with varying color as shown in below.
Conditional Formatting in the Radial Gauge
Now, I would like to explore conditional formatting in the Radial Gauge. With this feature, I can modify color of Range Pointer, Actual Value, Needle Pointer, Target Pointer and Title Color based on certain conditions.
The conditional formatting option is available in the Formatting section of the "Properties" panel. Enable "Advanced Setting" and add conditions and formatting in the dialog.
The conditional formatting dialog even allows me to add a condition based on a completely different field than the one already configured. I can also choose various condition types and formatting options as shown in the following image.
The following example will help to show a Radial Gauge with varying color based on the condition provided for Current Month Expense.
Now my widget will look like below with the applied formatting.
# How to Create a Combo Chart Widget
Getting Started with the Combo Chart Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Image Widget-FIFA world cup 2018 top scores” data source.
Simply select the data source you would like to use and click “Add”.
Selecting the Combo Chart Widget
Once you have chosen a data source, you can start selecting widgets. For this post, I am going to create a combo chart widget.
Combo charts allow you to compare values by combining two charts.
Here, bar charts can be combined with bar, stacked bar, and 100% stacked bar charts. In fact, you can create any combination you like using the following charts: column, line, area, spline, spline area, stacked column, stacked area, 100% stacked column, and 100% stacked area.
Assigning Data to the Combo Chart Widget
First, I need to drag the combo chart widget from the “Composition” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I know that combo charts allow me to easily compare values by combining two charts in a single widget. By default, primary values render with “Column chart” and secondary values render with “Line chart.”
In this widget, I would like to compare the performance of each player based on their attempts on target and goals scored in the World Cup.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of the widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Value(s),” “Secondary Value(s),” “Column(s),” and “Tooltip” boxes in the right column.
To compare the performance of each player, I need to drag the “Goals” field to the “Value(s)” box, the “Attempts On Target” field to the “Secondary Value(s)” box, and the “PlayerName” field to the “Column” box.
Customizing the Combo Chart Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “ComboChart1” to “Attempts vs Attained Goals.”
I would like to visualize the top 5 goal scorers along with their numbers of attempts. To achieve this, I can click “Edit” under the “Filter(s)” option in the Column “Settings” menu.
When I click the “Edit” option, a dialog will open. There, I am going to enable “Rank” and set the Count to ‘5’ for the “Goals” Column.
After clicking “OK,” my widget will show the top 5 goal scorers in the World Cup, along with their attempts on target. Here, I can see the values by hovering over the widget.
With the help of the “Properties” column, I can see the number of goals scored and the number of attempts by enabling “Show Value Labels” in “Basic Settings.”
Also, I can change the chart type and axis type using the “Change” button in “Basic Settings.”
Here, I would like to change the chart type for my Primary Value(s) to “Line.”
After clicking “OK,” my widget shows line graphs detailing the top 5 goal scorers with their numbers of attempts in the World Cup.
Also, I can customize the name and position of the Legend under “Basic Settings” in the “Properties” column.
Under the “Axis” section in the “Properties” column, I can customize axis settings like Show or Hide Axis Title, Edit Axis Range, and Label Rotation.
Showcasing Trends and Conditional Formatting
Now, I am going to add a trendline to my widget so I can see the trend of the data, which will be indicated with a single line. Here, I can add, edit, and delete the trendline.
I know I can add more than one trendline to Cartesian charts other than bar, series (line, column, area, and spline), and stacked charts.
After clicking the “Add” button, a dialog opens where I can customize the trendline.
Now my widget shows the trend you see below.
Next, I would like to explore conditional formatting in the combo chart. With this feature, I can modify the chart’s colors based on certain conditions.
The conditional formatting option is available in the “Formatting” section of the “Properties” column. Enable “Advanced Setting” to add conditions and formatting in the dialog.
The conditional formatting dialog even allows me to add a condition based on a completely different field than the one already configured. I can also choose various condition types and formatting options as shown in the following image.
The following example will help to show a combo chart with varying colors based on the condition provided for goals scored by top 5 players.
Now that this formatting has been applied, you can see the updated widget below.
# How to Create a Bing Maps Widget
Getting Started with the Bing Maps Widget
If you are a Bold BI Cloud user, log in to your cloud site account. If you are an Embedded BI user, open the Bold BI application installed on your server.
Click the “New Dashboard” button and select the “Blank Dashboard” option. A pop-up box will prompt you to configure a data source.
I have an Excel file titled “World Population Data of the year 2020” on my local machine. I can add this file as a new data source by clicking the "Data Sources" icon.
Now, I am going to click "CREATE NEW" to launch a new connection from the connection panel. In the connection panel, I am going to select the “Excel” data source to add my Excel file to Bold BI.
Then, I have to upload my file by using the “Browse” button and clicking “Preview & Connect.” It will navigate to the Data Preview dialog.
After clicking “Connect,” the data design view page will open as in the image below.
Now, I am going to drop the table in the table canvas and save the data source by clicking the “Save” button.
Selecting the Bing Maps Widget
Once you have added a data source, you can start selecting widgets. For this post, I am going to create a Bing Maps widget.
Bing Maps allow you to visualize markers based on latitude and longitude data.
Assigning Data to the Bing Maps Widget
First, I need to drag the Bing Maps widget from the “Relationship” section of the widget menu to my dashboard. Then, I am going to resize the widget by dragging its edges so that it will be easy to read.
I would like my widget to display population data for the year 2020 from the available data in my sample Excel file. Now that I have moved the widget to my dashboard, I can assign data to it.
To assign data to my widget, I need to click the “Settings” button in the upper right corner of the widget. Then, I will click the “Assign Data” tab.
I immediately see two columns. In the left column, I can select different fields called “Measures” and “Dimensions.” I can drag these fields to the “Marker Latitude,” “Marker Longitude,” “Column,” “Marker Tooltip,” and “Marker Image” boxes in the right column.
To display population data for the available countries in my sample file, I need to drag the “Latitude” field to the “Marker Latitude” box, the “Longitude” field to the “Marker Longitude” box, and the “Population_2020”and “Country” fields to the “Marker Tooltip” box.
Customizing the Bing Maps Widget
Now that I have assigned data to my widget, I am going to click the “Properties” tab to customize it. First, I am going to change the widget’s name from “BingMap1” to “2020_World Population Data.”
Now, my widget will show countries’ population data, and markers will indicate a country’s location based on latitude and longitude values. Here, I can see the data by hovering over a marker.
With the help of the “Properties” column, I would like to customize my widget. First, I am going to change the Map Theme to “Aerial” under “Basic Settings.”
Below, you can see what the widget looks like with the “Aerial” theme.
I know I can change the marker shape in “Marker Settings” under the “Properties” column. By default, the marker shape is “Circle.”
Adding Images to the Markers in Bing Maps
Now, I am going to add custom images to the markers or pushpins in the Bing Maps widget. I can add an image using several different methods that are outlined below.
In the “Assign Data” tab under the Marker Image box, I can bind an image field from my data source.
Now, my widget shows population data for countries, along with the countries’ flags.
In the “Properties” column, I can browse images from my local system, bind a URL from my data, or build a parameterized URL.
Conditional Formatting in the Bing Maps
Now, I would like to explore conditional formatting options. With this feature, I can modify the color, size, and shape of the marker based on certain conditions.
The conditional formatting option is available in the “Marker Settings” section of the “Properties” column. Enable “Advanced Setting” and add conditions and formatting in the dialog.
I would like to visualize the country “India” with a different marker shape, color, and size. So, I am going to format the marker as you see below.
With this formatting applied, my widget will look like the image below.
# How to Apply Hierarchical and Flat Filtering in Widgets
Bold BI has provided support for analysing data to showcase the hierarchical view in widgets. Users can apply a filter to the hierarchical view on widgets.
Use Case
The following example showcases overall team-wise players and their goals in a widget. The user would like to view the top three players who scored the most goals in each team, then apply the hierarchical filter to the players with the most goals. In flat filtering, the enabled hierarchical filtering is disabled to show the top three players on the overall data record.
Applying a hierarchical filter on the widgets
Configure the grid widget and apply hierarchical filtering in the configured columns. By default, enable hierarchical filtering is enabled for all widgets.
Follow these steps to achieve this:
Configure the columns to the widget as follows.
Widget Configuration
Select the settings icon on the column to apply the hierarchical filter.
Accessing Filter
After clicking the settings, click Filter(s), then proceed to Edit.
Navigating to filter
On the filter panel, enable Rank, update the count, set the Goals as the basis of filtering, and click OK.
Applying the filter
The hierarchical filter will be applied to the top three players for each team as follows.
Filtered widget
Customize filtering mode through widget properties
By default, enable hierarchical filtering is enabled for all widgets. You have the option in the properties to disable it and view the flat ranking of the overall record.
Follow these steps to achieve this:
Click Properties on the dashboard designer page.
Hierarchical filtering by properties settings
Disable the enable hierarchical filtering properties on the settings to view the top three players from the overall data.
Disabled hierarchical filtering
# How to Dynamically Change a Widget's Bound Column in View Mode in Bold BI
The Bold BI application supports the option to change the bound columns in the widget dynamically. By using the expression column and dashboard parameters, we can achieve this feature. We can do this by:
Creating dashboard parameters with column names.
Creating an expression column to switch the column names.
Configuring the widget with dynamic columns.
Use Case
In the example below, the feature is applicable when the user wants to visualize the total marks of the students in Quarterly, Half-yearly, and Annual exams dynamically in a single widget. Users can select the terms and showcase the marks in a widget.
Creating dashboard parameters with column names
We can add the column names to the dashboard parameter to change them dynamically in view mode.
Follow the steps below to achieve this requirement:
Select list mode in the dashboard parameter configuration page.
Dashboard Parameter configuration
Select the Value as Manual and add the column values on the text box then click Add.Dashboard Parameter configuration
Add the dashboard parameter as shown in the image below
Dashboard Parameter configuration
Enable set first value or choose a default value from the drop down as shown in the image below then save and close.
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NOTE: The user can add one or more values manually when updating the parameters.
:::
Creating expression column to switch the column names
We create the expression column with the parameter columns to switch the column values. Follow the steps below to achieve this:
Create an expression column for the dynamic measure as follows.
Expression column creation
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NOTE: More details about How to create different If condition-based expressions in Bold BI is explained on this link.
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Configuring widgets to view the dynamic columns
We configure the parameters on the combo chart to filter the dynamic measure values that are configured on the column chart. Follow the steps below to achieve this:
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NOTE: For proper visualization and compatibility, the widgets are configured in a combine widget as follows:
:::
Drag and drop the combo box and the column chart on the combine widget as shown below:
Configure the parameter on the combo box widget as shown below:
Combo box configuration
Configure a column chart with the value and the expression column as shown below:
Column chart configuration
Click Preview to view the dynamic column changes in widget.
Click to Preview
Select any column name to view the dynamic measure on the column chart.
Widget Filter
Select any other value from the term to view the respective mark details.
Widget Filter
We can also apply dynamic column changes on the dimension as shown below:
Dimension Dynamic changes
# How to Create an Organizational Chart Diagram as a Custom Widget in Bold BI
An organizational chart custom widget helps to visualize the relationship hierarchy and its structure. Its layout starts parsing from the root and iterates through all its child elements. The Bold BI Dashboard custom widget allows the user(s) to add any user-defined widget, d3 controls, Syncfusion controls, or any JS widgets in a dashboard, and it can perform like the normal widget.
Creating Organizational Chart as a Custom Widget
Follow the below steps to create an Organizational chart custom widget:
Download the Organizational chart custom widget from the link.
Bold BI Custom Widget Utility (bicw.exe) is used to create and manage the custom widget, and it will be shipped along with the Bold BI Application setup installation in the following folder.
Create command is used to create the widget in the specified path with provided name along with its unique GUID.
After downloading find the following files after extracting the downloaded folder.
Copy and paste the downloaded scripts and styles files of Diagram control into the custom widget created location as shown in the following image.
Script:
Styles:
Open the Manifest configuration file of the custom widget in the following location.
Refer to the copied script and style files in the above highlighted file. Also add the dependency scripts and refer it as in the below image.
```js
"dependencies": {
"scripts": [
"src/ej.widget.all.min.js"
],
"styles": [
"style/widget.css"
]
},
```
:::Info
NOTE: Users can edit(Renaming the widget name, display name, description, data field configuration) the custom widget as per their requirement. Click on this link for further details.
Create a div element to initialize the custom widget as shown in the following code samples in the above-mentioned source file, which is “Sourcefile.js.” Assign id for the created div. Once the widget div was created, append this div to its parent div.
```js
init: function () {
/* init method will be called when the widget is initialized */
var widget = document.createElement("div");
widget.setAttribute("id", "diagram");
this.element.appendChild(widget);
if(this.model.dataSource.length > 0){
window.label = this.model.boundColumns.Label[0].uniqueColumnName;
window.id = this.model.boundColumns.Id[0].uniqueColumnName;
window.parent = this.model.boundColumns.Parent[0].uniqueColumnName;
var data = this.model.dataSource;
//data.forEach((d, v)=> { for(x in d) { if(d[x] == "(Null)") { delete d[x] }; }});
$.map(data, function (value, index) { if(value[window.parent] == "(Blanks)") { delete value[window.parent] } });
}
```
Use Syncfusion Essential EJ2 Diagram control to create this custom widget. Refer to the highlighted diagram control script and its dependency script files in the following location.
Node is a graphical object used to visually represent the geometrical information or process flow. You must define the node object as in the following code samples and add that node collection to the Diagram property on the initialization.
```js
nodeTemplate: $.proxy(this.nodeTemplate),
dataSourceSettings: {
id: window.id, parent: window.parent, dataSource: data
},
pageSettings: {
scrollLimit: "diagram", muliplePages: false
},
snapSettings: {
snapConstraints: ej.datavisualization.Diagram.SnapConstraints.None
},
});
},
update: function (option) {
this.element.innerHTML = "";
this.init();
return;
},
nodeTemplate: function (diagram, node) {
node.labels[0].text = node[window.label];
node.fillColor = node.Color;
if (node[window.id]== "Parent") { node.fillColor = "#3484bb"; }
if (node[window.parent] == "Parent") { node.fillColor = "#9ace7f"; }
if (node[window.parent] == "1") { node.fillColor = "#9264aa"; }
if (node[window.parent] == "2") { node.fillColor = "#9264aa"; }
if (node[window.parent] == "3") { node.fillColor = "#9264aa"; }
},
```
Pack the custom widget as in the link. Execute the following syntax in the “bicw.exe” in Bold BI Application.
Syntax: pack [path of the widget to be packed]
Now you get the “. bicw” file of the Organizational Chart custom widget inside the output folder as mentioned in the above image.
Importing custom widget “. bicw” file into Bold BI
Follow the steps below to import the custom widget “. bicw” file into the Bold BI Application.
From the Widgets menu in the settings page of Bold BI application, select ‘Add New Widget’ to import.
Choose ‘Add widget’from the Manage Custom widgets pop-up and add the custom widget file which has the extension “. bicw”.
The file will be added as in the following image then click Upload.
Close the pop-up, the custom widget file will be added in the widgets Relationship section as in the following screenshot.
Drag and drop the custom widget from the widgets section and bind the data to the custom widget and preview it.
:::Info
NOTE: Topmost level of the Organization Id should be “parent”. Subsequent level connections can be linked by the corresponding Id, which need to be provided in the “Phase” value.
Map the dimension column with the parent, id, and label field of the custom widget as in the following screenshot.
Visualize the organization level data as in the following screenshot.
# How to Apply Cross-Data-Source Filtering in Bold BI
In Bold BI, Dashboard filters allow you to control the interdependency of widgets in the dashboard concerning dynamic user interactions. You can also apply cross-data source filtering in Bold BI for multiple data sources on a dashboard.
Applying a data source filtering in Bold BI
Please follow these steps to apply data source filtering.
Click the filter icon on the dashboard designer page.
Filter icon
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NOTE: The data source filter is configured to Default as follows.
:::
Default filter configuration
The filter configuration is set to default if a customer wants to customize the configuration. Switch the custom filter configuration to change the data source on the data source configuration panel.
Custom filter configuration
Click add (+) to view the drop-down of the target data source and columns in Bold BI.
Custom filter configuration
The data source from the filter widget is as follows, where the first drop-down represents the master widget column, the second drop-down represents the target data source, and the third drop-down shows the listener widget column.
Filter configuration panel
Click update to apply the changes to the filter configuration.
Filter update
Click Preview or Publish and apply the filter to see the filter with a cross-data source. On this dashboard, the Combo box (Project) is configured with Data source 1(Trello KB Test) while the Bar chart (Estimated vs Utilized Hours by Project) is configured with Data source 2(Trello-test). When the values on the Combo box filter widget are filtered, they will reflect on the Bar chart.
Dashboard preview
The widget with a cross-data source will be rendered successfully as follows.
Filtered cross-data source widget
# How to Create a Dual-Axis Chart in Bold BI
In Bold BI, you can create a dual axis chart in two ways. These two ways are:
Using Chart type & Axis Settings in properties.
Using Combo Chart or Combination Chart.
Using Chart type & Axis Settings in properties
The column chart allows you to compare values for a set of unordered items across categories through vertical bars ordered horizontally. Configure a column chart with two measures and change the series type to the column and line to achieve the dual axis chart.
Follow these steps to create a dual axis chart:
Configure a column chart with at least two measures as follows.
Widget Configuration
Click on the PROPERTIES tab to navigate to the settings and customize the widget.
Chart Properties
Click Change in the Chart Type& Axis under the properties pane, and a Chart Type & Axis Settings pane pops up as follows.
Change chart typeChange chart type
Change the column Chart Type to line, enable the secondary Axis option on the check box, then click OK.
Change chart type
The widget with a dual axis will be rendered as follows.
Chart with Dual Axis
Customize the widget to appear as follows.
The widget configured with a Dual Axis
Using a Combo Chart or Combination Chart
The Combination Chart allows you to compare values by combining multiple Cartesian charts (column, bar, stacked column, stacked bar, 100% stacked column, 100% stacked bar, spline, line, area, stacked area, and 100% stacked area). It also allows you to configure data to primary and secondary values separately, therefore, creating a dual-axis chart.
Follow these steps to configure a combo chart.
Drag and drop a combo chart to the dashboard designer page.
Dashboard Designer Page
Click Properties to open the property panel, then switch to the ASSIGN DATAWidget Properties Panel
Configure the Primary and Secondary values to the column as follows.
Widget Configuration Panel
Click on the properties tab to navigate to the properties panel and apply basic settings to the widget.
Widget Configuration Panel
The widget will be rendered as follows.
Configured Combo chart
# How to Predict Future Results Using Different Forecasting Models
Bold BI supports analyzing hierarchical data. Users can view hierarchical data in the widgets by doing a drill down or drill up on the specific value.
Enable hierarchical drill down or drill up in widgets in Bold BI
Please follow the steps to enable hierarchical drill down or drill up in the chart widget below:
Drag and drop the column hierarchies in the columns section.
Dashboard Designer Page
Select Yes to enable multi-level drill down on the pop-up window.
Multi-level drill down pop-up
Click the value you want to drill down in the chart:
Dashboard Designer Page
The chart will render the hierarchical data as shown below:
Dashboard Designer Page
To return to the previous view, click the highlighted text that indicates "drill up":
:::Info
NOTE: Drill down feature is applicable to the below mentioned widgets:
:::
Bar chart
Column Chart
Stacked Column Chart
Stacked Bar Chart
100% Stacked Bar Chart
100% Stacked Column chart
Treemap
Pivot Grid
Map
Bing map
Heat Map
We can also create custom and autohierarchy columns in Bold BI and use them to view a group of data fields that are bound to widgets. To achieve this, refer to this link.
# How to Increase Line Thickness in a Chart
In Bold BI, the option to adjust the line width is available on spline and line charts. Therefore, we can configure a line chart with two measures and change the series type to column and line. Then we can customize the line width. It will also serve the same purpose as a combination chart.
This process can be executed as shown below:
Configure a column chart with the measures as shown below:
Dashboard Designer Page
Click on the properties tab to navigate to the settings and customize the widget.
Dashboard Designer Page
Click the change button in the Chart Type and Axis under the properties pane, then a Chart Type & Axis Settings pane pops up.
Chart properties sectionChart Type and Axis Settings
Change the column axis type to line and enable the secondary axis option on the check box, then click OK.
Chart Type and Axis SettingsChanged chart type
Change the line width by inserting the intended value in the numerical text box.
Changed line width of Chart widget
# How to Predict Future Results Using Different Forecasting Models in Bold BI
Forecasting - BoldBI
Forecasting is the process of predicting future data based on past and present data. In the Bold BI application, the Forecasting feature has been implemented and the predicted data can be visualized in the Line chart widget. The technique that is used for forecasting the future data in the Bold BI is Exponential Smoothing. Before applying the forecasting techniques, Bold BI classifies the input data under two categories either Seasonal or Non-seasonal data. Depending upon the category of input data, the forecasting models will be applied.
What is Seasonal data and Non-Seasonal data?
Seasonal data refers to time-series data that experiences regular and predictable changes that recur over a period of time. Data fluctuations will occur periodically and will be cyclic over a period of time. Bold BI uses the Triple Exponential smoothing model to predict future data for Seasonal historical data.
Non-Seasonal data refers to data that does not fluctuate cyclically. Here, the data transmissions might be in a trend or univariate manner. Trend data has constant growth or downfall stripes over a period of time, Whereas the Univariate data does not have any constant fluctuations, and data variations were irrespective of any periodicity. Before predicting the Non-Seasonal data, Bold BI classifies the input data as either Trend or Univariate type and applies the forecasting model. For Trend and Univariate type input data, the Double Exponential smoothing and Single Exponential smoothing techniques were applied respectively.
Enabling Forecast in Bold BI dashboards
In Bold BI, the forecast option is available only in the Line chart widget. After assigning the Column and Value field in a Line chart, the forecast option can be enabled as shown in the following image,
Bold BI uses the Exponential smoothing technique for forecasting features. Exponential smoothing is a widely used forecasting technique for time series data and predictions would be accurate for seasonally fluctuated data.
About Exponential Smoothing
Exponential smoothing is a time series forecasting method for univariate data that can be extended to support data with a systematic trend or seasonal component. Exponential smoothing methods are the weighted average of past observation with the weights decaying exponentially as the observations get older that is more recent the observation, the higher the associated weights.
The exponential smoothing technique uses alpha, beta, and gamma values for prediction, and the forecasting output may vary based on these values. Bold BI uses an error prediction technique to choose the best alpha, beta, and gamma values to produce better forecasting results.
Classifications in Exponential smoothing
Exponential smoothing has been classified into three models and is used based on historical data.
Simple exponential smoothing
Double exponential smoothing
Triple exponential smoothing
How Bold BI chooses best Exponential model?
Bold BI automatically predicts the best suiting model among the three, based on the given input data, and to auto predict the type of input data, the auto-correlation technique is used.
Bold BI predicts a set of correlation values for the given input data and chooses the best Exponential model to apply based on the following conditions,
If the first index value is higher than the set of correlation values then the data will be considered as trend data and for trend data double exponential smoothing technique will be applied to predict the future data.
If the highest correlation value is present at the mid position then, the data is considered as seasonal data and for seasonal data triple exponential smoothing technique will be applied for forecasting.
If none of the above conditions are satisfied then, the data will be considered univariate, and the Single Exponential smoothing technique will be applied.
Enabling Seasonal forecasting in Bold BI
Instead of auto predicting the forecasting model, Seasonal forecasting can be enforced for any given input data by using the Seasonality property in the Bold BI Forecast Settings.
In the following image, the Seasonality value has been set as 6, hence without applying any auto prediction formulas, Bold BI will consider the given input data as seasonal data format and will apply the Triple Exponential forecasting technique for prediction.
Seasonality value can be set, only if familiar with the type of input data is seasonal and knowing of its exact seasonal value else seasonality property can remain unset so that Bold BI will apply the best forecasting technique using the auto-correlation technique.
Bold BI Forecasting for univariate data
A simple exponential smoothing model is a time series forecasting technique for univariate data that does not contain any trend or seasonal fluctuations.
The following image is an example of how univariate data looks,
Bold BI predicts a single smoothing factor or smoothing coefficient called alpha (α) for forecasting the univariate data.
The alpha value ranges from 0 to 1.
If the alpha value is close to 1 then, the most recent data will influence the forecast, whereas a value close to 0 will influence the older data for forecasting, and based on this forecasting output may differ.
Bold BI forecasting for Trend data
Double exponential is an extension of simple exponential smoothing that adds support to forecast the trend data.
Trend data has a constant growth over a period of time.
The following image showcases how a trend data looks,
For Double exponential, Bold BI predicts the alpha and beta values for prediction. Here, the alpha (α) parameter will be considered to influence the smoothing of level and the beta (β) parameter to influence the smoothing of a trend.
Both alpha and beta values range from 0 to 1 and based on the closest value either towards 0 or 1, the trend data differs.
Bold BI forecasting for seasonal cyclic data
Triple exponential smoothing is used to forecast time series data having seasonal fluctuations.
The following image showcases seasonal data,
For triple exponential smoothing, Bold BI uses the third equation for seasonality in addition to the existing two equations.
Uses alpha (α) constant to influence the smoothing of level and beta (β) constant to influence the smoothing of a trend, and gamma (γ) constant to influence the seasonality.
Bold BI matches with the combinations of constant values and chooses the best forecast output by predicting the error value.
A combination of alpha, beta, and gamma values having a lease error predicted value will be considered for forecasting the seasonal data.
# How to Configure a Connected App in Salesforce
This article explains the steps involved in creating an application in Salesforce and what scopes are required to be selected for using in the BOLD BI application for creating the dashboards.
The following section requires information about your organization, fill this form with the required information.Enable the OAuth settings for API Integration
Check the “Enable OAuth Settings” check box as shown in the following screenshot.
Fill the callback URL field with a valid callback URL.
:::Info
NOTE: If ng build command is not recognized in an angular application, use npm install -g @angular/cli@latest in an angular application in the vs code terminal.
:::
:::Info
NOTE: Replace column names (Column2, Column3, etc..) and database schema name according to your data source.. In the above query above, the database schema name is highlighted.
:::
:::Info
NOTE: SQL Server can also be connected to Bold BI in the designer as explained in this link: 
Bold BI has a great variety of sample data sources to choose from, and for this widget, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Two tabs will appear: “Properties” and “Assign Data.” I want my widget to display the top goal scorers from the World Cup, so under the “Properties” tab. Hence, I am going to change the name of my widget from the default “Chart1” to “Top Goal Scorers.”
For my purposes, a single title is sufficient, but you can add a subtitle and even a description of the widget if you like.
Then, I will click the “Assign Data” tab. You can drag different pieces of data to different parts of the widget (in this case, its columns) to display the statistics that interest you. I would like my column chart to display the top goal scorers, so I need to figure out how to make my widget show that information.
First, I will drag the “PlayerName” field to the “Columns” box. This ensures that each column will represent a player name.
Next, I will drag the “Goals” field to the “Values” box. This ensures that the value being displayed is the number of goals scored by each player.
My widget was created successfully, but as you can see, it is a bit unwieldy and difficult to read because it contains so much information. It would be helpful if I narrowed down the data that I would like to display.
In order to display the top six goal scorers, I simply need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Goals.”
This ensures that my data will be filtered such that the widget will only display the top six goal scorers.
If you would like the bars of your widget to be displayed horizontally rather than vertically, you can build a bar chart widget using exactly the same steps that are outlined above.
The bar chart and column chart widgets both compare values for a set of items; the only difference between them is that the column chart uses vertical bars while the bar chart uses horizontal bars.
# How to Create a Stacked Bar or Column Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Next, I will click the “Properties” tab and rename the widget “Goals and Shots by Team.”
Finally, I will click the “Assign Data” tab. I know that I want my data to be organized according to the different teams that played in the World Cup, so I am going to drag the “TeamName” field over to the “Columns” box.
I also know that there are two pieces of data I want to compare: the number of goals each team scored and the number of shots they took. To achieve this, I need to drag those two fields to the “Values” box.
My widget has now been created, but I am going to customize it further.
In order to display the top six goal-scoring teams, I simply need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Goals.”
This ensures that my data will be filtered such that the widget will only display the top six goal-scoring teams.
After I have filtered the data using the “TeamName” field, my widget looks like this.
Remember that the “Goals” measure is currently placed above the “Shots” measure in the “Values” box. However, the widget’s appearance will change depending on where you place the fields in the “Values” box.
For example, if I move the fields in the “Values” box so that the “Shots” measure appears above the “Goals” measure, my widget looks like this.
As you can see, changing the order of the fields in the “Values” box changes the way the data is displayed on the widget. In the first screenshot, goals are represented by the color blue, and they appear first in the bar. In the second screenshot, goals are represented by the color red, and they appear second in the bar.
I would like goals to display first in my widget’s bars, so I am going to move the “Goals” value so that it sits above the “Shots” value as it originally did. However, this is just another example of how customizable Bold BI’s widgets are.
Finally, I am going to add one more customization to my stacked bar widget: a multi-level drill down option. As the name implies, this option will allow me to drill down my data even further by displaying another level of information.
In this case, I would like to modify my widget so that if I click on a team’s bar (which shows the team’s total number of goals and shots), I can see a breakdown of which players on the team took shots and scored goals.
Making this customization will require me to change the data that is associated with my bars, so I need to navigate to the “Columns” box under the “Assign Data” tab. Currently, the only field in the “Columns” box is the “TeamName” field. If I would like my widget to display individual players’ statistics, I need to add the “PlayerName” field.
When I drag the “PlayerName” field to the “Columns” box, a pop-up appears asking if I want to enable multi-level drill down.
After I click “Yes,” my “Columns” box looks like this.
My widget has not changed its appearance; it still looks the same as it did before. However, because I have enabled multi-level drill down and have added the “PlayerName” field beneath the “TeamName” field, the functionality of my widget has changed. I can test the widget by clicking the “Preview” button in the upper right corner of my dashboard and navigating to the stacked bar widget.
Previously, the bars on my widget were not clickable. If I hovered over a bar, I could see the team’s number of goals or shots, but nothing happened if I clicked the bar itself.
Now that I have enabled multi-level drill down, I can click each bar of the widget to display additional information. In this case, I added the “PlayerName” field, so I will be able to see additional information about individual players.
As you can see, when I hover over a bar on the widget, I am still able to see the team’s number of goals or shots. Now, though, diagonal lines appear, indicating that I can click the bar to view additional information.
For example, if I click Belgium’s bar, I am able to see statistics for all six of the Belgian players who have taken shots and scored goals.
My drilled-down widget display has the same functionality as the main widget. If I hover over a bar, I am able to see the player’s full name, along with the total number of shots they took or goals they scored.
The drill up feature allows you to return to the previous view by clicking on the **“TeamName”** in the above widget.
As you can see, the multi-level drill down feature is extremely useful if you need to see multiple pieces of big-picture data (such as the sales numbers from several divisions) but also need access to more detailed information (such as the numbers for individual sales reps or a breakdown of the different products that each division has sold).
Multi-level drill down is available with 15 different Bold BI widgets. All of the widgets in the Comparison, Proportion, and Distribution sections of the widget menu offer this feature, allowing you endless customization options.
# How to Create a Bubble Map Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Bubble Map—South America Census Data” data source.
Simply select the data source you would like to use and click “Add.”
I would like my widget to display population data for the continent of South America, and now that I have moved the widget to my dashboard, I can assign data to it. First, I will click the “Settings” icon in the upper right corner of the widget.
Next, I will click the “Properties” tab and change the widget’s name from “BubbleMap1” to “South America Population Data.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the population of each country in South America, so I will drag the “Population” field to the “Values” box and the “Country” field to the “Shapes” box.
In this case, I have changed my bubble color to a custom shade of teal.
The “Basic Settings” section also offers me the option of changing my map’s appearance. A map of the world (“WorldMap Countries”) is selected by default; however, if I click the “Map” drop-down list box, I can choose from a variety of different national and continental maps.
Because I am only looking at data for South America, I am going to select the South America map option. My widget’s map immediately changes from a map of the world to a map of South America.
Now that my widget looks the way I want it to look, I can test its functionality by hovering over a few countries to see their population data.
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Choropleth Map—South America Census Data” data source.
Simply select the data source you would like to use and click “Add.”
Next, I will click the “Properties” tab and change the widget’s name from “ChoroplethMap1” to “South America Population Data.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the population of each country in South America, so I will drag the “Population” field to the “Values” box and the “Country” field to the “Shapes” box.
My widget now shows a color-coded map of South America, and if I hover over a particular country, I can view its population data.
The “Basic Settings” section also offers me the option of changing my map’s appearance. A map of the world (“WorldMap Countries”) is selected by default; however, if I click the “Map” drop-down list box, I can choose from a variety of different national and continental maps.
Because I am only looking at data for South America, I am going to select the South America map option. My widget’s map immediately changes from a map of the world to a map of South America.
Finally, if I continue scrolling to the “Range Color Settings” section of the “Properties” tab, I can click the arrow in the “Monochromatic” box to change the color scheme of my map.
I can choose a preselected color, or I can click the “Switcher” box in the lower left corner to create a custom color.
If I change my map’s color to a custom color, it immediately changes its appearance.
Now that my widget is complete, I can hover over each country on the map to see its population data.
# How to Create a Heat Map Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Heat Map-Weather Report” data source.
Simply select the data source you would like to use and click “Add.”
I would like my heat map to display the average temperature for five states in the southeastern US: Mississippi, Alabama, Florida, Georgia, and South Carolina.
Thus, I will drag the “Avg Temperature” field to the “Value” box.
I am going to leave the “Size” box empty for now, but we will return to it later.
Finally, I will drag the “Date” field to the “X-Axis” box and the “State” field to the “Y-Axis” box.
However, I do need to modify the settings of the “X-Axis” and “Y-Axis” boxes because they affect the dates and states that the widget displays, and this is the information I would like to change.
I will begin by looking at the “Date” field in the “X-Axis” box. After I dragged this field to the “X-Axis” box, its name changed to “Year(Date)” as the widget will display the data in this format by default.
However, I want my widget to show all of the months of the year, so I am going to click the “Options” button and select the “Month” option.
Now, the field’s name has changed to “Month(Date).”
Next, I will adjust the “State” field in the “Y-Axis” box by clicking the “Options” button and then clicking “Filter(s).”
At the top of the box that appears, I see a drop-down list box called “List.” Currently, every state in the US is selected; however, I can uncheck the “Check All” button and then manually select the states for which I would like to see data.
I am going to check the boxes beside Alabama, Florida, Georgia, Mississippi, and South Carolina, ensure that the “Include” button is selected, and click “Apply.”
After I click “OK” to exit the “Filters” box, my widget looks like this, and if I hover over a rectangle, I can see the average monthly temperature for that state. I am definitely on the right track, but there are a few additional modifications I would like to make.
To do this, I will click over to the “Properties” tab. First, I am going to rename my widget. I will call it “Average Monthly Temperatures—Southeastern US.”
Next, I am going to scroll down to the “Color Settings” section. This section contains two options for my widget’s color scale. The “Min Color” box determines which color is associated with lower values, and the “Max Color” box determines which color is associated with higher values.
Because I am working with temperatures, and because I would like to see a stark contrast between the lowest and highest values on my heat map, I am going to change these colors so that blue is my Min Color and red is my Max Color.
To do this, I need to click the down arrow in the Min Color box and then select the shade of blue I would like to use.
It is worth noting that you can click the “Switcher” button in the lower left corner of the box to create your own custom colors, but I am going to choose a shade of blue from the default options that appear and then click “Apply.”
Next, I will click the down arrow in the Max Color box, select a shade of red, and then click “Apply.”
I would also like to change the name of my heat map’s X-Axis. If I scroll down past the “Color Settings” section, I see a section titled “X-Axis Settings.” Currently, my axis title is “Month(Date),” which is the name of the field that I dragged to the “X-Axis” box in the “Assign Data” tab.
I am going to revise the text in this box so that it says “2017,” which is the year for which I am displaying data. I can immediately see this change reflected in my widget.
Now that my widget looks the way I want it to look, I am going to take a moment to explore its functionality.
As you can see, the heat map’s rectangles are shaded in different hues of red and blue. The hottest months are bright red, and the coldest months are bright blue. Months with temperatures in between the highest and lowest temperatures are a mix of the colors, with warmer months having more red and cooler months having more blue.
I can hover over any individual rectangle to see a state’s average monthly temperature. For example, I can see that Alabama’s average temperature in December was 46°F and that Florida’s average temperature for the same month was 66°F.
The dots are still color-coded; the hottest months are still bright red, the coldest months are still bright blue, and months with temperatures in between the highest and lowest temperatures are a mix of the colors, with warmer months having more red and cooler months having more blue. Now, though, my widget does not merely display information through the dots’ colors; it also conveys information through the dots’ sizes.
Here is a final example. If I drag the “Avg Precipitation” field to the “Size” box, then larger dots will represent higher amounts of precipitation, and smaller dots will represent lower amounts of precipitation. The colors red and blue still indicate which months had the highest and lowest temperatures. Now, however, I am also able to quickly see which states and months had the highest and lowest precipitation numbers by looking at the widget’s dot sizes.
As you can see, this functionality can be very useful as it provides a quick visual reference for not one but two pieces of data simultaneously (in this case, the states’ average temperatures and average precipitation, with the average temperature represented by color and the average precipitation represented by dot size).
# How to Create a Grid Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Next, I will click the “Properties” tab and change the widget’s name from “Grid1” to “Goals Scored by Player.”
Finally, I will click the “Assign Data” tab. I know that I want my widget to display the number of goals scored by each player in the World Cup, so I will drag the “PlayerName” and “Goals” fields over to the “Columns” box.
Changing the order of the fields in the “Columns” box will change the order of the columns on the widget. I would like the players’ names to display in the first column on my widget, so I will leave the fields in their current positions in the “Columns” box.
Now that my widget displays the desired information, I will customize it further and test its functionality.
After experimenting with these settings, I have decided to change my header background color to a custom shade of green by clicking the down arrow in the “Background” color box, selecting the “Switcher” box in the bottom left corner, and moving the cursor around the color swatch. I have also decided to remove the horizontal lines from my widget.
My widget now looks like this.
I would like to test the widget’s sorting functionality, but before I do, there is one more thing I would like to change. Currently, the columns of my widget display the names of the fields that I dragged to the “Columns” box (“PlayerName” and “Sum Of Goals”).
The column names accurately reflect the data they display, but they are field names—they are not the titles I would ordinarily give to my columns.
To revise my column names, I can scroll down to the “Column Settings” section of the “Properties” tab and click the “Edit Column Names” button. I can then type in the new column names and click “OK,” and the column names on my widget immediately change.
However, if I click the “Goals” header again, the goals will be displayed in descending order.
If you prefer to sort your data by player name, you can click the “Player” heading to display the names in ascending or descending alphabetical order.
As you can see, the simple but powerful grid widget allows you to easily display and sort key pieces of data, and you can even filter the data itself to customize the information the widget displays.
For example, if I want my widget to display only the top ten goal scorers in the World Cup, I can navigate back to the “Assign Data” tab, click the “Options” button that appears beside the “PlayerName” field, and click “Filter(s).”
Then, I can click the “Rank” checkbox, select “Top” from the “Mode” drop-down list box, change the “Count” option to 10, change the “Column” drop-down list box to “Goals,” and click “OK.”
Now, my widget will display only the top ten goal scorers from the World Cup. However, filtering the data has changed my sorting settings, so I will once again click the “Goals” header to sort by the number of goals that were scored in descending order.
# How to Create a Tree Map Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our “Comparison Chart—Olympic Medals” data source.
Simply select the data source you would like to use and click “Add.”
I would like my widget to display the gold and silver medals earned by each country, so I will drag the “Gold” and “Silver” fields to the “Values” box and the “Country” field to the “Columns” box.
:::Info
Note: As you create your tree map, you may notice that some rectangles are not displaying the information they should. For example, in the screenshot to the right, five of the rectangles are not displaying countries’ names.
:::
At the widget’s current size, there is not room in these rectangles to display the countries’ names. To fix this issue, simply resize your widget by dragging its edges.
As you can see, each rectangle displays a country name in the resized widget.
Now that my tree map displays the data I want it to display, I can click the “Properties” tab to further customize the widget. First, I am going to change the widget’s name from “TreeMap1” to “Top 15 Gold Medal Countries.”
Then, I am going to scroll down to the “Range Color Settings” section to explore my color scheme options.
The “Color Type” drop-down list box offers two options: “Monochromatic” (which is selected by default) and “Range Color.”
If the color type is set to monochromatic, I can click the arrow in the “Monochromatic” box to change the tree map’s color. I can choose a preselected color, or I can click the “Switcher” box in the lower left corner to create a custom color.
For example, I could change my tree map color to a custom shade of green.
Alternatively, I can change the “Color Type” drop-down list box to “Range Color.” Now, the widget will assign different colors to different ranges of data in the tree map.
By default, the rectangle with the highest value will be yellow. Rectangles in the middle of the value range will be red, and rectangles at the low end of the value range will be blue.
You can easily change the colors for the low, middle, and high value ranges by clicking the arrows in their respective boxes (just as I did when I changed the tree map’s color from blue to green when the color type was set to monochromatic).
Finally, I am going to test my widget’s functionality. Whether I set the “Color Type” drop-down list box to “Range Color” or “Monochromatic,” I will be able to see the data for any given country by hovering over it with my mouse.
# How to Create a Card Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Now, I am ready to assign data to my widget by clicking the “Assign Data” tab. If I would like to see teams’ assist data, I need to drag the “Assists” field to the “Values” box and the “TeamName” field to the “Columns” box.
Then, I need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to the desired number. Finally, I need to change the “Column” drop-down list box to “Assists.”
Now, my widget only shows the six teams with the most assists in the World Cup.
Next, I am going to add the multi-level drill down option to my widget. As its name suggests, this function allows me to add another layer of data to my widget.
In this case, I would like to modify my widget so that if I click on a team’s doughnut segment, I can see a breakdown of which players on the team had assists.
Making this customization will require me to change the data that is associated with my doughnut segments, so I need to navigate back to the “Columns” box under the “Assign Data” tab. If I want my widget to display information for players as well as teams, I need to drag the “PlayerName” field to the “Columns” box.
When I try to do so, a pop-up appears asking if I want to enable multi-level drill down.
After I click “Yes,” my “Columns” box displays the “PlayerName” field beneath the “TeamName” field, and multi-level drill down has been enabled. We will explore this feature’s functionality soon, but before doing so, I want to ensure that my widget looks the way I want it to look.
Right now, my doughnut’s segments are each associated with a percentage value. Though percentage values can be useful in many situations, they do not really suit my purposes, so I would like to replace them. I would also like to display a key or guide of some sort so that I know which team each color represents without hovering over each segment.
To achieve this, I can click the “Properties” tab. If I scroll down to the “Basic Settings” section, I can click the “Show Legend” option. My doughnut widget immediately displays a guide demonstrating which segment colors are associated with which teams.
I would still like to remove the percentage values from the widget, and in the “Basic Settings” section, I see a drop-down list box called “Data Label.” Currently, the “Percentage” option is selected.
If I select the “Value” option instead, my widget will replace the percentage value with the number of assists that each team has. It is worth noting that you can display both the numeric value and percentage value if you wish, but for this widget, I would only like to display the numeric value.
Now, my widget looks like this.
Now that my widget looks the way I want it to look, I would like to explore the multi-level drill down feature to ensure that it functions properly.
I can test the widget’s functionality by clicking the “Preview” button in the upper right corner of my dashboard and navigating to the doughnut widget. If I hover over a doughnut segment, I see the name of the team and the team’s total number of assists. The diagonal lines indicate that I can click the segment to view additional information.
If I click on Belgium’s segment, I can see individual Belgian players’ total numbers of assists. The drilled-down widget display also contains a legend demonstrating which segment color is associated with which player.
Multi-level drill down is available with 15 different Bold BI widgets. All of the widgets in the Comparison, Proportion, and Distribution sections of the widget menu offer this feature, allowing you endless customization options.
The drill up feature allows you to return to the previous view by clicking on the **"TeamName"** in the above widget.
Finally, it is worth noting that if you would like to create a pie chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the doughnut widget and the pie chart widget is that the pie widget does not have a white circle in its center, so its segments have a slightly different appearance (as you can see in the screenshot to the right). However, the widgets’ functionalities are the same.
# How to Create a Pyramid or Funnel Chart Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “OK.”
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Attempts On Target” field to the “Values” box. I want to see the data for individual players (rather than teams), so I will drag the “PlayerName” field to the “Columns” box.
Now, my widget’s data is far easier to read; however, I would like to make a few additional changes.
First, I would like to replace the percentage values on my widget with numeric values. Second, I would like to make my widget display a legend so I can see which color represents which player without hovering over the player’s pyramid segment. I can make both of these modifications in the “Properties” tab.
After I click the widget’s “Options” button and navigate to the “Properties” tab, I see a section titled “Basic Settings.”
In this section, I can click the checkbox beside the “Show Legend” option to make my widget display a guide demonstrating which segment color is associated with which player.
I can also change the “Data Label” drop-down list box option to “Value” in order to make my pyramid display numeric values instead of percentages.
Now, my pyramid widget looks the way I want it to look; it displays the numeric value of each player’s assists, and it contains a color-coded legend demonstrating which pyramid segment represents each player.
It is worth noting that if you would like to create a funnel chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the pyramid widget and the funnel widget is that the pyramid widget displays values in a progressively increasing manner while the funnel widget showcases values in a progressively decreasing manner.
# How to Create an Area Chart Widget
Bold BI has a great variety of sample data sources to choose from, and for this dashboard, I am selecting our 2018 World Cup data source.
Simply select the data source you would like to use and click “Add.”
Finally, I will click the “Assign Data” tab. I want my widget to display the number of penalty goals that were scored in the World Cup, so I need to drag the “Penalties Scored” field to the “Values” box.
I want to see the data for individual players (not teams), so I need to drag the “PlayerName” field to the “Columns” box.
My widget has now been created, but given the sheer amount of information it displays, I would like to filter my data to make the widget easier to read
Then, I need to click the “Rank” checkbox, select “Top” from the drop-down list box for the “Mode” option, and change the “Count” option to 6. Finally, I need to change the “Column” drop-down list box to “Penalties Scored.”
Now, I am happy with my spline widget’s appearance, but I would like to customize it so that if I click on a player’s name, I am able to see the name of their team.
To do this, I will enable the multi-level drill down feature. As the name implies, this option will allow me to drill down my data even further by displaying another level of information.
To enable multi-level drill down, I will navigate back to the “Assign Data” tab. Making this customization will require me to modify the data that is associated with players’ names, so I need to locate the “Columns” box.
Currently, the only field in the “Columns” box is the “PlayerName” field. If I would like my widget to display the names of the players’ teams, I need to add the “TeamName” field to the “Columns” box.
Thus, I will drag the “TeamName” field to the “Columns” box and place it underneath the “PlayerName” field. When I do this, a box will pop up asking me if I want to enable multi-level drill down.
After I click “Yes,” the “Columns” box displays the “PlayerName” field on top of the “TeamName” field. The widget’s appearance has not changed, but multi-level drill down is now enabled. This means that I can click the data points on my spline widget to obtain additional information (in this case, the name of the team that each player represented in the World Cup).
I can test the widget’s functionality by clicking the “Preview” button in the upper right corner of my dashboard, navigating to the spline widget, and hovering over a player’s dot on the widget. White diagonal lines appear within the blue dot, which indicates that I can click the dot to view additional information.
After I click the dot, the player’s data is displayed, and the name of their team appears at the bottom of the widget.
The drill up feature allows you to return to the previous view by clicking on the **"PlayerName”** in the above widget.
Finally, it is worth noting that if you would like to create a line chart widget, you can do so using exactly the same steps that are outlined above. The only difference between the spline widget and the line widget is that the spline widget uses smooth curves to connect data points while the line widget uses straight lines to connect data points. However, the widgets’ functionalities are the same.
# How to Add a List Box Filter
My area chart widget highlights the maximum temperature for each day of August 2018 (if you have not already done so, please feel free to read the post outlining how I created my area chart widget).
First, I need to drag the date picker filter from the “Filters” section of the widget menu onto my dashboard.
Next, I will click the “Assign Data” tab and will drag the “Date” field to the “Column” box.
Now, my filter has been created. To test my filter’s functionality, I can click the “Preview” button in the upper right corner of my dashboard and navigate to the date picker.
If I would like to clear the filter, I need only click the “Clear Master Filter” button that appears in the upper right corner of my date picker, and the widget will return to its original appearance.
# How to Create a KPI Card Widget
Simply select the data source you would like to use and click "Add".
To assign data to my widget, I need to click the “Settings” button in the upper right corner of my widget. Then, I will click the “Assign Data” tab.
Now, I am ready to assign data to my widget. After clicking the “Assign Data” tab, I will drag the “Max Temp” field to the “Values” box and the “Date” field to the “Argument” box.
My widget has now been created, but it looks a bit odd. This is because my data source only contains temperature data for one month, August 2018, but my widget is displaying the date in a year format (rather than showing each individual day of August as I intended).
You may have noticed that though the “Dimensions” box contains a field called “Date,” the field’s name changed to “Year(Date)” when you dragged it over to the “Argument” box. This is because the widget shows data for the entire year by default.
This format would be helpful if I wanted to compare data across multiple years, but since I am only looking at one month of data, I need to revise my date display criteria. It does not make sense for my widget to supposedly display data for all of 2018 if I am only examining one month of temperature data.
To change the date settings for my widget, I need to navigate back to the “Argument” box and click the “Options” button beside the “Year(Date)” field. When I do, I see a list of different date display options: Date, Year, and More (clicking the “More” button will provide you with additional options).
You can set “Range” and “Period” options from the Relative Date Filter menu. You can also set a specific date by enabling “Link to Specific Date”.
As we noted earlier, the “Year” option is selected by default. In order to see the maximum temperature data for each individual day of the month with the year, I am going to click the “Day Month Year” option.
After I click “Day Month Year,” I can see that the name of the date field in the “Argument” box has been changed to “DayMonthYear(Date),” and my widget’s appearance has been updated accordingly.
I can select a date range by dragging the sliders. For example, if I want to see data for the last 10 days of August, I can drag the sliders accordingly, and my area chart widget will show data for the selected date range.
If I would like to clear the applied filter, I just need to click the “Clear Filter” button that appears in the upper right corner of my range navigator, and the widget will return to its original appearance.
# How to Create a Pivot Grid Widget
Simply select the data source you would like to use and click “Add”.
To compare the performance of each player, I need to drag the “Goals” and “Matches” fields to the “Value(s)” box and the “PlayerName” field to the “Column” box.
When I click the “Edit” option, a dialog will open and in that I am going to enable “Rank” and choose the Count as ’5’ for the Rank Column.
After clicking “OK”, my widget will show the Top 5 Players performance in world cup.
With the help of properties column, I can make few additional changes to my widget. First, I would like to change my widget draw type as “Radar”. Second, I would like to see the medals received by each country without hovering over the Country name. This can be achieved by choosing the Draw Type as “Radar” and by enabling the “Show Value Label” under the “Basic Settings”.
Now, my widget looks the way I want it to look; it displays the player’s performance with Radar visualization.
Under the “Properties” column, I can change the color of the Legend name by changing it in a “Series Palette” section.
Also, I can customize the name and position of the Legend under “Legend Settings” in the “Properties” column.
# How to Create a Radial Gauge Widget?
Simply select the data source you would like to use and click “Add”.
I want to compare the Current Month and Previous Month expenses of each product. To do this, I need to drag the “Previous Month Expense” field to the “Actual Value” box and the “Current Month Expense” field to the “Target Value” box and “Product Name” field to the “Series” box.
Now my widget looks like below and show the Variation and Percent of Target with the sum of Previous Month and Current Month Expenses. Here, I can see the values by hovering over the widget.
In the “Properties” column, I can customize the value pointer with available types and colors under the “Pointer Settings”.
Here, I am choosing the “Value Pointer” as “Range with Needle” and changed the color of Range Pointer and my widget looks like below.
In the “Properties” column, I can enable the “Show Range” to show the selected range of values with selected range color under the “Range Settings”.
Now my widget will show the range of values with varying color as shown in below.
The following example will help to show a Radial Gauge with varying color based on the condition provided for Current Month Expense.
Now my widget will look like below with the applied formatting.
# How to Create a Combo Chart Widget
Simply select the data source you would like to use and click “Add”.
To compare the performance of each player, I need to drag the “Goals” field to the “Value(s)” box, the “Attempts On Target” field to the “Secondary Value(s)” box, and the “PlayerName” field to the “Column” box.
When I click the “Edit” option, a dialog will open. There, I am going to enable “Rank” and set the Count to ‘5’ for the “Goals” Column.
After clicking “OK,” my widget will show the top 5 goal scorers in the World Cup, along with their attempts on target. Here, I can see the values by hovering over the widget.
With the help of the “Properties” column, I can see the number of goals scored and the number of attempts by enabling “Show Value Labels” in “Basic Settings.”
Also, I can change the chart type and axis type using the “Change” button in “Basic Settings.”
Here, I would like to change the chart type for my Primary Value(s) to “Line.”
After clicking “OK,” my widget shows line graphs detailing the top 5 goal scorers with their numbers of attempts in the World Cup.
Also, I can customize the name and position of the Legend under “Basic Settings” in the “Properties” column.
Under the “Axis” section in the “Properties” column, I can customize axis settings like Show or Hide Axis Title, Edit Axis Range, and Label Rotation.
After clicking the “Add” button, a dialog opens where I can customize the trendline.
Now my widget shows the trend you see below.
Next, I would like to explore conditional formatting in the combo chart. With this feature, I can modify the chart’s colors based on certain conditions.
The conditional formatting option is available in the “Formatting” section of the “Properties” column. Enable “Advanced Setting” to add conditions and formatting in the dialog.
The conditional formatting dialog even allows me to add a condition based on a completely different field than the one already configured. I can also choose various condition types and formatting options as shown in the following image.
The following example will help to show a combo chart with varying colors based on the condition provided for goals scored by top 5 players.
Now that this formatting has been applied, you can see the updated widget below.
# How to Create a Bing Maps Widget
Below, you can see what the widget looks like with the “Aerial” theme.
I know I can change the marker shape in “Marker Settings” under the “Properties” column. By default, the marker shape is “Circle.”
Now, my widget shows population data for countries, along with the countries’ flags.
In the “Properties” column, I can browse images from my local system, bind a URL from my data, or build a parameterized URL.
I would like to visualize the country “India” with a different marker shape, color, and size. So, I am going to format the marker as you see below.
With this formatting applied, my widget will look like the image below.
# How to Apply Hierarchical and Flat Filtering in Widgets
Bold BI has provided support for analysing data to showcase the hierarchical view in widgets. Users can apply a filter to the hierarchical view on widgets.
Enable the OAuth settings for API Integration
