How to Remove Null or Blank Values in Bold BI Widgets

Overview

Null or blank values in Bold BI can appear in widgets, combo box filters, and other visuals, affecting user experience and report accuracy. These may come from actual NULL values or empty strings in the data source.

This article shows two effective ways to remove them:

• Widget Level — Affects only the specific widget.
• Data Source Level — Removes nulls across all widgets using that dataset.

A. Remove Null Values at Widget Level (Recommended for Specific Widgets)

Steps

Step 1. Open the dashboard in Edit mode.

Step 2. Select the widget showing null/blank values.

Step 3. Click the Settings (gear) icon to open the Assign Data panel.

Step 4. In the Filters section, drag and drop the column(s) containing null/blank values.

Step 5. Click the filter settings for the added column.

Step 6. In the list view, uncheck (Null), blank (empty), or unwanted values.

Use Include or Exclude mode as needed.

Step 7. Click Apply.

Step 8. Repeat for other columns if needed. The widget will now display without null/blank values.

B. Remove Null Values at Data Source Level (Global Fix)

Use this when nulls should be excluded from all widgets using the dataset.

Steps

Step 1. Open the dashboard and click the Data Source icon to enter the Data Source Designer.

Step 2. Click the funnel (Filter) icon to open Data Filters.

Step 3. Create a new filter condition:

• For NULL values: Column Is Not Null
• For empty strings: Column Not Equal To '' (blank)

Step 4. Save and apply the changes. Refresh affected dashboards.

C. Alternative: Replace Null/Blank Values

Instead of filtering, you can replace nulls using Bold BI’s Replace Value feature (Data Source → Column Level) to convert them to meaningful defaults (e.g., “N/A”, 0).

When to Use Each Method

Troubleshooting

• (Null) still appears — Ensure you unchecked it in List view and republished the dashboard.
• Filter option missing — Confirm the column is added to Filters in Assign Data.
• Performance impact — Prefer Data Source filters for large datasets.
• Changes not visible? Clear browser cache or republish.

Best Practices

• Clean data at the source (database/SQL query) whenever possible.
• Use Replace Value for better UX instead of hiding rows.
• Document filters for team maintainability.
• Test combo box / slicer filters after changes.

Conclusion

Removing or replacing null values improves dashboard cleanliness and user experience. Start with Widget-level filters for quick fixes, then move to Data Source level for broader impact.

Related Articles

• Configuring Widget Filters
• Configuring Replace Value Support
• Data Source Data Filters
• Handling Empty Points in Charts