How to Access JSON with Multiple Nested Levels in Bold BI Web API Connector

Steps to Access JSON with Multiple Nested Levels in Bold BI Web API Connector

Introduction

This article provides a step-by-step guide on how to access and connect to JSON data with multiple nested levels using the Bold BI Web API connector. This process is essential for users who need to work with complex JSON structures in their data visualization projects.

Step 1: Create a Data Source Without Inner Nested Select Schema Levels.

• Begin by connecting to the JSON data. If the JSON structure contains an anonymous array without inner nested arrays, Bold BI will connect to it seamlessly.
• You can connect to the data source URL without encountering any issues, allowing you to create a data source in Bold BI without any complications.

Step 2: Create a Data Source with Inner Nested Select Schema Levels.

• If the JSON data includes one or more inner nested arrays (denoted as N inner nested arrays), you will need to take additional steps.
• Upon connecting to the data source URL, Bold BI will load the data, excluding the inner arrays. The data will be displayed in the schema selection, with the inner arrays in an unchecked state.
  
  
• This approach is designed to allow you to selectively choose the required nodes from the schema.
• By following this method, you can effectively connect to and utilize data from inner nested arrays within Bold BI, enhancing your data analysis capabilities.

Conclusion

Accessing JSON data with multiple nested levels in Bold BI requires careful attention to the structure of the data source. By following the steps outlined above, users can successfully connect to both simple and complex JSON structures, ensuring that they can fully leverage the power of Bold BI for their data visualization needs.

Note:

When working with a large number of nested schema levels that generate numerous rows and columns, users may experience prolonged loading times and potential out-of-memory issues when connecting to a web API data source. As a best practice, utilize only the necessary schema levels for your analysis.