Optimizing SQL Data Source Indexing and Configuration for Better Performance in Bold BI

When working with Bold BI, it’s crucial to optimize your SQL data source indexing and configuration for the best performance. Here are some recommendations:

Indexing Data

Indexing data can increase storage size, but it also improves data accessing speed. It’s generally recommended to index the data based on fields that are used for grouping or performing filtering. More details can be found in this blog post.

Separating the Serving Layer

Consider separating the serving layer for the Dashboard from the original database server. This means having a separate server running only to serve the Dashboard, Reporting, and Analytics use case. This way, the transactional database server or production DB performance will not be affected.

Creating Data Marts

Instead of having a duplicate copy of records in the serving layer, another option is to create Data Marts. These are tables with aggregated data that serve as the serving layer for the dashboard. This approach eliminates the need for large aggregations over the data, thereby improving query performance.

Adding Partitioning Techniques

Implementing partitioning techniques can also significantly improve performance.

For more information on the impact of indexing on data, refer to this document.

For more details on how to aggregate data based on the dimension column, refer to this document.

By following these recommendations, you can optimize your SQL data source indexing and configuration for better performance in Bold BI.