Best practices for Power BI performance & security: Part II

Following on from our previous post, here is the second in our series on improving performance and security in Power BI implementations through PowerBI development.

• Use different Power BI gateways for Live Connection & Scheduled Data RefreshIf the same gateway is used for Scheduled Data Refresh and Live Connection, Live Connection performance will slow down when Scheduled Data Refresh is active. Avoid this issue by creating separate gateways for Live Connection and Scheduled Data Refresh.
• Test custom visual performance for fast report load timeUncertified custom visuals are generally not tested by the Power BI team. Custom visuals can perform poorly when handling large datasets or complex aggregations, so if a custom visual performs poorly, consider replacing it with a different visual.
• Limit complicated complex measures and aggregations in data modelsPush calculated columns and measures to the source where possible. The closer they are to the source, the higher the likelihood of improved performance. Create calculated measures instead of calculated columns, and use star schema to design data models.
• Use slicers sparinglySlicers are a great way of allowing users to navigate data, but they come at a cost. Each slicer generates two queries: One gets the data, and the other fetches selection details. Creating too many slicers negatively impacts performance. To evaluate which slicers are infrequently used, use the Filter pane and remove unnecessary slicers.
• Ensure the Power BI report and data source are in the same regionWith the tenant and data source in the same region, you can reduce network latency. The results are faster data transfer and faster query execution.
• Import only necessary fields and tables instead of entire datasetsEnsure the model is as narrow and lean as possible. Power BI works on columnar indexes; longer and leaner tables are preferred.
• Ensure the cache update frequency aligns with the data source refresh frequencyCache update frequency should be set at similar intervals to data source refresh frequency. By default, Power BI cache update frequencies are set to one hour. If, for example, your data set refreshes only once per day, you should update the cache frequency accordingly.