How do I optimize Power BI report performance when dealing with large datasets in DirectQuery mode?

All answers to this question.

Performance in DirectQuery usually bottlenecks at the data source. First, ensure you are using "User-defined Aggregations." This allows Power BI to query a small, cached "agg" table for high-level summaries while only hitting the raw SQL data for granular details. Also, limit the use of complex DAX measures that require row-level logic; push as much calculation as possible back to the SQL layer via Views or Stored Procedures. Lastly, check the "Assume Referential Integrity" setting in your relationships to allow for inner joins instead of outer joins, which are significantly faster for the SQL engine to process.

   Answered 2025-06-18 by Margaret Brennan

Those are solid technical fixes. But have you looked into the "Query Reduction" settings in Power BI Desktop to stop slicers from instantly refreshing every visual until the user hits an 'Apply' button?

   Answered 2025-06-20 by Brian Fitzgerald

• That is a very practical suggestion, Brian. To answer your point, I actually implemented the "Apply" button on our multi-select slicers last week. It significantly reduced the number of redundant queries hitting the server while users were still making their selections. It hasn't solved the core latency for the final execution, but it definitely improved the perceived performance and reduced the overall load on our SQL cluster during peak hours.

     Commented 2025-06-25 by Jessica Thompson

Make sure you aren't using bidirectional cross-filtering unless absolutely necessary. It creates highly complex SQL queries that can easily crawl to a halt with millions of rows.

   Answered 2025-07-02 by Steven Walker

• Steven is 100% correct. I've seen bidirectional filters turn a simple SELECT into a nightmare join structure. Sticking to a clean Star Schema is the best way to keep Power BI happy.

     Commented 2025-07-05 by Margaret Brennan