Summary
Slow reports and dashboards frustrate users and break AI-powered experiences like Copilot chat and Fabric IQ data agents. In this module, you learned a systematic approach to find and fix those performance problems.
You started with Performance analyzer to identify which visuals are slow and whether the bottleneck is in the DAX query, visual rendering, or data source. From there, you learned how to optimize DAX calculations using variables, efficient filter patterns, and the right aggregation functions. You explored cardinality reduction techniques to shrink model size and speed up queries, and you learned when aggregations (both user-defined and automatic) can accelerate queries on large datasets.
With these skills, you can diagnose performance issues, apply targeted fixes, and verify the improvement. Your semantic models are faster for human users and responsive enough to support AI-driven interactions.