Focus on this objective today: Optimize enterprise-scale semantic models: Implement performance improvements in queries and report visuals. Explain it in your own words, apply it to one realistic scenario, and verify the details against the official source. Source context: Read in English Optimize semantic model performance Module 9 Units Feedback Advanced Data Analyst Microsoft Fabric Power BI Diagnose and fix semantic model and report performance issues. Use Performance analyzer to identify bottlenecks, optimize DAX calculations, reduce cardinality, and implement aggregations to improve query speed. Learning objectives By the end of this module, you're able to: Use Performance analyzer to identify performance bottlenecks Optimize DAX calculations for better query performance Reduce cardinality levels to improve model efficiency Implement aggregations to accelerate queries on large datasets Apply a systematic approach to troubleshoot common performance issues Add Prerequisites Semantic model design experience and DAX authoring skills Introduction min Use Performance analyzer to diagnose issues min Optimize DAX calculations min Reduce cardinality for better performance min Implement aggregations min Troubleshoot common performance issues min Exercise: Diagnose and fix a slow report min Knowledge check min Summary min Take the module assessment Module Assessment Results Assess your understanding of this module.
Objective
Optimize enterprise-scale semantic models: Implement performance improvements in queries and report visuals