For determining whether queries are mapped to aggregated data via user-defined aggregations, which single tool is most suitable for profiling queries in a semantic model?

For determining whether queries are mapped to aggregated data via user-defined aggregations, which single tool is most suitable for profiling queries in a semantic model?

• A. DAX Studio
• B. Performance Analyzer
• C. SQL Server Profiler
• D. Tabular Editor

Answer: (C)

The key idea is to observe exactly how a semantic model processes queries at the server level to see if they are routed to aggregated data via user-defined aggregations. SQL Server Profiler is the most suitable single tool for this because it hooks into the server-side engine (Analysis Services or SQL Server) and captures real-time traces of the executed queries, their texts (DAX/MDX for semantic models), timings, and the components involved. With these traces, you can identify whether a given query is being fulfilled by the aggregated structures defined in the model, showing the path the engine takes when UDAs come into play. DAX Studio specializes in profiling DAX queries and is excellent for detailed client-side query analysis, but UDAs operate at the storage/engine level. Performance Analyzer in Power BI gives you in-report timings and visuals-level queries, which is useful for diagnosing slow visuals but doesn’t provide the full server-side trace needed to confirm aggregation routing. Tabular Editor focuses on editing the model’s metadata and definitions rather than profiling query execution.

The key idea is to observe exactly how a semantic model processes queries at the server level to see if they are routed to aggregated data via user-defined aggregations. SQL Server Profiler is the most suitable single tool for this because it hooks into the server-side engine (Analysis Services or SQL Server) and captures real-time traces of the executed queries, their texts (DAX/MDX for semantic models), timings, and the components involved. With these traces, you can identify whether a given query is being fulfilled by the aggregated structures defined in the model, showing the path the engine takes when UDAs come into play.

DAX Studio specializes in profiling DAX queries and is excellent for detailed client-side query analysis, but UDAs operate at the storage/engine level. Performance Analyzer in Power BI gives you in-report timings and visuals-level queries, which is useful for diagnosing slow visuals but doesn’t provide the full server-side trace needed to confirm aggregation routing. Tabular Editor focuses on editing the model’s metadata and definitions rather than profiling query execution.