When diagnosing slow DAX performance, which two elements can you view in Power BI to understand how time is spent?

When diagnosing slow DAX performance, which two elements can you view in Power BI to understand how time is spent?

• A. Query Timings tab and Server Timings tab
• B. Performance Analyzer and DAX Studio
• C. Visual Studio Diagnostic Tools
• D. Data view and Model view

Answer: (A)

When a report slows down, you want to separate the work the client does from what the engine does with the data. That split is shown in Power BI’s diagnostic view through two timing views: the Query Timings tab and the Server Timings tab. The Query Timings tab lets you see how long each query takes from the moment Power BI requests the data for a visual to when the results come back. This helps you gauge client-side factors, such as the time spent sending the query, waiting for a response, or rendering the visual. The Server Timings tab reveals the time spent inside the data engine itself while processing the DAX query—things like measure evaluation and storage engine work. This shows how much work the engine is doing to compute the results. By looking at both together, you can tell where the bottleneck lies. If the Query Timings are long but Server Timings are short, the delay is likely on the client side or in data transfer. If Server Timings are long, the heavy lifting is happening in the engine, pointing to potential optimizations in the DAX formulas, data model, or storage layout.

When a report slows down, you want to separate the work the client does from what the engine does with the data. That split is shown in Power BI’s diagnostic view through two timing views: the Query Timings tab and the Server Timings tab.

The Query Timings tab lets you see how long each query takes from the moment Power BI requests the data for a visual to when the results come back. This helps you gauge client-side factors, such as the time spent sending the query, waiting for a response, or rendering the visual.

The Server Timings tab reveals the time spent inside the data engine itself while processing the DAX query—things like measure evaluation and storage engine work. This shows how much work the engine is doing to compute the results.

By looking at both together, you can tell where the bottleneck lies. If the Query Timings are long but Server Timings are short, the delay is likely on the client side or in data transfer. If Server Timings are long, the heavy lifting is happening in the engine, pointing to potential optimizations in the DAX formulas, data model, or storage layout.