In Power BI, if the results of a DAX measure are not as expected, the following measures can be taken in order to troubleshoot and fix the problem as much as possible:
Assess row and filter context: Analyzing DAX calculations considers the context, which includes, but is not limited to, row and filter scopes. Simple isolated visualizations such as tables help understand the behavior of the measure when different filters are applied. This assists in understanding whether the measure is inaccurate as a result of context.
Decompose the measure: When the measure is long, complicated, and intricate, decompose it into shorter or simpler measures or resilient calculations. Develop temporary measures for the various components of the measure being tested. This will assist in determining the location of the problem and the point at which the calculation fails to meet the anticipated outcome.
Utilize the DAX Studio Tool: DAX Studio is a high-performance tool for working with Power BI, especially for performance analysis and debugging. You can run your DAX expressions in it and check the results proportioned at each stage of query execution. DAX Studio also provides performance metrics, including total query execution time, which can be used to evaluate possible shortfalls in system performance.
Put Practices to the test with CALCULATE and FILTER: Because CALCULATE and FILTER functions change context, investigate how they relate and how they affect a measure you created. Consider performing some tests by using CALCULATE with no other filters without reserving any results since that is part of the aim and then fading in other filters back in order to resolve the question.
Specify with VAR where necessary: Specifying parts of your measure with VAR improves the readability and the debuggability of the calculation. Because you can define certain calculations in variables, it becomes possible to encapsulate and functionalize each section of the measure.
Evaluate with Performance Analyzer: This tool in Power BI will help you determine which visuals or measures are taking more time than average.
