How I start using DAX Query View in Power BI.

In this writing, I’ll share how I began using the DAX Query View feature in Power BI Desktop, with the hope that by the end, readers will be confidently clicking that button without a second’s hesitation.

Before I share about my experience—which, admittedly, goes a bit off from the core purpose of the DAX Query View feature—I’d like to give a quick overview of what DAX Query View is. For more detailed information, check out the official Microsoft documentation below.

Link to the Microsoft website: DAX query view - Power BI | Microsoft Learn

The DAX Query View feature in Power BI is a powerful tool for data professionals, offering valuable insights into the execution of DAX queries. By providing a detailed view of the underlying queries driving the visualizations, it enables users to optimize DAX queries, streamline efficiency, and quickly identify potential issues. Whether you're fine-tuning complex calculations or troubleshooting data quality concerns, DAX Query View offers the transparency and control necessary to make informed decisions, ultimately enhancing both data accuracy and user experience.

It may seem like every Power BI developer should immediately start using this feature, and yet, even after learning how valuable DAX Query View is, I found myself rarely using it.

The moment I began confidently and frequently clicking the " Run in DAX Query View" button in Power BI Desktop came when I stumbled upon an issue in one of my DAX measures. The calculation, which was supposed to ignore the filter context applied to the visual and the page, produced an incorrect result. Surprisingly, I uncovered the problem and fixed it with ease—all thanks to DAX Query View.

Let me walk you through my experience using the sample semantic model.

As described above, Page 1 served as the landing page of the report, where I quickly noticed that the total sales for the entire period amounted to approximately 1.37 million.

While developing the report pages, I noticed that one of my measures was producing incorrect results, as shown below.

I suspected that the issue might lie in the section shown below.

So, I tested it and expected to see 1.37 million in every row of the table visualization, including the Total row. However, that wasn’t the case.

I couldn't immediately pinpoint where things went wrong in my [test measure: ] (though I might have figured it out with a bit more time... 🤔). That was when I decided to click the "Run in DAX Query View" button in the Performance Analyzer pane.

In the DAX Query View shown in the image below, I could see the components that make up the table visualization. And, it immediately became clear that there were two additional columns involved, which I had forgotten to include when writing my [Sales ratio by YearMonth:] DAX measure.

As shown above:

- The dim_product[Brand] column was filtered to display only Contoso.

- The dim_date[YearMonthNumber] column was involved, even though I hadn’t included it anywhere in the visualization or on the page. This column is used to configure the sort order for the dim_date[YearMonth] column.

The dim_product[Brand] and dim_date[YearMonthNumber] columns needed to be included in the DAX measure. Once I updated the measure to incorporate these columns, it displayed the expected numbers as requested by the end users.

To summarize, my experience highlights one of key benefits of using the DAX Query View feature. At the starting period of using DAX Query View, leveraging this tool allowed me to quickly identify and resolve issues in my DAX measures, showcasing its effectiveness in streamlining troubleshooting and improving report accuracy.

Starting with DAX Query View as a foundational tool, as illustrated by my experience, can simplify getting acquainted with its capabilities.

As you become more comfortable using it in straightforward scenarios, and later in more complex situations, you’ll likely incorporate it more frequently across various use cases. Ultimately, this approach will help you master this powerful feature and enhance your Power BI expertise.

Start from a simple case, like me. 😁

I hope this helps readers have more fun with the DAX Query View feature!