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Category: DAX

DAX UDF Measures vs Calculation Groups for Time Intelligence

Published 2026-05-27 by Kevin Feasel

Bernat Agullo Rosello compares two capabilities:

Ever since DAX UDFs came out as public preview in September 2025, many DAX developers started wondering how they will compare with calculation groups since both have the centralization of code as one of their main selling points. As pointed out in a recent article by SQLBI they are indeed very different beasts, even though they can be used to achieve very similar outputs.

In short, a calculation group is a model-level object whose items swap one DAX expression for another at evaluation time. Once an item is in the filter context, it applies to every measure being evaluated. A DAX UDF is a smaller object: a named, reusable expression with parameters, callable from any measure but invisible to report users.

Read on to see when calculation groups still make sense and when DAX UDFs are the better choice.

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User-Aware Calculated Columns in Power BI

Published 2026-05-20 by Kevin Feasel

Marco Russo and Alberto Ferrari show off something new:

A calculated column is computed when the table is refreshed and stored in the model (in Import mode), just like any other column, so its value does not depend on the user who is connected. The introduction of user-aware calculated columns in Power BI changes this picture because we can define a calculated column that is evaluated at query time and depends on the user running the query. This behavior can be obtained by setting the Expression Context property of a calculated column to User Context.

Click through to see the benefit of this new functionality.

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Filtering DAX Measures through Slicers

Published 2026-05-05 by Kevin Feasel

Marco Russo and Alberto Ferrari provide a deeper answer:

A very common request by Power BI newbies is, “How can I use a slicer to filter a measure rather than a regular model column?” The most common answer to this question is, “You cannot filter a measure through a slicer”. The answer is entirely correct because there is no such thing as “filtering a measure”. However, elaborating on the why gives us a good way to explain not only what is wrong with the question, but also how to further reason about the requirements needed to obtain a working solution.

This blog post is an example of how challenging it can be to answer a beginner’s question, where the immediate answer is “No, you can’t do that” but the underlying problem is solvable.

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Unmaterialized Columns in Power BI

Published 2026-04-28 by Kevin Feasel

Teo Lachev has ideal columns:

Coming back from a long vacation, I’ve almost missed this interesting Power BI enhancement: Power BI unmaterialized calculated columns. Normally, I avoid the traditional DAX calculated columns for a variety of reasons, such as confusion about where business logic is applied, limited support across storage modes (for example, Direct Lake doesn’t support them), longer refresh times, etc. This not to say that calculated columns can’t be useful, such as in the case where you need to flatten a parent-child hierarchy. But unmaterialized calculated columns could open interesting scenarios that go beyond content translation to other languages mentioned by Microsoft in the April 2026 update.

Click through to learn what unmaterialized columns are and how they work.

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User-Context-Aware Calculated Columns in Power BI

Published 2026-04-22 by Kevin Feasel

Nikola Ilic digs into a new feature:

A few weeks ago, I was sitting in a session at FabCon Atlanta. It was an amazing session about Direct Lake semantic models and various optimization tips and tricks, delivered by true masters, Christian Wade and Phil Seamark (both from Microsoft). Among many fantastic topics, the one that immediately caught my attention was the new feature that Christian Wade introduced: User-context-aware calculated columns.

Although we all know that DAX calculated columns are the “last island” in what are considered recommended data modeling practices (“Roche’s Maxim”, etc.), this one still stood out for me as something that might be super useful in certain scenarios.

Read on to see how it works and scenarios in which it could be useful.

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Parameter Types in DAX User-Defined Functions

Published 2026-04-21 by Kevin Feasel

Marco Russo and Alberto Ferrari talk about type systems:

In a previous article, Introducing user-defined functions in DAX, we described the syntax for creating user-defined functions, including the two passing modes (VAL and EXPR) and the fundamental parameter types SCALAR and TABLE. In this article, we build on that foundation and focus on the complete type system, with particular attention to the reference types introduced in March 2026 that provide better documentation, stronger validation, and improved IntelliSense support.

Before diving into the new types, let us briefly recap the full picture of parameter types and passing modes available in DAX user-defined functions.

Click through for a classic deep dive from Marco and Alberto.

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Validating DAX against a Lakehouse via Semantic Link

Published 2026-04-17 by Kevin Feasel

Jens Vestergaard performs some checks:

A semantic model is a promise. It promises that the numbers in your reports match the data in your lakehouse. But after enough model changes, renamed columns, new relationships, and tweaked measures, that promise gets harder to verify. I wanted a way to check it programmatically.

This is my second submission to the Fabric Semantic Link Developer Experience Challenge. The first was a DAX unit test harness that compares measures against hardcoded expected values. That works well for known business rules, but it has a limitation: someone has to decide and maintain what the “right” answer is. For a model with hundreds of measures across dozens of filter contexts, that does not scale.

Click through to see what Jens did instead.

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Unit Testing DAX via Semantic Link

Published 2026-04-13 by Kevin Feasel

Jens Vestergaard writes a test:

Every BI developer has felt it. You change a measure, update a relationship, or rename a column in a semantic model, and then you spend the next hour clicking through report pages to check if something broke. Manual spot-checking is how most teams validate DAX today. It works until it does not.

I have been building and maintaining semantic models for years. The further I get into Fabric-based development, the more my models start to feel like production code. They power dashboards that drive decisions. They feed downstream pipelines. When something breaks, the blast radius is real. And yet, the testing story has always been: deploy, open the report, squint at the numbers.

That gap bothered me enough to do something about it.

Click through to see what Jens has done.

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Performing a GROUPBY in Excel

Published 2026-04-09 by Kevin Feasel

Ben Richardson explains a DAX function:

If you’ve ever built a summary table in Excel by writing five separate SUMIFS formulas – one for each region, product, or department – you’ll appreciate what GROUPBY does.

It collapses all of that into a single formula that updates automatically, sorts itself, and can even filter out rows you don’t care about.

Introduced to Microsoft 365 in late 2024, GROUPBY is one of the most practically useful additions Excel has had in years.

But it also comes with real limitations that most people gloss over.

Read on to learn more about the capability and one big catch.

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Highlighting Rows in DAX via Visual Calculations

Published 2026-04-07 by Kevin Feasel

Marco Russo and Alberto Ferrari point out a row:

When it comes to visuals, users may want to specific cells highlighted in order to spot important information quickly. While browsing the forums, we came across an interesting requirement that can easily be solved with a DAX measure: highlight an entire row based on the value in the last column of the visual only. In our example, we highlight Wide World Importers because it has the maximum value (71,904.98) in the last year (2026).

I’ve had a need for this several times in the past, so it’s nice to see you can do it via visual calculations.

So, let’s use this in Power BI Report Server. Oh, wait, you can’t. But if you’re not shackled to that train wreck, click through for a nice solution.

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