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Category: Power BI

Source Control for Power BI Semantic Models

Published 2026-09-16 by Kevin Feasel

Ruben Van de Voorde provides an overview of how source control works with Power BI reports:

Some years ago, our founder Daniel wrote a five-part blog series titled “You’re deploying it wrong!”, which was essentially him shouting that he stole fire from the software gods and handing out torches. He was talking about how software engineers had this wonderful thing called CI/CD, and how it was finally within reach of data people working with Analysis Services. Jokes aside, the core ideas have not changed, but the landscape and toolchain have, so the series deserves an update, and this is it.

Power BI has come a long way in this regard. Unless you’re using Power BI Report Server, in which case, the joke’s on you.

I’m going to return to my Power BI Report Server corner now and not have any of the nice things.

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Tracking Changes in Power BI Semantic Models

Published 2026-09-15 by Kevin Feasel

Chris Webb wants to know what changed:

Here’s a situation I’ve found myself in many times. You’re called to help someone whose Power BI report is suddenly very slow. You ask whether any changes were made to the semantic model around the time performance got worse and the answer is no, absolutely not. You then spend anything from a few hours to a few days trying to fix the problem and when you find it, it turns out that someone did make a ‘minor’ change to the semantic model after all and this was the cause of it all. Wouldn’t it be good if you could see when things like measures were last changed? Well you can.

Click through to see how, as well as some challenges you might run into along the way.

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Scatter and Sampling in Power BI Core vs Deneb

Published 2026-09-08 by Kevin Feasel

Kerry Kolosko shows some comparisons:

In almost a decade of building Power BI reports, a common blind spot I still see from colleagues regards data point limits in core visuals — largely unnoticed until someone maps their data and finds entire regions are missing.

Compare the following lasagne plot created using a Power BI core visual scatterplot with one created using a Power BI custom visual (Deneb).

Click through for the difference. The more I see Deneb, the more impressed I am with it. I’ve seen people do some wild things with it while still working just fine in Power BI. There’s even compatibility with Power BI Report Server, if you can believe it.

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Azure Databricks and Power BI Storage Modes

Published 2026-09-08 by Kevin Feasel

Chris Webb makes a choice:

In case you haven’t already seen the blog post on the Power BI blog or the discussion on LinkedIn, we at Microsoft published a new white paper last week to help you decide which storage mode to use when you’re using Power BI to create semantic models and reports on data stored in Azure Databricks. You can find the announcement and the link to the paper here.

Click through for Chris’s thoughts and check out the whitepaper.

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Compiling Power BI Calculation Groups

Published 2026-09-03 by Kevin Feasel

Phil Seamark looks at an optimization:

Power BI now avoids compiling calculation items that a query has already filtered out. The time saved is before the first storage engine event. It does not make the scans themselves faster.

Will I benefit? If your query filters a calculation group down to a subset of its items, it may compile faster. A single filtered group can benefit, although often only by a little. The largest gains are in models where calculation groups reference one another, because the engine used to expand combinations the query never needed. If your query has no calculation groups, or uses every item in them, there is nothing to prune.

Click through to see what the hubbub is all about and if it might affect you.

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Referencing Assets in Power BI Reports via OneLake URLs

Published 2026-08-31 by Kevin Feasel

Chris Webb wants to load some images:

Several years ago I wrote a very popular blog post about how to store images for your reports inside your Power BI semantic model. It solved the problem of how you could use display images (for example of products) inside your reports without making those images available via a public URL or personal OneDrive Embed Codes. I was very proud of how efficient the M code to do this was but the code was complicated and storing images as text inside a semantic model makes refreshes a lot slower and increases the size of your semantic model in memory, so it’s not ideal. The good news is that, if you have enabled Fabric in your tenant, the August 2026 release of Power BI brings a much better way of solving this problem: you can now store your images (and indeed other files) inside OneLake and reference them from there. This means you can store your images in a secure location, alongside all of your other data, and make them available for use in Power BI. What’s more this doesn’t just work for images, it also works for other types of files such as GeoJSON files used by map visuals.

Click through to see how.

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Displaying Detail Rows Expression Results in Power BI

Published 2026-08-17 by Kevin Feasel

Chris Webb works around a limitation:

In last week’s post I mentioned that while Power BI reports (unlike Excel PivotTables) do not support the Detail Rows Expression feature, it is possible to partially work around this limitation by using the paginated report visual. In this post I’ll show you how I was able to do this and what is and isn’t possible.

Click through to see how. I’m unclear as to whether this also applies to Power BI Report Server, though my default expectation is “No, it does not apply, because nothing new ever applies for Power BI Report Server, because Power BI Report Server users don’t deserve nice things.” But that’s just because of years of experience in not having nice things with PBIRS, not any specific information.

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Drilling into Separate Fact Tables via Detail Rows in Power BI

Published 2026-08-10 by Kevin Feasel

Chris Webb crosses fact tables:

If you have a DirectQuery fact table in Power BI you can use user-defined aggregations to improve query performance; querying a smaller, summarised copy of your data in an Import mode aggregation table is always going to be faster than querying a large fact table containing all your detail data that is in DirectQuery mode. What’s more a composite model like this can have a much smaller footprint in memory than a model where all your tables are in Import or Direct Lake mode, which means you can use a smaller Fabric capacity SKU. However, in some cases you can take the same tables that you would use to create a composite model like this and solve the same problem slightly differently without using aggregations.

Click through for an example of this.

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The Performance Impact of Visual Calculations

Published 2026-07-29 by Kevin Feasel

Marco Russo and Alberto Ferrari dig into the nuance:

The goal of visual calculations is to simplify some reports and calculations, rather than to optimize performance. However, it is common sense that – in some scenarios – visual calculations can bring some benefit from the performance point of view.

The main idea is that a report may precompute some values and then, to further elaborate on them, it may use the content of the virtual table rather than recompute the values multiple times.

Read on to learn how you can adjudge what that visual calculation is doing for you in terms of performance relative to alternatives. But hey, if you’re stuck with Power BI Report Server, you don’t have to worry about visual calculations potentially slowing anything down. Mostly because you don’t get visual calculations.

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