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Category: Power BI

Monitoring the Refresh of a Semantic Model

Reitse Eskens checks the logs:

As you’ve probably heard and read before, monitoring your Fabric environment as a whole is quite important. It really does help to know what’s going on.
Now, one thing I’ve learned over all these years is that report users do quite like their data to be as fresh and up to date as possible. And, when the data seems stale, they tend to ask questions.

Read on for some notes covering how to refresh a semantic model, when you might want to, how to automate it, and how to monitor the refresh process.

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Tabular Editor CLI 0.6.0 Release

Ruben Van de Voorde announces a new update:

Since announcing the Tabular Editor CLI, we’ve been hard at work polishing the CLI and bashing the bugs we found, thanks to your help. We deeply appreciate all the input we received so far through GitHub, talking to you at events, comments on these blogs, and all other channels you engage with us (leave yours at the bottom of this page). Keep it coming!

We’re now at a point where we feel ready to share the updated version with you: version 0.6.0.

This is still in a limited public preview, so it’s free until the end of September. After that point, it becomes a paid product.

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Power BI: Database Was Evicted to Balance the CPU Load

Chris Webb diagnoses a case of passive voice:

A few months ago I wrote about a rare error – the “Maximum allowable memory allocation” error – that may occur when the physical machine, or node, that a semantic model is running on in the Power BI Service comes under memory pressure. Recently, someone I was working with who was doing some load testing showed me a related error:

The operation was canceled and the database was evicted to balance the CPU load on the node. Please try again later.

Read on to see what causes this.

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The Basics of Query Folding with Power BI

Andy Brownsword explains one performance improvement technique for Power BI data transformations:

As a database developer, when I started using Power BI, I was concerned about it retrieving reams of data only to perform transformations downstream. The Power Query editor misleads us into thinking the retrieval and transformations are applied sequentially.

Thanks to Query Folding, that’s not usually the case. And that gives us more power to extract performance from the database.

This only works in situations where there’s something downstream to perform that processing, like a relational database. And one of the areas where you can affect performance, either positively or negatively, is in organizing operations such that you have a stretch of foldable operations. That way, all of it can run as one operation in the database.

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Reviewing the Power BI Date Picker

Teo Lachev takes a look at a new preview:

The June release of Power BI Desktop includes a preview of a new Power BI slicer configuration – Date Picker. It’s meant to solve two issues with report design.

Read on to see what those two issues are and how this new date picker can resolve them. It’s still in preview, so you’d have to change the settings in Power BI Desktop. And I imagine it won’t be available in Power BI Report Server because those people (including me) can’t be trusted to have nice things.

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Clustering Text via Embeddings and HDBSCAN

Ivan Palomaras Carrascosa groups things together:

In this article, you will learn how to build a text clustering pipeline by combining large language model embeddings with HDBSCAN, a density-based clustering algorithm, to automatically discover topics in unlabeled text data.

Topics we will cover include:

  • How to generate text embeddings for raw documents using a pre-trained sentence-transformers model.
  • How to reduce the dimensionality of those embeddings with UMAP to prepare them for clustering.
  • How to apply HDBSCAN to automatically discover topic clusters and visualize the results.

This is a pretty neat trick that takes advantage of the embedding model’s ability to convert raw text into hundreds (or thousands) of floating point numbers while maintaining enough of the context to differentiate ideas. A lot of it is the original word2vec concepts but scaled up.

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Optimizing Power BI Data Agents

Paul Turley shares some advice:

Amid the AI frenzy, there is a lot of conversation about how business users will use agentic chat to answer business questions rather than interactive, dashboard-style reports. Is there truly a shift in the industry, and is agentic analytics going to change the way most business users consume data?

Just how viable is the whole “chat with your data” option, and is it really a replacement for conventional reporting? I recently heard a VP-level leader at a large consulting firm say something to the effect of “we need to stop investing in dashboard-building skills and focus on creating AI-driven data analysis solutions for our consulting customers.” I’m paraphrasing from memory, but that was the sentiment. Are all business leaders across the industry giving up their dashboards, interactive visual reports and scorecards in exchange for AI chat? No. Of course they aren’t — but conversational analysis is a new way to consume business data.

Much of the advice is very similar to what you’d get for standard dashboard creation, and it makes sense. The clearer your data model is and the tighter your semantic model is, the easier it is for processes to use that semantic model. But Paul also covers some things specific to Data Agents as well.

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User-Defined Functions and Power BI Testing

John Kerski is excited:

User Defined Functions (UDFs) are, in my opinion, the biggest update to Power BI Desktop since PBIP.

That may sound dramatic, but if you care about DataOps, semantic model quality, and reusable development patterns, UDFs fundamentally change what is possible with DAX.

Reuse is one of the core principles of DataOps. For years we have been able to build reusable patterns in Power Query, PowerShell, Python, YAML, and infrastructure automation. But DAX was always missing a key capability: reusable logic that could live inside the semantic model itself.

Until now.

Read on to learn more, as well as to get a link to John’s PQL.Assert DAX unit testing library.

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Fabric Data Agents and Power BI Row-Level Security

Jens Vestergaard digs into a security challenge:

In the last post I walked through auditing a semantic model before connecting it to an AI tool like Fabric Data Agent. Descriptions, naming, explicit measures, star schema: the things that decide whether a Fabric data agent generates an accurate query or a confident wrong one. I left one thing out on purpose, because it deserved its own post and because I got it wrong the first time I thought about it.

Security.

Click through for a few subtle security issues that automated agents can expose. It turns out to be a lot more challenging than you may first expect, just as Jens discovered.

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PBIR Files and Second-Class Report Server Citizens

Ronald Kraijesteijn tells a tale of woe with Power BI Report Server:

The setup is an on-prem Power BI Report Server, fully patched, running the May 2026 release (1.26.9637.31070, build15.0.1121.109). I had a report I needed to publish, but first I had to swap a whole batch of connection strings. Doing that by hand in Desktop is miserable, so I took a shortcut that turned out to be the root of all my pain. More on that below.

The error was a generic mess and the cause was getting too high for your station and actually expecting something from Power BI Report Server.

I say this as a fellow long-time Power BI Report Server sufferer.

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