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Power BI Semantic Model Memory Errors, Part 5: The “Maximum Allowable Memory Allocation” Error

This is a very late addition to the series of posts I wrote back in 2024 and which started here on Power BI memory errors. It’s about a very rare error that is hard to deal with and often temporary but since people do run into it from time to time I decided to write … Continue reading Power BI Semantic Model Memory Errors, Part 5: The “Maximum Allowable Memory Allocation” Error

Connecting Power BI Semantic Models To Data Sources Automatically With Binding Hints

Did you know that you can configure your Power BI semantic model so that it automatically binds to a data source connection when you publish? To illustrate how to do this, I created an Import mode Power BI semantic model in Power BI Desktop connected to the Products table in the ContosoSales sample database in … Continue reading Connecting Power BI Semantic Models To Data Sources Automatically With Binding Hints

Generating Sample Data In Fabric Dataflows With FabricAI.Prompt()

Back in December the FabricAI.Prompt() M function was released in Fabric Dataflows Gen2. Most of the people writing about it at that time, as in this great post by my colleague Sandeep Pawar, focused on calling this function for each row in a table – something that the UI in the editor makes easy. However … Continue reading Generating Sample Data In Fabric Dataflows With FabricAI.Prompt()

Power BI And Support For Third Party Semantic Models

I’ve been working with Microsoft BI tools for 28 years now and for all that time Microsoft has been consistent in its belief that semantic models are a good thing. Fashions have changed and at different times the wider BI industry has agreed and disagreed with this belief; right now, semantic models are cool again … Continue reading Power BI And Support For Third Party Semantic Models

Role-Playing Dimensions In Fabric Direct Lake Semantic Models Revisited

Back in September 2024 I wrote a blog post on how to create multiple copies of the same dimension in a Direct Lake semantic model without creating copies of the underlying Delta table. Not long after that I started getting comments that people who tried following my instructions were getting errors, and while some bugs … Continue reading Role-Playing Dimensions In Fabric Direct Lake Semantic Models Revisited

When Can Partitioned Compute Help Improve Fabric Dataflow Performance?

Partitioned Compute is a new feature in Fabric Dataflows that allows you to run certain operations inside a Dataflow query in parallel and therefore improve performance. While UI support is limited at the moment it can be used in any Dataflow by adding a single line of fairly simple M code and checking a box … Continue reading When Can Partitioned Compute Help Improve Fabric Dataflow Performance?

A Closer Look At Preview-Only Steps In Fabric Dataflows

I have been spending a lot of time recently investigating the new performance-related features that have rolled out in Fabric Dataflows over the last few months, so expect a lot of blog posts on this subject in the near future. Probably my favourite of these features is Preview-Only steps: they make such a big difference … Continue reading A Closer Look At Preview-Only Steps In Fabric Dataflows