A Fine Slice Of SQL Server
Koen Verbeeck speeds things up:
We are building a large warehouse in Microsoft Fabric using the warehouse. Our biggest fact tables have some performance issues when we are running our analytical queries, and it seems we cannot use indexes in the Fabric Warehouse. Is there some way to improve performance?
Click through to see how you can use clustering to improve the performance of warehousing queries, as well as some of the pre-requisites to make it work.
Leave a CommentWhen you provision a Microsoft Fabric trial, it spins up at F64 by default. That’s the equivalent of 64 Capacity Units — a solid chunk of compute. For most trial users, this is just the number they see and never think twice about.
But here’s what I just discovered: you can change it.
Click through to see how.
Leave a CommentNikola Ilic asks, what’s in a name?
My dear Microsoft Fabric friends – if you’ve ever opened a workspace and seen “Lakehouse”, “Lakehouse 1”, “lh_test_v2”, and “NewLakehouse_DELETE_ME” all sitting next to each other, this post is for you
Three weeks into a fresh Fabric tenant, things look great. Twelve weeks in, you’re staring at 47 workspaces, three of them called something like “Test – DO NOT USE”, and nobody on the team can remember which Lakehouse holds the actual production sales data.
I don’t know how Nikola has figured out my naming strategy so well. Click through for a systematic attempt to standardize naming for Fabric objects.
Leave a CommentJens 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.
Leave a CommentThis post covers using fab deploy in Azure DevOps for Microsoft Fabric deployments based on YAML pipelines. In addition, this post shows how you can perform initial tests locally and introduces some AI concepts. Plus, this post shares plenty of links and advice.
You can find an example to accompany this post in the ‘create-genworkspace-fabric-cli.yml‘ file my ADO-fabric-cicd-sample Git repository. I also added some AI elements within this Git repository as well. Including the Fabric CLI skills that were announced during FabCon.
Click through to learn more about fab deploy and how the process works.
Leave a CommentJens Vestergaard wants to know who moved his cheese:
Semantic models do not have version control. Not really. You can store
.pbipfiles in Git, and Tabular Editor gives you a.bimfile you can diff, but neither of those workflows answers the simplest question a team asks after an update cycle: what changed?I do not mean “which file was touched.” I mean: which measures were modified, which columns were added, which relationships were removed, and what exactly is different in the DAX expression that someone edited last Tuesday. That is the question I kept running into, and the one I built this notebook to answer.
Click through to learn how.
Leave a CommentKoen Verbeeck troubleshoots an issue:
A short blog post about an issue with Fabric Mirroring (with Azure SQL DB as the source) that I’ve managed to run into, twice. I’ve set up mirroring by creating a connection using a service principal and this principal has the proper permissions on the source database. Configuring the replication was without issues, and the replication status went from “starting” to “running”. However, no rows were being copied. The tables were all listed in the monitoring pane, but the counters of “rows replicated” remained at zero. There were no errors in the logs (in OneLake) and nothing suspicious was mentioned in the monitoring.
This was a rather pernicious issue. Based on Koen’s explanation, it sounds like there’s no way to know what the actual problem was.
Leave a CommentTzvia Gitlin Troyna shows off some new functionality:
As Microsoft Fabric continues to converge analytics experiences across workloads, one of the most important steps forward is reducing friction in how users move from raw data to insights. With the latest integrations, the Eventhouse Endpoint is now deeply embedded into the “Analyze data with” entry points across Lakehouse, Data Warehouse, and Eventhouse, bringing a consistent, discoverable, and powerful way to analyze data using SQL Endpoint and Notebooks, both new and existing.
Click through to see what this means. This is a preview feature, but it does help tell the story a bit better around Fabric being a coherent entity rather than a bunch of products slapped together.
Leave a CommentHarmeet Gill announces general availability of OneLake File Explorer:
Imagine this scenario: You’re a data engineer working with files on your local machine—CSV extracts, Excel files from the business, or intermediate outputs generated on your PC. Your goal is to run a Fabric pipeline, explore the data in a notebook, or train a model in Microsoft Fabric.
Traditionally, that means uploading files through a browser, writing scripts to push data into the lake, or coordinating with someone else who has access. It works—but it adds friction.
OneLake File Explorer removes that friction by bringing OneLake directly into Windows File Explorer.
It’s taken about 3 years to get to this point, but I’m glad to see it get past the preview hurdle.
Leave a CommentAlicia Li and Arindam Chatterjee share some updates:
Over the first quarter of 2026, Fabric Eventstreams shipped meaningful improvements across three themes that have repeatedly come up in feedback from our broad community of customers and partners: broader connectivity, richer real-time processing, and secure enterprise‑ready networking and operations.
This post highlights some of the most impactful new Eventstreams-related features and capabilities delivered between January and March 2026.
Click through to see what’s new. Some of this is GA, though a good amount is in preview.
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