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Category: Microsoft Fabric

Lessons Learned from Replicating BigQuery to Microsoft Fabric

Published 2025-10-06 by Kevin Feasel

Teo Lachev shares some knowledge:

A recent engagement required replicating some DW tables from Google BigQuery to a Fabric Lakehouse. We considered the Fabric mirroring feature (back then in private preview, now publicly available) and learned some lessons along the way:

1. 400 Error during replication configuration – Caused by attempting to use a read-only GBQ dataset that is linked to another GBQ dataset but the link was broken.

Read on for additional tips, including a major one around permissions.

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Performance of User-Defined Functions in Fabric Warehouses

Published 2025-10-03 by Kevin Feasel

Jared Westover shares some findings:

In Part One, we saw that simple scalar user-defined functions (UDFs) perform as well as inline code in a Fabric warehouse. But with a more complex UDF, does performance change? If it drops, is the code-reuse convenience worth the price?

I’m surprised that the performance profile was so good. I had assumed it would perform like T-SQL user-defined functions—namely, worse in general.

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Tracking Memory Consumption in Fabric SQL Database

Published 2025-10-02 by Kevin Feasel

Lance Wright tracks memory utilization:

SQL Database in Fabric continues its commitment to providing you with robust tools for database management, performance monitoring, and optimization. Earlier this year, we released a performance dashboard to help you monitor and improve the performance of your SQL Database in Fabric. We’ve improved upon those performance monitoring capabilities with the ability to track memory consumption. This new capability delivers real-time, actionable data regarding the memory utilization of all database queries to help you make more informed decisions and manage SQL Database resources more efficiently.

Read on to see what you can do with this.

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Microsoft Fabric Copy Job Updates

Published 2025-10-01 by Kevin Feasel

Ye Xu has an update:

Copy job is the go-to solution in Microsoft Fabric Data Factory for simplified data movement. With native support for multiple delivery styles, including bulk copy, incremental copy, and change data capture (CDC) replication, Copy job offers the flexibility to handle a wide range of scenarios—all through an intuitive, easy-to-use experience.

This update introduces several enhancements, including connection parameterization, expanded CDC capabilities, new connectors, and a streamlined Copy Assistant powered by Copy job.

Read on to see what’s new. Some of the items in this list are preview features, and it looks like others are currently GA.

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Linking Fabric Warehouse SQL Query Results to the Capacity Metrics App

Published 2025-09-30 by Kevin Feasel

Chris Webb follows up on a previous post:

Following on from my post two weeks ago about how to get the details of Power BI operations seen in the Capacity Metrics App using the OperationId column on the Timepoint Detail page, I thought it was important to point out that you can do the same thing with TSQL queries against a Fabric Warehouse/SQL Endpoint and with Spark jobs. These two areas of Fabric are outside my area of expertise so please excuse any mistakes or simplifications, but I know a lot of you are Fabric capacity admins so I hope you’ll find this useful.

Read on to learn more.

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Fabric Mirroring for Azure SQL MI Now GA

Published 2025-09-30 by Kevin Feasel

Ajay Jagannathan announces a feature has gone to general availability:

Mirroring in Fabric is a powerful feature that allows you to replicate data from various data sources such as your Azure SQL Managed Instance to Fabric’s OneLake. This ensures that your data is always up-to-date and readily available for advanced analytics, AI, and data science without the need for complex ETL processes.

Jokes about Azure SQL Managed Instance aside, it’s good that these features are becoming generally available.

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Content Discovery in Microsoft Fabric

Published 2025-09-30 by Kevin Feasel

Jon Vöge wants to find data:

So you built a nice Data Platform on Microsoft Fabric. Users are happily using a few Models and Reports, but you face two problems:

  1. Users are not aware of all the other awesome models, reports and even lakehouses that they already have access to, which they should be using.
  2. Users also don’t know anything about the models, report and lakehouses that they don’t have access to, but which could also be useful for them, if they requested access.

For my take on how best to solve this natively in Fabric, read on below.

Read on to see how you can enable content discovery.

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Viewing Security Settings in OneLake Catalog

Published 2025-09-26 by Kevin Feasel

Aaron Merrill announces a new preview feature:

Introducing the Secure tab in the OneLake catalog—your central place to understand and manage access across Fabric items. From a single view, you can workspace roles with the View users experience and inspect or modify role OneLake security roles with View security roles. The Secure tab brings a streamlined view for governance teams and workspace owners to quickly validate permissions and tighten least‑privilege access.

Click through to see how it looks.

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Announcements from FabCon Vienna

Published 2025-09-25 by Kevin Feasel

James Serra has a round-up:

A bunch of new features for Microsoft Fabric were announced at the Microsoft Fabric Community Conference (FabCon Vienna) recently. Here are all the new features that I found most interesting, with some released now and others coming soon:

Click through for approximately two dozen more announcements.

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Comparing Spark Application Performance in Microsoft Fabric

Published 2025-09-24 by Kevin Feasel

Jenny Jiang announces a new capability:

The Spark Applications Comparison feature is now in preview in Microsoft Fabric. This new capability empowers developers and data engineers to analyze, debug, and optimize Spark performance across multiple application runs—whether you’re tracking changes from code updates or data variations to improve performance.

The image in the blog post is pretty small and hard to read, but I do wonder if (or how well) it will capture cases where you’re twiddling your thumbs to get a machine so that you can execute your code. This seems to be a big problem sometimes.

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