Press "Enter" to skip to content

Category: Microsoft Fabric

Implementing IoT-Style Data in Microsoft Fabric

Published 2026-06-24 by Kevin Feasel

Hristo Hristov takes us through a walkthrough:

Hardware sensors or diverse types of equipment can generate IoT data at a high frequency, e.g., every second. Additionally, IoT data can be messy, semi-structured or just have huge volume and many disparate sources. How to ingest and model IoT data in Microsoft Fabric using the medallion lakehouse architecture?

As I was reading through this, the thing that kept coming to my mind is, if we’re really working with device data at a fairly high periodic frequency (e.g., once a minute or more often), this is probably a job for the Eventhouse and KQL. Though if your devices either don’t collect push information more frequently than, say, hourly, this approach is probably fine.

Comments closed

Major Announcements from Microsoft Build 2026

Published 2026-06-19 by Kevin Feasel

James Serra puts together a list:

Once again there were a number of Microsoft Build announcements related to data and AI, and some were very impressive. Below are my favorites. I am prioritizing the data announcements first, because that is where my brain naturally goes (and because AI without good data is just a very confident intern with access to a keyboard).

The biggest announcements across Microsoft Fabric and databases can be found in the Microsoft Build 2026: Building agentic apps with Microsoft Fabric and Microsoft Databases blog post.

This looks like another year of Fabric + AI as the (almost) entire data platform focus at Build.

Comments closed

Fabric Data Agents and Power BI Row-Level Security

Published 2026-06-19 by Kevin Feasel

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.

Comments closed

Variable Libraries in Microsoft Fabric

Published 2026-06-18 by Kevin Feasel

Nikola Ilic digs into a feature:

I hear you, I hear you: Nikola, that’s what deployment rules in Fabric Deployment Pipelines are for, isn’t it? Well, partly. But there’s a Fabric item built specifically to put an end to this whole genre of pain, and it’s the variable library. This article is the long version: what it is, how it’s wired together under the hood, who can actually consume it, when you should reach for it, when you absolutely shouldn’t, how it compares to the other parameterization features in Fabric, and a real telco demo to make it all concrete.

Click through for a deep dive into how it works.

Comments closed

Moving Fabric Notebooks between Workspaces

Published 2026-06-17 by Kevin Feasel

Gilbert Quevauvilliers takes advantage of source control:

With the new Lakehouse Auto-Binding capability in Notebook Git integration, Fabric can now intelligently preserve and resolve the binding between your notebooks and their attached Lakehouses as you move them across workspaces. This makes true multi-environment development and CI/CD workflows in Fabric significantly smoother and more reliable.

I am going to show you how to do this in the blog post below.

That is pretty nice, and Gilbert has a demo of the process, showing that it’s not particularly onerous

Comments closed

The Benfit of Disabling V-Order in Fabric Dataflows Gen2

Published 2026-06-15 by Kevin Feasel

Chris Webb covers a specific use case:

Quite a few new Dataflows Gen2 features were released recently without much fanfare, but that doesn’t mean they aren’t important. I will take a look at them all in my next few posts; in this first post I’ll look at the ability to disable V-Order on staged data.

As the (very detailed) documentation for this new feature describes, V-Order is a write-time optimisation for the parquet files that underpin the Delta tables that OneLake uses to store data. It slows down writing data to the tables but means that reading data from them, for example in Power BI Direct Lake mode, is much faster. 

Click through to see how disabling V-Order can make certain staging loads faster.

Comments closed

Identity Columns in Fabric Runtime 2.0

Published 2026-06-11 by Kevin Feasel

Jon Lunn is happy:

Fabric Runtime 2.0 is in public preview, and there is one small change for this that makes my life as a data engineer a little bit easier. Identity columns. I miss the good old T-SQL Identity column “Id INT IDENTITY(1,1)”, now we have something like it in Spark/Delta.

So with the the old spark/delta table runtime, you couldn’t have an default, automatically increasing column. But now we have these updates.

Click through to see how it works.

Comments closed

The Limits of Parallelism with Fabric Dataflows Gen2

Published 2026-06-08 by Kevin Feasel

Chris Webb notes that parallelism does not mean “free performance improvements”:

To finish off my series of posts on concurrent evaluation in Fabric Dataflows Gen2 (see part 1 and part 2) I decided to do some more realistic tests to see how much parallelism I could get. To do this I uploaded 244 identical Excel files containing almost 542000 rows of data each to a SharePoint document library. Excel files are probably the worst-performing file format for dataflows (see here for some tests that show this), while SharePoint is probably the worst-performing place to store data for a dataflow and also has a reputation for throttling applications that make too many requests.

Click through for Chris’s test results.

Comments closed

Accessing Data between Private Link and Public Fabric Workspaces

Published 2026-06-05 by Kevin Feasel

Gilbert Quevauvilliers uses the private endpoint:

In this blog post I show how it is possible to access data between a Private Link Workspace, where I want to read the data from my Public Workspace.

An example of this is where I wanted to use a DirectLake Semantic Model sitting in my Public Workspace where the data is from data in my Private Link Workspace.

Click through to see how it works.

Comments closed