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Category: Microsoft Fabric

Accessing Microsoft Graph API via Fabric Data Factory

Published 2025-12-22 by Kevin Feasel

Paul Hernandez makes a connection:

This article is an updated version of my 2022 post on using Synapse pipelines to retrieve security groups and their members through the Microsoft Graph API. Some customers recently asked for a Microsoft Fabric–based approach, and I also noticed that many developers are still defaulting to Python clients to interact with Graph. While Python works perfectly fine, this walkthrough demonstrates how you can accomplish the same using a parameterized Copy Data activity inside a Fabric Data Factory pipeline.

Read on to see how.

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Connecting Microsoft Fabric to Azure DevOps via Service Principal

Published 2025-12-22 by Kevin Feasel

Yaron Pri Gal doesn’t need no steenkin’ passwords:

Following Azure DevOps Service Principal & Cross Tenant Support (Generally Available) announcement for service principal and cross-tenant support – Microsoft Fabric Git Integration with Azure DevOps (ADO), this blog post serves as a guide to connecting Fabric workspaces to Azure DevOps repositories using service principal.

Fabric Git Integration is the foundation for organizations implementing fully automated CI/CD pipelines, enabling seamless movement of assets across Development, Test, and Production environments.

Currently, Fabric Git Integration supports two major Git providers: Azure DevOps and GitHub. This blog post addresses the new service principal capability for Azure DevOps.

Click through for more info and a link to Microsoft Learn that contains the instructions.

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DATE_BUCKET() Now GA in Fabric Data Warehouse

Published 2025-12-19 by Kevin Feasel

Jovan Popovic makes an announcement:

We have introduced a new DATE_BUCKET() function in Fabric Data Warehouse SQL language that makes reporting and analytics even easier.

In this blog post, you’ll discover how it simplifies time-based reporting and makes grouping dates effortless.

My experience is that DATE_BUCKET() takes a bit of effort getting used to, as it is not an intuitive function. That said, it can be really powerful for dealing with time series data. It is also available in SQL Server, as of SQL Server 2022.

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Microsoft Fabric Lakehouse Schemas now GA

Published 2025-12-12 by Kevin Feasel

Ted Vilutis makes an announcement:

Schema lakehouses are now Generally Available. By using schemas in lakehouses, users can arrange their tables more efficiently and make it easier to find data. When creating new lakehouses, schema-enabled lakehouses will now be the default choice. However, users still have the option to create lakehouses without a schema if they prefer.

Read on to see how they work, as well as a bug(?) around pinned lakehouses.

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The Good and Bad of Microsoft Fabric Variable Libraries

Published 2025-12-11 by Kevin Feasel

Jon Lunn digs in:

One of the big issues with Deployment Pipelines in Fabric, or as I call them Disappointment Pipelines, has been the lack of being able to parameterise connections. You do have deployment rules in the pipelines, but they are limited in functionality and don’t support pipeline parameters (boo!), so if you need to push and change items between workspaces in a typical Development, Test and Production workspaces scenario, you had to configure the connections manually, which is a massive pain. Variable Libraries should make the experience of deployment a lot easier.

Read on to see how they work, as well as some of the existing pain points around them.

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OneLake Security ReadWrite Access

Published 2025-12-10 by Kevin Feasel

Kiefer Sheldon practices least privilege:

Many data teams face the same challenge: balancing the need for open collaboration with the responsibility of protecting sensitive information. As organizations grow, data often lives across multiple domains—some containing critical or confidential datasets—while partner teams may only need access to a subset of that information.

Until recently, maintaining this balance often meant trade-offs. Teams had to choose between a fragmented storage setup or overexposing data just to keep their workflows running smoothly.

Read on to see how this works.

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Tracking Historical Changes in Microsoft Fabric

Published 2025-12-10 by Kevin Feasel

Kenneth Omorodion generates a snapshot:

In most modern businesses, by default, operational systems are managed in a way that only shows the current view of things in their data like active tickets, open incidents, active complaints, and daily sales. While this is a great way to monitor day-to-day reporting, it however tends to hide an important narrative for the business. For instance, it does not show how things have changed over time. It also does not tell a story on how previous periods compared to the current, in terms of the actual state of the data.

So, without a snapshot view implementation, there is no way to accurately view when data changes, and this may lead to a loss of the previous view forever with no way to retrieve that snapshot.

Click through to see how.

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Accessing Excel Files from OneDrive via Power BI

Published 2025-12-09 by Kevin Feasel

Kristyna Ferris is happy:

I can’t believe it’s finally here! A way to have Excel live in OneDrive and access it from Power BI nearly live! We can officially short cut files to our OneLake from both SharePoint and OneDrive! I am super excited about this feature, and I hope you are too. This feature plus User Data Functions allows us to not only have data from Excel in our reports but keep it as fresh as needed. Imagine having budget allocations that you want to adjust right before or during a meeting. Now you can! You can edit a file in Excel and hit one button to see the new numbers in your report. In the past, we relied on 3rd party services or Power Apps licensing to accomplish this sort of experience. Now we can just use Excel, an old data friend.

Kristyna does note that this is in preview, so take it with that caveat in mind and read on to see how it all works.

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Exposing Materialized View in Microsoft Fabric Lakehouses

Published 2025-12-04 by Kevin Feasel

Ed Lima makes some data available to other tools:

In today’s data-driven world, the ability to quickly expose data through modern APIs is crucial. Microsoft Fabric’s API for GraphQL combined with Materialized Lake Views offers a powerful solution that bridges the gap between your Fabric LakeHouse data and application developers who need fast, flexible access to your data.

In this guide, we’ll walk you through how to create a materialized view in a Lakehouse and expose it through a GraphQL API—all within the Microsoft Fabric ecosystem. This approach gives you the best of both worlds: the performance optimization of materialized views and the developer-friendly querying capabilities of GraphQL.

I’d say one interesting reason for why you might want to do this is to feed data to products like Teams, Power Automate, or Copilot Studio. In those cases, having the data be accessible via GraphQL makes it easier than working with finicky connectors that may or may not exist.

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