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Category: Microsoft Fabric

Native Power BI Write-Back in Microsoft Fabric

Published 2025-06-04 by Kevin Feasel

Jon Vöge comes full-circle:

Three years ago, write-back to Power BI was my gateway into the Power BI community.

Power Apps embedded into Power BI, enabling write-back to Sharepoint, Azure SQL and Fabric, and sharing those solutions with the community, have always been some of the most fun I’ve had with “work”.

However.

While Power Apps are relatively easy to build, the solution architecture quickly becomes complex. Especially when you consider governance, CI/CD and licensing, all of which balloons in size when you are forced to integrate with a new platform (Dataverse/Power Platform) to solve a seemingly small issue in a Power BI report.

Click through to see the new way to do this. It’s been a point of frustration for me that, for so long, it has been such a challenge to allow a user to annotate or augment data in Power BI.

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Automated Table Statistics on Delta Tables in Microsoft Fabric

Published 2025-05-30 by Kevin Feasel

Santhosh Kumar Ravindran makes an announcement:

We’re thrilled to introduce Automated Table Statistics in Microsoft Fabric Data Engineering — a major upgrade that helps you get blazing-fast query performance with zero manual effort.

Whether you’re running complex joins, large aggregations, or heavy filtering workloads, Fabric’s new automated statistics will help Spark make smarter decisions, saving you time, compute, and money.

Click through to see what’s included, as well as the limitations associated with this. You can still create manual statistics if you’d like, so on the whole, I approve.

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Mirroring in Microsoft Fabric

Published 2025-05-28 by Kevin Feasel

Swetha Mannepalli explains how mirroring works in Microsoft Fabric:

Data is complex. It’s often scattered across multiple systems, stored in various formats, locked in silos and changing all the time — making it difficult to harness its full potential. Bringing this data together to power AI and BI workloads typically requires time-consuming ETL processes, custom pipelines, and deep technical expertise. There’s no simple way to get started…until now. 

Click through for more details. And I get the complaint that the term “mirroring” has a different meaning in SQL Server, and that Fabric mirroring from a SQL Server instance doesn’t actually use the mirroring technology that has been deprecated since 2012 but still remains in the product because reasons. But in fairness, there are only so many synonyms people can use. Which means, three years from now, marketing will rename the feature to “replication.”

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Common Data Transformations in Microsoft Fabric

Published 2025-05-28 by Kevin Feasel

Nikola Ilic takes us through several data transformations:

In the lakehouse, for example, you can transform the data by using PySpark, but also Spark SQL, which is VERY similar to Microsoft’s dialect of SQL, called Transact-SQL (or T-SQL, abbreviated). In the warehouse, you can apply transformations using T-SQL, but Python is also an option by leveraging a special pyodbc library. Finally, in the KQL database, you can run both KQL and T-SQL statements. As you may rightly assume, the lines are blurred, and sometimes the path is not 100% clear.

Therefore, in this article, I’ll explore five common data transformations and how to perform each one using three Fabric languages: PySpark, T-SQL, and KQL.

Click through for those transformations, such as extracting date parts, fixing casing, and pivoting data.

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Trying out Microsoft Fabric Data Agents

Published 2025-05-27 by Kevin Feasel

Wolfgang Strasser gives a generative AI solution built into Microsoft Fabric a try:

Today, I wanted to give the new Fabric Data Agents a try. According to the documentation, a Fabric Data Agent is defined as follows:

Data agent in Microsoft Fabric is a new Microsoft Fabric feature that allows you to build your own conversational Q&A systems using generative AI. A Fabric data agent makes data insights more accessible and actionable for everyone in your organization. With a Fabric data agent, your team can have conversations, with plain English-language questions, about the data that your organization stored in Fabric OneLake and then receive relevant answers. This way, even people without technical expertise in AI or a deep understanding of the data structure can receive precise and context-rich answers.

Let’s give it a try and build our first Data Agent.

Click through for the pre-requisites, the setup process, and how everything looked for Wolfgang.

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Loading JSON into a Microsoft Fabric Eventhouse

Published 2025-05-23 by Kevin Feasel

Christopher Schmidt loads some data:

In the era of big data, efficiently parsing and analyzing JSON data is critical for gaining actionable insights. Leveraging Kusto, a powerful query engine developed by Microsoft, enhances the efficiency of handling JSON data, making it simpler and faster to derive meaningful patterns and trends. Perhaps more importantly, Kusto’s ability to easily parse simple or nested JSON makes it easier then ever to extract meaningful insights from this data. The purpose of this blog post is to walk through ways that JSON data can be loaded into Eventhouse in Microsoft Fabric, where you can then leverage Kusto’s powerful capabilities for this. I’ve tried this a few different ways, and the below approach is the fastest, most efficient low-code way to ingest the data into the Eventhouse. As JSON inherently supports different schemas in a single file, the expectation here is that we have a json file with varying schemas within a single file, and we would like to load this into our Eventhouse for efficient parsing with KQL.

Read on for the process.

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Materialized Lake Views in Microsoft Fabric

Published 2025-05-22 by Kevin Feasel

Balaji Sankaran has a new announcement:

We are excited to announce Materialized Lake views (MLV) in Microsoft Fabric. Coming soon in preview, MLV is a new feature that allows you to build declarative data pipelines using SQL, complete with built-in data quality rules and automatic monitoring of data transformations. In essence, an MLV is a persisted, continuously updated view of your data that simplifies how you implement multi-stage Lakehouse processing, commonly referred to as medallion architecture.

Read on to see how it works and some of its capabilities.

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Cosmos DB in Microsoft Fabric

Published 2025-05-21 by Kevin Feasel

Anitha Adusumilli has an announcement:

Building on the momentum from the launch of SQL database in Fabric, we are expanding databases workload in Fabric with this new addition. You can now store semi-structured NoSQL data in Cosmos DB in Fabric, alongside your relational data in SQL databases, enabling a unified data platform for your applications. This further positions Fabric as a complete data platform to handle all your organizational needs, from operational to analytics and BI.

Good news: Microsoft is helping us find the exact limit for the credit cards we’re using to pay for Fabric.

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