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Day: May 28, 2025

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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Retrieving Child Records with APPLY

Published 2025-05-28 by Kevin Feasel

I have a new video:

In this video, I show how we can use the APPLY operator to find records associated with a “parent” table. We look at getting the latest record, as well as any arbitrary number of records. We also spend time digging into under what circumstances the APPLY operator out-performs other common options.

During the outro segment, I dig into under what circumstances APPLY is the best tool for the job, so stick around for the end.

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Using Filtered Indexes in SQL Server

Published 2025-05-28 by Kevin Feasel

Stephen Planck explains the value (and limitations) of filtered indexes:

When a table holds millions of rows yet most queries touch only a small, well-defined subset, a traditional non-clustered index feels like using a searchlight to find something sitting under a desk lamp: the index still stores an entry for every row even though the workload rarely needs most of them. SQL Server’s answer is the filtered index—introduced in SQL Server 2008 and still under-used today—allowing you to index just the rows that match a predicate you supply in a WHERE clause.

I always thought I would get more value out of filtered indexes. Instead, they’re very useful for specific circumstances, but not the all-purpose performance dynamos you’d want them to be, particularly because of the limitations.

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Salesforce to Purchase Informatica for $8 Billion

Published 2025-05-28 by Kevin Feasel

Alex Woodie prints the news:

It’s been 13 months since Salesforce and Informatica called off their first attempt at an acquisition. But the second time appears to be the charm, as Informatica today announced that Salesforce will buy it for $8 billion.

Informatica was founded in 1993 ago to serve the burgeoning market for data integration tools, in particular the need for extract, transformation, and load (ETL) tools for early data warehouses. Companies at the time needed to pull transactional data out of mainframes, midrange, and Unix systems, transform the data into a suitable format, and then load it into their analytical database.

It will be interesting to see what comes out of this.

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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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Building a Rubik’s Cube in Power Apps

Published 2025-05-28 by Kevin Feasel

Jon Vöge builds an app:

This time however, the Power Hour led me to come fully clean to my colleagues, by attempting to build a Rubik’s Cube emulator within a Canvas Power App.

For this week’s blog, I’ll take you for a brief tour of its inner workings, and share the code with you for yourself to play around with.

Click through for the code and explanation.

In the meantime, I’ll share a family secret on how we solve Rubik’s cubes. We remove the wrong stickers and swap them with the correct ones. Boom, problem solved. Also, this is getting the most coveted category I have to offer on Curated SQL, so good on Jon.

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