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Author: Kevin Feasel

Tag-Based Masking in Snowflake

Published 2025-10-01 by Kevin Feasel

Kevin Wilkie gets tagging:

If you’ve followed our site for a while, you would have seen in a previous post how powerful tag-based masking policies are in Snowflake. They let you enforce consistent data masking rules across columns without constantly rewriting logic. But Snowflake hasn’t stopped there—recent enhancements now make it even easier to classify, tag, and mask data at scale. In this post, we’ll recap the essentials of tag-based masking, highlight the new functionality, and share some practical tips for rolling it out in your environment.

Kevin has a new blog theme and everything.

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Adding a Drillthrough Button in Power BI

Published 2025-10-01 by Kevin Feasel

Elena Drakulevska adds a button:

If you’ve been building Power BI reports, you probably know about drillthrough.

In short: drillthrough lets users move from a summary view to a detail page focused on one data point. For example, you can right-click on Austria in a sales chart and jump straight to a page showing visuals and metrics only about Austria.

Sounds powerful, right?

The catch: most users don’t even know it’s been implemented.

The other catch: those of us sad souls using Power BI Report Server don’t get drillthrough at all.

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Set MAXDOP in Azure SQL DB

Published 2025-10-01 by Kevin Feasel

Brent Ozar has a public service announcement:

In Azure SQL DB, you set max degrees of parallelism at the database level. You right-click on the database, go into properties, and set the MAXDOP number.

I say “you” because it really is “you” – this is on you, bucko. Microsoft’s magical self-tuning database doesn’t do this for you.

And where this backfires, badly, is that Azure SQL DB has much, much lower caps on the maximum number of worker threads your database can consume before it gets cut off. 

Click through to see what kind of error message you get and just how low these limits are.

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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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Finding Rows with Errors in Power Query

Published 2025-10-01 by Kevin Feasel

Gilbert Quevauvilliers goes around looking for trouble:

In the past when there has been an error when loading data into the semantic model, there can be times when clicking on the View errors can either take a very long time to show those errors. Or in some cases it never shows you the error.

In this blog post I am going to show you an alternative way to quickly find the errors.

The column quality data preview option is absolutely worth keeping on at all times.

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CONTINUE and BREAK in T-SQL WHILE Loops

Published 2025-09-30 by Kevin Feasel

Erik Darling tries to count and gets kind of far along. The key part of the video is the use of CONTINUE and BREAK as control logic in WHILE loops. CONTINUE is something I’ve very rarely used, though it’s pretty useful. BREAK, however, is something I’m quite familiar with, especially in conjunction with record counts. This way, you can perform small updates (e.g., update 1000 records) with a filter that tells you which records still need updated, and when @@ROWCOUNT is below 1000, you know you’re done with the updates.

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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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Splitting GUIDs into Multiple BIGINTs for Columnstore

Published 2025-09-30 by Kevin Feasel

Forrest McDaniel performs an experiment:

You may have run into issues with GUIDs as clustering keys, but another major problem is in columnstore. Smart people at Microsoft wrote columnstore in a way to take advantage of modern CPU features, but those CPU features don’t play well with datatypes larger than 8 bytes. Which includes GUIDs.

Read on for the demonstration of this, a clever workaround, and the ramifications of splitting GUIDs into two BIGINTs. Full points for cleverness, though like Forrest, I wouldn’t want to use this in production.

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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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