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Author: Kevin Feasel

Improving Power BI Performance

Published 2026-07-27 by Kevin Feasel

James Serra has updated a guide on Power BI performance optimizations:

This post is a complete replacement for and update to my April 2022 post, Power BI Performance Features. That post focused on several performance features that were new or in preview at the time. Four years later, many of those features have matured, Microsoft Fabric has changed the architecture choices available to us, and Direct Lake has become an important part of the conversation. So rather than keep adding notes to an old feature list, I decided to step back and answer the more useful question: How should you design, diagnose, and improve Power BI performance today?

Here’s the bottom line: Power BI performance is not one feature, one setting, or one capacity size. It is the result of a chain that includes the data source, data preparation, storage mode, semantic model, DAX, report design, security, refresh process, and Fabric capacity. A weakness anywhere in that chain can become the bottleneck, which is why randomly changing DAX or buying more capacity often does not solve the real problem. The best approach is to make the right architectural choices first, measure what is slow, and then fix the layer that is actually causing the delay. For more info, see Optimization guide for Power BI.

Click through for James’s guidance.

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Looping Databases on an Azure SQL Instance

Published 2026-07-27 by Kevin Feasel

Jess Pomfret has a script:

In the on-prem world, or when we’re working with SQL Servers on VMs, wherever they might live it was pretty easy with dbatools to run a query against all the databases, collect some info and collate it into one record set. This used to work with Azure SQL Instances too – but Azure auth, or cloud auth in general is hard and recently the Connect-DbaInstance command needed to change to make it more reliable.

So, this is a quick post to cover how we can still manage this.

Click through to see how.

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Inbound Network Protection Feature Gaps in Microsoft Fabric

Published 2026-07-27 by Kevin Feasel

Meagan Longoria tells a cautionary tale:

Fabric’s inbound network protection gives you two tenant-level controls: Private Link, which routes traffic through your virtual network instead of the public internet, and Block Public Internet Access, which closes the public internet off entirely once Private Link is in place. Together they look like the obvious move if you’re trying to get a data platform off the public internet. Flip two settings, close off the internet, ship a more secure platform. That’s the pitch.

But read on to learn the downside cost to this: you’re giving up quite a bit of capability.

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Ways to Impute Missing Data in R

Published 2026-07-23 by Kevin Feasel

The DataScience+ desk compares methods:

Missing data is the daily reality of medical and epidemiological work: a patient skips a lab draw, a questionnaire item is left blank. So in this tutorial I use real health-survey data and compare three current imputation packages on it: mice (multiple imputation, still the reference method for statistical inference), missRanger (random-forest imputation, the fast successor of missForest), and VIM (k-nearest-neighbour imputation). Before any imputing I use naniar, the modern, ggplot-native toolkit for missing data, to picture where the gaps are. I also include the method most analyses actually use by default, dropping incomplete rows, because seeing why it fails is half the point.

I start from complete records, delete values myself, and check each package against the truth I hid.

Click through for the method and different ways to impute data to fill in the gaps. The text of the article looks AI-generated, though the recommendations end up being pretty solid (at least in my experience with imputation and working with mice).

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Page Splits in Animated Form

Published 2026-07-23 by Kevin Feasel

Brent Ozar paints a picture:

You’ve heard that page splits are bad, and they’re an indication that your table design is making your storage work too hard. You’ve heard that the right answer to fix it is adjusting fill factor lower, or doing regular index maintenance.

Before you watch the below animation, you’ll wanna get up to speed with how index seeks work. Then, let’s explain page splits with an animation:

Click through for the visual explanation.

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Working with DATEDIFF() and DATETRUNC()

Published 2026-07-23 by Kevin Feasel

Erik Darling has a video for us:

So we’re going to talk about just some not terribly advanced stuff, but stuff that is at least worth making sure that everyone understands when it comes to the date diff function.

There’s not terribly a lot of advanced things to say about it, but who knows where you’re starting off. So one thing that seems to get on some people’s nerves is deciding on a boundary.

So when you say, I only care about a year of data, you need to think carefully about how you do that. 

This is one tiny part of how working with dates is so painful, and not specifically due to any gap in tooling but just in how complex date and time logic is. And that’s before we even think about the date math involved in working with the Future Semiconditionally Modified Subinverted Plagal Past Subjunctive Intentional.

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Exfiltrating Data via sp_invoke_external_rest_endpoint

Published 2026-07-23 by Kevin Feasel

Vlad Druma slides some data past the bouncer:

In this post I cover how an attacker can take advantage of SQL Server 2025’s sp_invoke_external_rest_endpoint to exfiltrate data from a compromised instance.

In my previous post I used sp_invoke_external_rest_endpoint to get some data about internet-exposed SQL Server instances.
While doing that, I realized that, similarly to xp_cmdshell, SQL Server 2025’s sp_invoke_external_rest_endpoint can be used by an attacker to exfiltrate data from SQL Server.

Click through to see how.

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Securing SQL Server Maintenance Tasks

Published 2026-07-22 by Kevin Feasel

Fabiano Amorim shares some advice:

SQL Server is often marketed or perceived as secure by default, but real-world testing shows that default installations and default permissions still expose several attack surfaces. With this in mind, “secure by default” does not mean “safe without review.” 

Many risks come from legacy behavior, backward compatibility, broad permissions granted to the public role, system procedures, implicit trust boundaries, and administrative convenience features. 

The risk appears when they are combined: a database user with more permissions than necessary, a maintenance job running as a highly privileged owner, an unexpected trigger, or an impersonated module that changes how permissions are evaluated. 

Click through for a depiction of how the attack path works and things you can do to prevent systems compromise.

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Solving the Jug Problem with Bezout’s Identity

Published 2026-07-22 by Kevin Feasel

Tomaz Kastrun shifts liquids:

With DFS we can solve this with Bezout’s identity; which in general is a theorem which relates two arbitraty integers with their greatests common divisor; and used in algebraic language, finding common zeros of n-polznomials in n-indeterminates. So the common zeros equals the product of the degrees of the polynomials.

The idea, to refresh your memory, is that you have three jugs of different sizes. Tomaz uses 16L, 11L, and 7L. Using just those, how can you get 8L into each of the two larger jugs? Click through for the answer.

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