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Author: Kevin Feasel

Proactive Monitoring in Microsoft Fabric via Activator

Published 2025-04-10 by Kevin Feasel

Someleze Diko shows off a powerful feature in Microsoft Fabric:

Driving actions from real-time organizational data is important for making informed data-driven decisions and improving overall efficiency. By leveraging data effectively, organizations can gain insights into customer behaviour, operational performance, and market trends, enabling them to respond promptly to emerging issues and opportunities.

Setting alerts on KQL queries can significantly enhance this proactive approach, especially in scenarios such as customer support. For instance, by monitoring key metrics like response times, ticket volumes, and satisfaction scores, support teams can identify patterns and anomalies that may indicate underlying problems.

This helps drive home an important mental shift around “real-time intelligence.” Ignoring my standard disdain for misuse of the term “real-time,” most people will ignore the feature because of a perfectly reasonable belief: my data doesn’t come in that frequently, so I don’t really need to process it in near-real-time. But the real-time intelligence functionality isn’t necessarily just about loading in your data and making it available to users faster. Instead, think of it as acting immediately when your data does change, especially if you have multiple sources of data loading at different times during the day.

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Indexing for PostgreSQL in pgNow

Published 2025-04-10 by Kevin Feasel

Ryan Booz continues a series on pgNow:

In that first article, I shared how pgNow can be a lifesaver when you need immediate performance insights, highlighting features like query tuning and current activity monitoring. The tool’s ability to take periodic snapshots of query activity and spotlight active sessions has already been a significant help for early users.

Today, I wanted to look at another area of information that pgNow can help you explore during times of performance degradation or even as part of a regular database maintenance and hygiene: the Indexing tab.

Click through to see what’s in the feature and to get a free copy of the preview for pgNow.

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SQL Server Book Recommendations

Published 2025-04-10 by Kevin Feasel

Erik Darling has a list:

They are organized by author, and in no particular order of importance, quality, or anything other than how they appear on my bookshelf.

I am saddened that the $20 I sent Erik did not make it in time for my glorious book on PolyBase in SQL Server 2019 to make it on his recommendations list.

Jokes aside, you could do a lot worse than starting off with the list Erik has. There are quite a few books I’d add to that list, but the idea is not to scare people away by recommending a stack of books as tall as they are.

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Bulk Replacement in Power BI via TMDL

Published 2025-04-10 by Kevin Feasel

Gilbert Quevauvilliers finds and replaces:

It is great to see the advancements in Power BI with regards to TMDL.

Recently I was working on a customer’s semantic model where I was doing some optimizations in the semantic model.

One of the changes I wanted to make was to replace the Dynamic Format String for the measures.

My challenge was that there were roughly 40 measures where the Dynamic Format String needed to be updated.

I could have done this using Power BI Desktop, but that would mean making the changes 40 times.

Read on to see how Gilbert was able to make this change en masse.

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The Basics of Bayes’ Theorem

Published 2025-04-09 by Kevin Feasel

I have a new video:

In this video, I provide an introduction to Bayes’ theorem, explaining the key concepts and terms, as well as solving a totally realistic problem via Bayesian analysis.

My goal in this video was to explain a counter-intuitive phenomenon: how much a positive test or piece of information moves the needle depends primarily on how frequently the event normally happens and how frequently we generate false positives in tests. The less common the scenario, the less your positive test actually moves the needle.

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Error Handling in Powershell

Published 2025-04-09 by Kevin Feasel

Patrick Gruenauer catches ’em all:

Error handling is a critical aspect of writing robust scripts in any programming language. PowerShell provides a powerful structure for handling errors gracefully using try, catch, and finally blocks. These constructs allows us to manage exceptions and ensure that important cleanup actions are performed, even when errors occur. In this blog post, I will show you how to use try catch finally in PowerShell. Let’s jump in.

Click through to see how the logic works in Powershell, as well as how you can read the exception itself in the catch block.

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Finding Tables Matching a Pattern via dbatools

Published 2025-04-09 by Kevin Feasel

Jess Pomfret looks for old tables:

There are many reasons why you might end up with tables named something_old in your database. Perhaps this is part of your decommission strategy, to rename them to make sure they really aren’t in use. Or, it could be because you need to make schema changes, you can rename the current table and create a new table with the desired schema. But, the key to this blog post is when you then forget to come back and clean these tables up. We can easily find them with a dbatools command.

Read on to see how you can use dbatools cmdlets to find and remove these deprecated tables.

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SELECT FOR UPDATE in PostgreSQL

Published 2025-04-09 by Kevin Feasel

Umair Shahid preps for an update:

When multiple transactions need to modify the same rows, ensuring data consistency can become tricky. A single wrong approach to locking can lead to suboptimal performance or even bring your application to a standstill as numerous transactions block one another. One tool in PostgreSQL’s arsenal to handle concurrency is SELECT FOR UPDATE. It allows you to lock specific rows before updating them, preventing other transactions from modifying those rows until your transaction completes.

In this blog, we will dive deep into SELECT FOR UPDATE in PostgreSQL. We will explore how it helps in reducing contention, avoiding deadlocks, and ultimately boosting performance when dealing with highly concurrent applications.

Click through to understand how this works and also some notes on when to use it and when not to use it.

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