Our agenda is live! 📅 Saturday, September 26, 2026 📅 🕜 8:00 am ⭐️ SUPERCHARGE YOUR DASHBOARDS WITH POWER BI We’ll explore advanced techniques for optimizing data models

Wait, what? Resiliency? Against what? Well. The cloud sounds like an amazing, magical place without limits. The truth is, it isn't. Maybe you've seen the funny T-shirts with the text "the cloud is just someone else's computer". And that's true. Instead of building and maintaining your own data centre, you're hiring a global corporation to do that for you. And with that, you get a whole lot of options.

Before I get started, yes, I'm going to write about Power BI. If you're not familiar with my work, the long and short of it is that I tend to keep a healthy distance from anything involving semantic models and reports. Why? In one word, pie charts. Sorry if that triggered you. But every now and again, I need to do work adjacent to this; specifically, when onboarding new clients or helping them migrate things, I have to touch the Power BI stuff too.

This week, I worked for a client using the following setup. Setup They're using SQL Server databases to store their OLTP data. They use a variety of options to authenticate. Fabric isn't using private links or anything; it connects to the data through the on-premises data gateway. Inside Fabric, we chose the Copy Job activity because it helps the customer maintain the solution and fits the data we need to ingest.

I was trying out some things to learn more about RegEx when I ran into something weird. When using REGEX_LIKE in a query, I got an error in both SQL Server and Azure SQL Hyperscale. Now, I learned what will be shared in this blog from Cláudio Silva, Greg Low, and Erland Sommarskog. They were very kind to share their experiences and knowledge.

As part of the retirement of lower TLS versions 1.0 and 1.1 and the enforcement of 1.2 as the new default minimum TLS version, Azure SQL will be changing the...

Last week, I noticed that I published my 250th blog post. I'm not sure if it's something to celebrate (I'm not really someone who celebrates things), but it is an extra reason to write a new post. Endurance I started writing in 2018 after Brent Ozar suggested I do this. He also told me that the first blog posts wouldn't get that much attention, and that I had to sustain the effort to keep writing.

Retro Data is brought to you by Andy Cutler and Justin Bird. As organisers, it's become increasingly apparent how quickly our industry moves from one ...

Claude Code plugins from Erik Darling Data. Contribute to erikdarlingdata/claude-plugins development by creating an account on GitHub.

Alt: Man Giggles with a Smile

Data Community Day Austria (fka SQL Saturday Vienna) is back!Monday 18th January 2027 For 2027 we are going in-person again - and are organizing a fu...

In today's cloud era, Azure SQL is usually first with new functionality, while on-premises SQL Server follows. One of the new things is the JSON data type and accompanying JSON index. Because I had to learn how JSON works in SQL Server for my DP-800 exam, I decided to see how the JSON index works and when it works. I'll go into the execution plans, some details, and check out the statistics when a query runs.

First up, congrats to Adam Machanic and Steve Jones on reaching 200 episodes of T-SQL Tuesday; you can be proud of yourselves! I've always loved the variety of topics, the different views of the bloggers, and the learning that can be gained from all the posts. I've even had the honour of hosting. Anyway, Brent Ozar invites us this month to write about the most horrible things we've encountered in a query.

As you've probably heard and read before, monitoring your Fabric environment as a whole is quite important. It really does help to know what's going on. Now, one thing I've learned over all these years is that report users do quite like their data to be as fresh and up to date as possible. And, when the data seems stale, they tend to ask questions.

Alt: Playful Golden Retriever Dog turning in circles

Earlier this year, Microsoft released a new certification that combines AI and SQL Server knowledge: the DP-800: Developing AI-Enabled Database Solutions. As I still deeply care about SQL Server and am convinced it has a very central place in any data architecture (cloud or on-premises), this one sparked a lot of interest. Today, I took the exam, and now it's time to share my experience.

This week, I was invited to the Microsoft office in London. The reason was a Level 400 training for Microsoft partners on Real-Time Intelligence. As I've been working with RTI on a large project for the last year, it felt natural to join this training. My objectives were not listed, but I wanted to see whether the way we set up the code was consistent with best practices, whether there were things we were overlooking, and what options we could add if it would make sense.

Today I had the pleasure of presenting my session on Copilot for SQL at the Data Ceili event in Dublin. Somewhere between 50 and 60 people attended, having fun and learning how this Copilot works, what it can and can't do, and, very important today, how much it will cost you. The challenge While preparing this session, I tested some features in SSMS 22.6, and everything looked good.

A three-line title that promises a lot! So let's try to simplify this a bit. In essence, this blog will cover how to make OneLake data quicker in an Eventhouse using shortcuts. The process, at a high level, is quite simple. In your eventhouse, create a shortcut to a Lakehouse, for instance. Enable query acceleration, and you're done. If you're not using an Eventhouse, you can stay here just to read more, or take back some of your time to learn something else.

When you start using SSMS with GitHub Copilot, there is no default set of instructions in place. The agent will just sort of do what it thinks is best. But you can make sure the agent has more knowledge of your local environment (yes, it can be a cloud database as well), how it should address you and maybe what not to do.

Welcome to another instalment in the DP-700 learn series. This time we're going to talk about Apache Airflow settings. It's a little bit of a misnomer in the header, maybe, but we have to follow the titles Microsoft offers in the official curriculum. Now, before we dig into the fun techy stuff, let's familiarise ourselves with what Apache Airflow is. I was hoping that it had something to do with air conditioning, but alas.

This month, Koen Verbeeck invites the blogging community to write about their thoughts on returning to on-premises. What could be struggles, things we have to re-learn, etcetera. When I read the invite, it immediately sparked inspiration, because there are increasing rumours around cloud exits. People musing about 'what if'. Some clients reference these questions, but so far no one has directly asked me one with the intent of moving forward with it.

The DP-800 training is new and was released to GA a few weeks ago. It now sits in the same family as DP-600 (Data Analytics using Microsoft Fabric), 700 (Data Engineering using Microsoft Fabric) and 750 (Data Engineering using Databricks). The full name of this training is "Develop AI-Enabled Database Solutions". This one sparked my interest, mainly because of the word Database.

Microsoft Build 2026 highlights advancements in app development with Microsoft Fabric and Microsoft Databases, emphasizing a unified data and AI platform.

Let's be honest: how many times have you accidentally deleted something? Either on your laptop, in a database or in a SaaS product. It happens. We're all humans (unless you allow agents to do all your work for you), and mistakes happen. Until recently, when you deleted an item in Fabric, it was gone. Poof. Done. No grace period. And that was a bit scary, to be honest, but now we have a new option to help us recover from oopsies!