Top Highlights from #MSIgnite 2024

By the time you read this, I'm guessing the big #MSIgnite announcements were yesterday. You can use that hashtag to find most of the posts on social media. And there were many, very cool, announcements! Let me quickly take you through my favourites. Databases! As I still love the DBA work, announcing SQL Server 2025 … Continue reading Top Highlights from #MSIgnite 2024 →

Mastering the DP-700: Your Guide to Microsoft Fabric Certification

For those of you who either attended Fabric Conference Europe and/or have some sort of social media account, it won't come as a huge surprise that Microsoft is launching a new certification. If you're working with Microsoft Fabric and focusing on the data engineering side, this certification is for you! What is it? While the … Continue reading Mastering the DP-700: Your Guide to Microsoft Fabric Certification →

Understanding Cross Workspace Data Transfer in Microsoft Fabric

When you open Fabric, the first thing you need to do is choose a so-called workspace. This serves as a container for all your Fabric items. You can have one or more workspaces and the design is entirely up to you. From one workspace to rule them all to one workspace for each set of … Continue reading Understanding Cross Workspace Data Transfer in Microsoft Fabric →

Fabric Lakehouse Data Ingestion: CSV vs. SQL Scenarios

This blog will be a quite short one compared to the other blogs as it's more of an overview to show you the capacity of Fabric ingesting CSV files in their native format into a Lakehouse and ingesting SQL data into a table structure inside the Lakehouse. Simple, straightforward stuff without any form of modification. … Continue reading Fabric Lakehouse Data Ingestion: CSV vs. SQL Scenarios →

Testing Microsoft Fabric Capacity: Data Warehouse vs Lakehouse Performance

I just can't seem to stop doing this, checking the limits of Microsoft Fabric. In this instalment I'll try and find some limits on the data warehouse experience and compare them with the Lakehouse experience. The data warehouse is a bit different compared to the Lakehouse, so I'll be digging into that one first. Then … Continue reading Testing Microsoft Fabric Capacity: Data Warehouse vs Lakehouse Performance →

Fabric Conference key note first thoughts

Blog Alert! Arun Ulag shared some neat new developments on #MicrosoftFabric at the keynote. Here are my first thoughts on them! #mvpbuzz #FabCon

Loadtesting Fabric part 2, bringing Pain to Powerbi

In my previous blog on Fabric and loadtesting, I ended with not really knowing how PowerBI would respond to all these rows. After creating and presenting a session on this subject, it's time to dig into this part of Fabric as well. There were questions and I made promises. So here goes! This blog will … Continue reading Loadtesting Fabric part 2, bringing Pain to Powerbi →

Microsoft Fabric GA, and now?

Last week the big announcement came at Microsoft Ignite, Fabric is GA. Very cool, a lot of noise again for this shiny toolbox, but do we need to abandon everything and focus solely on the new toys? Before I'll answer that question, let's look at a few moving parts of Fabric. Integration The most important … Continue reading Microsoft Fabric GA, and now? →

Why won’t you go parallel, part 2

In my previous blogpost (Click here to read) I wrote about a query that just wouldn't go parallel. This sparked some discussion and interest from a few people who were very kind and helpful with their suggestions and even deep dives into the query plans, execution statistics etc. To make one thing very clear, this … Continue reading Why won’t you go parallel, part 2 →

Microsoft Fabric, capacity usage and a design

This monday, I was lucky enough to attend the Fabric level 300 precon at dataMindsConnect. If you ever have the chance to go there, do it! It's very well organised, the sessions are amazing and so are all the people there. But that's not what this blog is about; today a Twitter thread started on … Continue reading Microsoft Fabric, capacity usage and a design →