Direct Lake or Import which Semantic Model has the best performance
In this blog post I am going to show you how I completed the automated testing and then the results where I am going to compare Direct Lake, Import and DirectQuery and which one appears to be the best. As always, your testing may very or be different to my tests below. I would highly recommend that you use the…
Comparing Microsoft Direct Lake vs Import– Which Semantic Model performs best?
I was recently part of a discussion (which I have heard of multiple times), which was which semantic model to use in Microsoft Fabric. This was the source for this blog post where I am going to compare Microsoft Direct Lake (DL) to an Import Semantic Model. The goal is to first explain how I set up and configured the…
Backing Up Your Microsoft Fabric Workspace: A Notebook-Driven Approach to Disaster Recovery
In the high-stakes world of data architecture, where downtime can cascade into real business disruptions, I’ve learned that even the most robust platforms have their blind spots. Just last month, while collaborating with a client’s Architecture team on their disaster recovery strategy, we uncovered a subtle but critical gap in Microsoft Fabric: while OneLake thoughtfully mirrors data across multiple regions…
Power BI MCP Tuner Server and does it reduce capacity requirements – Part 4
This blog post is about using MCP to tune DAX and then using the Automated Load Testing does it reduce capacity. I originally did not plan for this post but after viewing the details from Justin Martin – DAX Performance Tuner | LinkedIn I had to give it a go. It was then easy for me to test if the…
Running and viewing Automated Load Testing Results – Part 3
This blog post is going to detail how I run the load test and then view the load testing results to determine how the capacity has coped when I increase the number of users. Along with demonstrating how I automated the load testing without having to run it manually! Please find below the previous series in case. This is the…
Automating Load Testing Setting Up Your Fabric Lakehouse and Notebooks – Part 2
In today’s blog post I am going to show you how to set up the Lakehouse and Fabric notebooks so that you can then configure it to be ready to be used with the JSON file we created in the previous blog post. Series Details Part 1: Capturing Real Queries with Performance Analyzer Part 2 (This blog post): Setting Up…
Fabulous Fabcon Vienna 2025
In this blog post I will be covering the Fabcon Vienna updates. Apologies for the misspelling of the word “Announcements” I had recorded the video and was too lazy to re-record! Below are the slides that I presented in my video along with the links, which could be useful if you want more information. CI/CD 100% Support Fabric Command…
Comparing Fabric Capacity Consumption – Notebook vs Warehouse SQL
I saw that there was an update where it is now possible to use the Microsoft Fabric Warehouse to copy data directly from OneLake into the Warehouse. This got me thinking, which would consume more capacity to get the data into the Warehouse table. As well as which one would be faster. To do this I am going to be…
How to use the Tabular Object Model using Semantic Link Labs in a Microsoft Fabric Notebook
In this blog post I am going to show you how to use the powerful Semantic Link Labs library for Tabular Object Model (TOM) for semantic model manipulation. The goal of this blog post is to give you an understanding of how to connect using TOM, then based on the documentation use one of the functions. Don’t get me wrong…
Using a Python Notebook Loop through a data frame and write once to a Lakehouse Table
In this blog post I am going to explain how to loop through a data frame to query data and write once to a Lakehouse table. The example I will use is to loop through a list of dates which I get from my date table, then query an API, append to an existing data frame and finally write once…