Bas Land 
When managing large-scale data lakes with Microsoft Fabric, performance optimisation becomes crucial. One effective technique to achieve better performance is Delta Lake partitioning. Partitioning can significantly enhance query performance, reduce computational costs, and improve data management efficiency within Microsoft Fabric environments. In this blog post, we will explore what Delta Lake partitioning is, how it …
My session, titled ‘Microsoft Fabric als succesfactor voor Power BI projecten’ (in Dutch), helped showcase attendees how Microsoft Fabric can be used as a success factor for Power BI projects. I demonstrated how Fabric can be used to collect and prepare data for Power BI, in a very cost efficient way. Microsoft Fabric als succesfactor …
This year was my first time speaking at PBIG, the largest Power BI Community Event My session, titled ‘Using Tabular Editor and best practices to speed up Power BI development – a live demo’, was aimed at speeding up your Power BI Semantic Modelling efforts using Tabular Editor. I started with a few slides on …
Understanding the cost implications of implementing Microsoft Fabric is crucial for organisations transitioning to this unified analytics platform. This guide explores the fundamentals of Fabric’s billing model, helping you make informed decisions about resource allocation and cost management. Microsoft Fabric costs is a difficult topic, apparently, let’s make it a bit more understandable! The Basics …
I had the pleasure of speaking at RADACAD’s Power BI & Fabric Summit 2025, probably one of the largest Fabric events worldwide. It is organised by the fine folks over at RADACAD and brought together more than 150 speakers and thousands of attendees. My session, titled ‘Analysing 4 Billion Rows Using Power BI DirectLake’, focused …
I had the pleasure of speaking at RADACAD’s Power BI & Fabric Summit 2025, probably one of the largest Fabric events worldwide. It is organised by the fine folks over at RADACAD and brought together more than 150 speakers and thousands of attendees. My session, titled ‘Don’t Repeat Yourself – how custom Python modules give …
Most APIs these days will have some kind of pagination built into them. This is to make sure that queries against the underlying database are not returning too much data, compromising the database performance as well as sending too large messages across the network. Often, these APIs will tell you in their responses how many …
I had the pleasure of speaking at the Danish Fabric User Group, an event hosted by community representatives and aimed at sharing knowledge between Microsoft Fabric professionals. My session, titled ‘Don’t Repeat Yourself – how custom Python modules give back hours of your time’, focused on the software engineering principle of DRY, that can be …
When we start implementing a data lake using Microsoft Fabric, we might be tempted to start creating pipelines and notebooks right away, without thinking about design principles. However, there’s one design principle I’d like you to consider from the beginning: DRY. DRY is an acronym that stands for Don’t Repeat Yourself. In this blog post, …
I had the pleasure of speaking at Data Saturday in Parma, Italy, a very nice event that brought together lots of enthusiastic, mostly Italian, data professionals. My session, titled ‘Don’t Repeat Yourself – how custom Python modules give back hours of your time’, focused on the software engineering principle of DRY, that can be brought …
Yesterday, I had the pleasure of speaking at Cloud Data Driven, a free data and analytics user group with weekly online meetings. It brought together interested data professionals from all over the world. My session, titled ‘Don’t Repeat Yourself – how custom Python modules give back hours of your time’, focused on the software engineering …
Coming from the ‘old school’ world of SSIS and SQL Server, and later Azure Data Factory and Azure SQL Database, I have always built my ETL orchestration processes using some kind of pipelines. In Fabric, we also have pipelines (the successor of ADF), but, we can now also create notebook orchestration using NotebookUtils and runMultiple(). …
In Microsoft Fabric data engineering, we use Spark to apply transformations to our data. Just like you would write T-SQL to transform data in SQL Server, you would write PySpark or SparkSQL to transform data in a Fabric lakehouse. There are a lot of parallels between Spark en SQL in the way you can process …
Introduction In this guide, we’ll dive straight into the practical steps of how to implement Medallion Lakehouses using Microsoft Fabric. If you’re unfamiliar with the Medallion Architecture, or need a refresher, check out our previous post on the theory behind the Medallion Architecture. This post focuses on hands-on implementation, guiding you through each step of …
The medallion architecture is maybe the most important concept to grasp when you start building lakehouse solutions on Microsoft Fabric. Data products should never be built ‘right away’ or on their own. There’s a structure and process to follow. Luckily, we don’t have to figure out that structure by ourselves. Rather, I’d suggest using what …
Last week, I had the pleasure of speaking at DATA:SCOTLAND, a free data and analytics conference in Glasgow that brought together nearly a thousand data enthusiasts. My session, titled ‘Your first Microsoft Fabric Lakehouse implementation’, focused on practical tips for setting up lakehouses using Microsoft Fabric. Despite being relatively new to public speaking, I enjoyed …
Yesterday, I was thrilled to deliver my first public speaking session in years! I was invited by the friendly people of the Dutch Fabric User Group to present my story to a group of about 35 people interested in Microsoft Fabric.. My session, titled ‘Fabric Lakehouses for SQL Data Engineers’, was focused on helping data …