Microsoft Fabric
Fabric: Lakehouse or Data Warehouse?
There are 2 kinds of companies currently active in the Microsoft data space: those who are migrating to Microsoft Fabric, and those who will soon be planning their migration to Microsoft Fabric. 😅 One question that often comes back is Should I focus on the Lakehouse or the Data Warehouse? Let’s answer that in this post. I can already tell you this: you’re asking the wrong question 😉
Is Microsoft Fabric just a rebranding?
It’s a question I see popping up every now and then. Is Microsoft Fabric just a rebranding of existing Azure services like Synapse, Data Factory, Event Hub, Stream Analytics, etc.? Is it something more? Or is it something entirely new? I hate clickbait titles as much as you do. So, before we dive in, let me answer the question right away. No, Fabric is not just a rebranding. I would not even describe Fabric as an evolution (as Microsoft often does), but rather as a revolution! Now, let’s find out why.
My take-aways from Big Data London: Delta Lake & the open lakehouses
Last week I attended Big Data London. Both days were filled with interesting sessions, mostly focussing on one of the vendors also exhibiting at the conference. There are 2 things I am taking away from this conference: Delta Lake has won the data format wars, and your next data platform is either Snowflake, either an open Lakehouse.
Fabric end-to-end use case: Analytics Engineering part 2 - Reports
Welcome to the fifth part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the analytics engineering part of the use case. In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case.
Fabric end-to-end use case: Analytics Engineering part 1 - dbt with the Lakehouse
Welcome to the fourth part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the analytics engineering part of the use case. In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case.
Fabric end-to-end use case: Data Engineering part 2 - Pipelines
Welcome to the third part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the data engineering part of the use case. In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case.
Fabric end-to-end use case: Data Engineering part 1 - Spark and Pandas in Notebooks
Welcome to the second part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the data engineering part of the use case. In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case.
Fabric end-to-end use case: overview & architecture
Welcome to the first part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the architecture overview of the use case. In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case.
All Microsoft Fabric icons for diagramming
Do you often have to draw up diagrams of data flows or data architectures and would you like to use Microsoft Fabric icons in your diagrams? Then this post is for you! I always found it hard to find the right icons I needed, so I’ve put them all on this single page for easy access, both as PNG and SVG.
Let Fabric teach you how to code with Data Wrangler
I’m going to be honest with you. I’m bad at writing Pandas data transformation code. Throughout the years I mostly focussed on the Spark APIs in Scala and PySpark, SQL, dbt, and some others, but I find the Pandas APIs usually just confusing and hard to read. I don’t like the black box magic and lock-in of low-code solutions either. Did you know that Microsoft Fabric has the perfect middle ground for this? It’s called Data Wrangler. Let’s dive in!
How to use service principal authentication to access Microsoft Fabric's OneLake
Microsoft recently added support to authenticate to OneLake using service principals and managed identities. This allows users to access OneLake from applications without having to use a user account. Let’s see how this works.
A closer look at Microsoft Fabric pricing, billing, and autoscaling
If you’re considering using Microsoft Fabric, you’re probably thinking “How much is this going to cost me?” Continue reading to learn how Microsoft might have just created the most compelling data platform offering available today.
Migrating Azure Synapse Dedicated SQL to Microsoft Fabric
If all those posts about Microsoft Fabric have made you excited, you might want to consider it as your next data platform. Since it is very new, not all features are available yet and most are still in preview. You could already adopt it, but if you want to deploy this to a production scenario, you’ll want to wait a bit longer. In the meantime, you can already start preparing for the migration. Let’s dive into the steps to migrate to Microsoft Fabric. Today: starting from Synapse Dedicated SQL Pools.
Connect to Fabric Lakehouses & Warehouses from Python code
In this post, I will show you how to connect to your Microsoft Fabric Lakehouses and Warehouses from Python.
Preparing a migration to Microsoft Fabric: from Azure Synapse Serverless SQL
If all those posts about Microsoft Fabric have made you curious, you might want to consider it as your next data platform. Since it is very new, not all features are available yet and most are still in preview. You could already adopt it, but if you want to deploy this to a production scenario, you’ll want to wait a bit longer. In the meantime, you can already start preparing for the migration. Let’s dive into the paths to migrate to Microsoft Fabric. Today: starting from Synapse Serverless SQL Pools.
Microsoft Fabric's Auto Discovery: a closer look
In previous posts , I dug deeper into Microsoft Fabric’s SQL-based features and we even explored OneLake using Azure Storage Explorer . In this post, I’ll take a closer look at Fabric’s auto-discovery feature using Shortcuts. Auto-discovery, what’s that? Fabric’s Lakehouses can automatically discover all the datasets already present in your data lake and expose these as tables in Lakehouses (and Warehouses). Cool, right? At the time of writing, there is a single condition: the tables must be stored in the Delta Lake format. Let’s take a closer look.
Exploring OneLake with Microsoft Azure Storage Explorer
Recap: OneLake & Delta Lake One of the coolest things about Microsoft Fabric is that it nicely decouples storage and compute and it is very transparent about the storage: everything ends up in the OneLake. This is a huge advantage over other data platforms since you don’t have to worry about moving data around, it is always available, wherever you need it.
Welcome to the 3rd generation: SQL in Microsoft Fabric
While typing this blog post, I’m flying back from the Data Platform Next Step conference where I gave a talk about using dbt with Microsoft Fabric . DP Next Step was the first conference focussed on Microsoft data services right after the announcement of Microsoft Fabric so a lot of speakers were Microsoft employees and most of the talks had some Fabric content. Fabric Fabric Fabric, what is it all about? In this post I’ll go deeper into what it is, why you should care and focus specifically on the SQL aspect of Fabric.