Search the blog

Automate Lakehouse Table Maintenance In Fabric

Automate Microsoft Fabric Lakehouse maintenance using Python ThreadPoolExecutor. Run OPTIMIZE and VACUUM across multiple tables. Complete code + error handling.

Custom Logging in Microsoft Fabric Notebooks

This blog post is a guide on how to setup custom logging to an Event house in Microsoft Fabric from a Notebook using Python.

Custom Logging Package in Microsoft Fabric

In this post we will take our custom logging from Notebooks to Eventhouse in Microsoft Fabric a step further by creating a custom package we can upload to an Environment in Microsoft Fabric.

Processing Semantic Models Using Semantic Link In Microsoft Fabric

Using a notebook with Semantic Link in Microsoft Fabric gives you more control over how each semantic model is processed and lets you refresh a single model or several at once. Utilizing Semantic Link in a notebook also makes your pipelines more reliable.

A Native macOS and Linux Semantic Model Editor

There is finally a Semantic Model editor that runs native on macOS and Linux called Semantic Modeler from Fact Foundry! It's compatible with Tabular Models for Microsoft Fabric, SQL Server Analysis Services and Azure Analysis Services!

MS Fabric Lakehouse Data Missing?

Loaded data into a Microsoft Fabric Lakehouse but can't see it? Learn why this happens on lower capacities (F16 and below) and how to fix it using REFRESH, OPTIMIZE, and VACUUM commands.

Comment Your Code

Why should you comment your code? Let's take a look at why and how to comment your code.