How to get data from a Fabric Lakehouse File into Power BI Desktop – Using Scanner API JSON
How to get data from a Fabric Lakehouse File into Power BI Desktop – Using Scanner API JSON In this blog post I am going to show you how I connected to my Scanner API JSON file which is stored in the files section of my Microsoft Fabric Lakehouse. Full credit on how to complete this comes from Marc’s blog…
Downloading Scanner API data using a Microsoft Fabric Notebook
Downloading Scanner API data using a Microsoft Fabric Notebook I was recently working with a customer where they had more then 100 app workspaces and I was running into some challenges when using the Scanner API in Power Automate. I then discovered this blog post where they detailed how to download the Scanner API data (DataXbi – admin-scan.py), it was…
How to read a Lakehouse table in another App Workspace – Microsoft Fabric
I was doing some work recently for a customer and they had data stored in different Lakehouse’s which was in a different App Workspace. I was pleasantly surprised that this can be quite easy to do. In my example below I am going to show you how in my notebook I can read a table in a Lakehouse table when…
How to stop/fix Mirroring to a database in Microsoft Fabric
How to stop/fix Mirroring to a database in Microsoft Fabric I recently had a challenge where the mirroring in Fabric stopped working because there was no activity. For me to start this again when I tried to connect to a table it said the database was already being used to mirror as shown below. Here is the text error which…
Semantic-Link-Labs – Automate updating your Incremental Refresh Policy for your Semantic Model
The scenario here is that quite often there is a requirement to only keep data from a specific start date, or where it should be keeping data for the last N number of years (which is the first day in January). Currently in Power BI using the default Incremental refresh settings this is not possible. Typically, you must keep more…
Loading Fabric Lakehouse Tables with partitions
When loading data, it is always important to load the data with performance and scalability in mind. For lakehouse tables to return queries quickly and to scale it is essential to load your lakehouse tables with partitions. What I am going to show you in my blog post today is how to load data into a Lakehouse table where the…
Easily scale up or scale down your Fabric Capacity using Power Automate (Via email)
Easily scale up or scale down your Fabric Capacity using Power Automate (Via email) Following on from my previous blog post (Stop and start your Fabric Capacity using Power Automate) I got a question from Tristan as shown below! I always enjoy a good challenge and I got it working! In this blog post I will use the same method…
Stop and start your Fabric Capacity using Power Automate
Stop and start your Fabric Capacity using Power Automate With Fabric Capacities trial coming to an end, you need to make sure to stop and start Fabric Capacities. In my blog post below, I am going to show you how I can start or stop my Fabric Capacity by simply sending an email to myself with the details in the…
How to get the TopN rows using Python in Fabric Notebooks
How to get the TopN rows using Python in Fabric Notebooks When working with data there are sometimes weird and wonderful requirements which must be created in order to get to the desired solution. In today’s blog post I had a situation where I wanted to get a single row with the highest duration. This is how I did it…
Looping through data using PySpark notebook in Fabric
Fabric Notebooks – Looping through data using PySpark Continuing with my existing blog series on what I’m learning with notebooks and PySpark. Today, I’m going to explain to you how I found a way to loop through data in a notebook. In this example, I’m going to show you how I loop through a range of dates, which can then…