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Category: Microsoft Fabric

Microsoft Fabric Capacities and Reserved Instances

Published 2024-09-10 by Kevin Feasel

Marc Lelijveld shares an experience:

Last week, I had a situation in which a client wanted to purchase a reserved instance Fabric capacity. Me being me, I assumed it would be super straight forward to purchase through Azure. However, at some point I was lost in the process where the official documentation confused even more. In the end, I figured out and managed to get a capacity running based on the Reserved Instance pricing. I didn’t find any other blogs or articles describing this confusion or specific case. Therefore, I decided to write down my thoughts and findings in a blog.

This blog is not only relevant if you work with Microsoft Fabric, but also for anyone currently working with Power BI Premium. Given the deprecation of Power BI Premium capacities, you have to switch to Fabric capacities sooner or later.

Read on to learn more about the differences between pay-as-you-go and reserved instance capacities, the process to make a reservation, and what comes after that before you have a Microsoft Fabric capacity ready to go.

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Querying a Fabric SQL Endpoint via Notebook and T-SQL

Published 2024-09-06 by Kevin Feasel

Sandeep Pawar talks about a Spark connector:

I am not sharing anything new. The spark data warehouse connector has been available for a couple months now. It had some bugs, but it seems to be stable now. This connector allows you to query the lakehouse or warehouse endpoint in the Fabric notebook using spark. You can read the documentation for details but below is a quick pattern that you may find handy.

Despite it not being anything new, it is still interesting to see the use case of writing T-SQL instead of Spark SQL.

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Running a Microsoft Fabric Notebook via Azure DevOps

Published 2024-09-05 by Kevin Feasel

Kevin Chant runs a notebook:

In this post I want to share one way that you can run a Microsoft Fabric notebook from Azure DevOps.

You can consider this post a follow-up to my last post about unit tests on Microsoft Fabric items. Since somebody asked me about automating notebooks and I wanted to show it in action.

Please note, currently the ability to call the API that runs a notebook on demand does not support service principals.

Despite that limitation, Kevin shows two ways to authenticate while calling the appropriate API.

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Granting Entra ID Guest Users Access to a Semantic Model via Excel

Published 2024-09-05 by Kevin Feasel

Gilbert Quevauvilliers notes an implication:

Yes, you read that right, it is possible where you have shared Power BI semantic model with an external (guest user in Entra ID) they can now connect to the semantic model using Excel.

This has been around for quite a while I just did not know about it, here is the Microsoft documentation: Semantic model connectivity and management with the XMLA endpoint in Power BI – Power BI | Microsoft Learn

The first thing to note is that this currently only works in the Excel Desktop App.

I did try using Excel on the Web and unfortunately that did not work.

I then created my Excel file, uploaded to SharePoint Online and tried to interact with the Excel Pivot table and that too did not work.

Ok enough of the limitations let me show you how to get it working.

Click through to see how. Gilbert also has an important note about row-level security, co read the whole thing.

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Building an App to Use Fabric AI Skills Locally

Published 2024-09-04 by Kevin Feasel

Sandeep Pawar takes us on-premises:

If you are a regular reader of this blog, you probably know I have been testing Fabric AI Skills extensively. I have written three blogs so far on various ways the AI Skills endpoint can be used. The feature is still in preview but I am excited to see how it can be used to create new solutions as it matures.

I was curious to test if the AI Skills endpoint can be used locally and in other applications. This will open many opportunities to integrate it in different tools, inside and outside of Fabric ecosystem. So, I built an app using Gradio to make API calls to the endpoint and show the results in a local browser along with interactive plots.

Click through for a link to the code and some instructions on how to build it yourself.

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Connecting Snowflake to Microsoft Fabric

Published 2024-09-04 by Kevin Feasel

Stephanie Bruno makes a connection:

If you’re new to Snowflake and you need to mirror a Snowflake database in Microsoft Fabric, where do you begin? The steps are straightforward enough, but when trying something new, I often get tripped up by the basics. In this case, the configuration screen for mirroring. The documentation tells us to simply enter the server and warehouse, and provides some helpful information on where to find the details, but I prefer step by step instructions with pictures. If you do, too, then this post is for you.

Click through for a walkthrough.

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Loading Scanner API JSON Data from Fabric into Power BI Desktop

Published 2024-08-28 by Kevin Feasel

Gilbert Quevauvilliers hunts for some output files:

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 post https://data-marc.com/2023/08/25/access-onelake-files-from-power-bi-desktop/

Click through for the instructions.

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mssparkutils now notebookutils and Validating DAGs in Fabric

Published 2024-08-26 by Kevin Feasel

Sandeep Pawar gives us two quick hits:

First, if you haven’t noticed mssparkutils has been officially renamed to notebookutils. Check out the official documentation for details. Be sure to use/update your notebooks to notebookutils.

Read on for a pair of notes around this name change, as well as some capabilities to validate DAGs when using runMultiple to orchestrate multiple notebook executions.

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Time Series Anomaly Detection in Microsoft Fabric

Published 2024-08-23 by Kevin Feasel

Adi Eldar talks anomaly detection:

Anomaly Detector, one of Azure AI services, enables you to monitor and detect anomalies in your time series data. This service is based on advanced algorithms, SR-CNN for univariate analysis and MTAD-GAT for multivariate analysis. This service is being retired by October 2026, and as part of the migration process

  • The algorithms were open sourced and published by the new time-series-anomaly-detector · PyPI package.
  • We offer a time series anomaly detection workflow in Microsoft Fabric data platform.

Read on to see what replacements exist and how you can use the time-series-anomaly-detector package in Microsoft Fabric.

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