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Category: Microsoft Fabric

Troubleshooting Non-Editable Power Query Parameters in Microsoft Fabric

Published 2024-08-20 by Kevin Feasel

Soheil Bakhshi digs into a problem:

Power Query is a powerful tool within the Microsoft Fabric environment, enabling users to manage data sources and transform data efficiently. However, a common issue you may face is that after publishing the Semantic Model, the Power Query parameters either do not appear or are greyed out, making them non-editable. In this post and its accompanying YouTube video, I’ll walk you through the steps to diagnose and fix these problems, ensuring that your parameters work as expected in your published semantic models.

Click through for the video and a pair of common reasons.

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Finding Columns in Memory in Power BI Direct Lake Mode

Published 2024-08-20 by Kevin Feasel

Chris Webb goes searching:

As you probably know, in Power BI Direct Lake mode column data is only loaded into memory when it is needed by a query. I gave a few examples of this – and how to monitor it using DMVs – in this blog post from last year. But which columns are loaded into memory in which circumstances? I was thinking about this recently and realised I didn’t know for sure, so I decided to do some tests. Some of the results were obvious, some were a surprise.

Read on for the answer.

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Microsoft Fabric Capacity Limits

Published 2024-08-16 by Kevin Feasel

Teo Lachev builds a pair of tables:

Here is table that is getting more and more difficult to find as searching for Fabric capacity limits returns results about CU compute units (for the most part meaningless in my opinion). I embed in a searchable format below before it vanishes on Internet. The most important column for semantic modeling is the max memory which denotes the upper limit of memory Fabric will grant a semantic model.

Click through for that table, followed by a table comparing Fabric SKUs to Power BI SKUs.

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A Reference Architecture for Microsoft Fabric

Published 2024-08-15 by Kevin Feasel

James Serra draws boxes:

Microsoft Fabric uses a data lakehouse architecture, which means it does not use a relational data warehouse (with its relational engine and relational storage) and instead uses only a data lake to store data. Data is stored in Delta lake format so that the data lake acquires relational data warehouse-like features (check out my book that goes into much detail on this, or my video). Here is what a typical architecture looks like when using Fabric (click here for the .vsd):

Click through for the image as well as James’s explanation of the components.

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Building a Microsoft Fabric AI Skill to Generate Data

Published 2024-08-13 by Kevin Feasel

Sandeep Pawar tries out AI Skills in Microsoft Fabric:

In the last blog I wrote, I showed how to call the AI Skills endpoint in a Fabric notebook. Being able to call the endpoint programmatically creates many opportunities to integrate AI Skills in different applications. One that I thought of was using AI Skills as a function. Function Calling or Tools is a specific use case in Gen AI to create structured output based on a function or behavior instructed by the user. I am not referring to that as AI Skills can only return a table. Instead, what if you created a number of these AI Skills that are grounded in your data with specific functions built to get the intended output? You could serve/share these with end users who can call these functions to generate data/results. Think of these as macros in Excel.

Click through for an example of how it works.

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Cosmos DB HTAP into Azure Synapse Analytics and Microsoft Fabric

Published 2024-08-13 by Kevin Feasel

Paul Hernandez doesn’t want to write ETL jobs:

In the ever-evolving landscape of data management and analytics, choosing the right tools and approaches is crucial for optimizing performance and achieving business goals. Two prominent solutions that have gained traction are Azure Synapse Link for Azure Cosmos DB and Mirroring in Microsoft Fabric. Both offer unique benefits and cater to different needs, making it essential to understand their differences and use cases.

Read on to see how each of these works, as well as a quick demonstration of efficacy.

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Using AI Skills as Cell Magics in Microsoft Fabric Notebooks

Published 2024-08-09 by Kevin Feasel

Sandeep Pawar takes a look at a new preview capability:

The public preview of AI Skills in Microsoft Fabric was announced yesterday. AI Skills allows Fabric developers to create their own GenAI experience using data in the lakehouse. Unlike Copilot, which is an AI assistant, AI Skills lets users build a validated Q&A application that queries lakehouse data by converting natural language questions into T-SQL queries. It’s only available in paid F64+ SKUs. You can watch the below video for Copilot, AI Skills and Gen AI experiences in Fabric:

Read on for more details on how it works.

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Building Real-Time Dashboards from Lakehouse Data in Microsoft Fabric

Published 2024-08-09 by Kevin Feasel

Dennes Torres gets around a limitation:

Real-Time dashboards are a great feature in Real Time Intelligence experience to monitor our data. However, by default it’s made to work only with Kusto Databases. The options to create a real time dashboard or to define its data source only accept Kusto Databases.

What if we would like to see in real time the information we have in a lakehouse as well? Let’s discover a solution for this.

Read on for the solution.

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Managed Private Endpoints and Trusted Workspace Access for All

Published 2024-08-07 by Kevin Feasel

Wolfgang Strasser is very pleased with a recent announcement:

In times of data breaches and millions of customer entries breached, the security of your data platform is one of the things you need to consider upfront and – preferably in all your data solutions.

When Microsoft Fabric was announced the concepts of connecting to other parts of your already secured data platform in Azure was not possible. The options to (securely) connect Fabric to other parts of your Azure platform were not available initially.

Read on to learn more about Managed Private Endpoints and Trusted Workspace Access, the initial problem with them both, and how Microsoft has definitely improved things recently.

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