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Category: Microsoft Fabric

Querying the Power BI REST API from Fabric Spark

Gerhard Brueckl makes the call:

Microsoft Fabric has a lot of different components which usually work very well together. However, even though Power BI is a fundamental part of Fabric, there is not really a tight integration between Data Engineering components and Power BI. In this blog post I will show you an easy and reusable way to query the Power BI REST API via Fabric SQL in a very straight forward way. The extracted data can then be stored in the data lake e.g. to create a history of your dataset refreshes, the state of your workspaces or any other information that is provided by the REST API.

Click through for a list of operations, followed by the code you’ll need to pull this off.

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Multiple Workspaces and Microsoft Fabric Git Integration

Kevin Chant can’t stop at one:

In this post I want to cover working with Microsoft Fabric Git integration and multiple workspaces. By highlighting one method that you can use in the real-world.

I must admit that I have been very keen to test this particular way of working with Microsoft Fabric Git integration and multiple workspaces.

By the end of this post, you will know one way that you can work with Microsoft Fabric Git integration and multiple workspaces. Based on real-world working practices. Including multiple branches and pull requests.

Click through to see what Kevin has in mind usingg Azure DevOps.

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Storing Log Analytics Data in the Microsoft Fabric Lakehouse

Gilbert Quevauvilliers needs a place to store this data:

Following on in my series, in this blog post I am going to use the dataflow Gen2 in Microsoft Fabric to load the data into a lake house table.

By doing this, it will allow me to store the data in a delta lake table.

In this series I am going to show you all the steps I did to have the successful outcome I had with my client.

Click through for links to the first two parts of the series, as well as a step-by-step guide for part 3.

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Comparing the Microsoft Fabric Data Wrangler and Power Query Editor

Reza Rad performs a comparison:

Power Query Editor and Data Wrangler are data transformation and preparation tools in Microsoft Fabric. There are similarities between these two tools. However, there are differences, too. It is essential to know the capabilities of each tool to understand which one should be used for what purpose and scenario. In this article, this is our quest.

Reza includes a video and an article. Reza also has a summary chart at the bottom.

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Accessing OneLake Files from Power BI Desktop

Marc Lelijveld reads a file:

Fabric content is all over the place by now. In Fabric, as a SaaS platform, most (if not all) services have interconnectivity. In a few clicks you connect your web-developed Power BI dataset to a lakehouse, or warehouse to fetch data from OneLake. But what about Power BI Desktop? You might have uploaded some files to OneLake which you cannot access from Power BI Desktop.

In this blog I’ll explain on how you can connect to OneLake data using Power BI Desktop!

This turns out to be a bit trickier than I would have expected. Hopefully the experience gets better over time.

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Git Integration for Power BI Reports in Microsoft Fabric

Kevin Chant gives GIt integration a try:

To manage expectations, this post covers:

  1. Brief overview of Microsoft Fabric Git integration.
  2. How I converted a Power BI report to a Power BI Desktop project containing metadata files.
  3. Converting the folder that contains the Desktop project into a Git repository.
  4. Synchronizing the Git repository with Azure DevOps.
  5. Setting up Microsoft Fabric Git integration.
  6. Initial tests.
  7. Interesting workaround to deploy a second Power BI report using metadata.

Read on for Kevin’s thoughts.

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Contrasting Azure Synapse Analytics and Microsoft Fabric

Warner Chaves explains the difference:

In the modern era of data-driven decision-making, businesses rely heavily on robust and efficient data platforms to process, analyze, and derive insights from their vast amounts of data. Since 2019, Azure Synapse Analytics has been Microsoft’s main contender in this space, offering powerful capabilities to handle complex data workloads.

Now, Microsoft has announced a new data platform called Microsoft Fabric, an evolution of the data platform built with a modified philosophy. It is a similar product but with enough differences to make them not interchangeable and so it’s very important to understand how they both compare and contrast if you’re planning a new data platform deployment. Microsoft wanted a product that was even simpler to deploy and operate and could function well outside of an Azure cloud environment as a full standalone Software As a Service offering.

In this blog post, we’ll compare Synapse Analytics and Fabric, highlighting their features, strengths, and considerations to help you make an informed decision for your organization’s data needs.

Warner has seven main areas of comparison, so click through to see how the two products stack up.

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Against Waiting for Microsoft Fabric

Paul Andrew follows Betteridge’s Law of Headlines:

But, lets prepare for it in terms of the technical capabilities we line up in our existing data architecture.

The hype curve around Microsoft Fabric since its announcement earlier in the year has been huge. The problem is, we now face some difficult questions in terms of our technology estate. Especially if we have designs and a project already in flight using other Azure Resources.

Read on for Paul’s thoughts on the matter and why you shouldn’t wait until Microsoft Fabric is officially out—use what is available in the meantime and then decide whether you want to make a transition. Paul leaves one thing in the margins that I would want to make clear: if this is your plan, avoid the dedicated SQL pool unless you absolutely need it or plan to stay on Synapse once Fabric is GA.

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Tenant Configuration in Microsoft Fabric

Marc Lelijveld collects some data:

It has been quiet for a few weeks due to summer break. But now, it’s time to ramp up again and continue posting about Fabric. This time, I’ll start with a question that many Fabric (and Power BI) users ask themselves: “What does my tenant configuration look like?”. Often, users find themselves eager to explore new features they’ve come across online. But somehow, they cannot get it to work, or the feature does not even show for them.

In this blog, I’ll elaborate on the challenges and scenarios in which questions like these come up, and what you can do as a Fabric / Power BI administrator to ease answering this question.

Read on for one of the most common scenarios.

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