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Category: Microsoft Fabric

Programmatic Power BI Report Modification via semantic-link-labs

Published 2024-10-02 by Kevin Feasel

Kurt Buhler makes a change:

Whether building reports in Power BI Desktop or in the web browser via the Power BI service, you have limited options to batch or streamline changes. Put another way; it’s tedious and slow to make many small changes to one or more Power BI reports. It’s also easy to make mistakes

When initially designing or building a report, this is not so much of a problem. Unless you’re using a template, you want to control report layout and formatting, yourself. However, certain changes can be little more than a waste of time. Some examples include:

  • Replacing fields when there’s a broken reference due to i.e. renaming a model measure or column.
  • Swapping one measure or column for another in the report
  • Changing visual container styles, like background, border, and shadow/glow.
  • Changing text or text styles across multiple visuals, pages, or reports.
  • Changing chart formatting (like color) or properties (like edit interactions) across multiple visuals, pages, or reports.

Read on to see how you can make some of these changes in Python code using the semantic-link-labs library.

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Managing Power BI Assets with semantic-link-labs

Published 2024-10-01 by Kevin Feasel

Kurt Buhler takes us through a Python library:

Thus far, the part of Microsoft Fabric that I’ve personally found the most interesting is not Copilot, Direct Lake, or its data warehousing capabilities, but a combination of notebooks and simple file/table storage via Lakehouses. Specifically, the library semantic link and its “expansion pack” semantic-link-labs, spearheaded by Michael Kovalsky. These tools help you build, manage, use, and audit the various items in Fabric from a Python notebook, including Power BI semantic models and reports.

Semantic-link-labs provide a lot of convenient functions that you can use to automate and streamline certain tasks during Power BI development; both of models and reports. For me, I’m particularly interested in the reporting functionalities, because this is where I typically find that I lose the most time, and because there is a drought of tools to address this area.

Read the whole thing.

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Implementing a Star Schema in a Microsoft Fabric Lakehouse

Published 2024-09-30 by Kevin Feasel

Nikola Ilic builds a lakehouse:

But, what is a star schema in the first place? I have good and bad news for you:)…The bad news is that I’m not covering it in this article because this one focuses on explaining how to implement a star schema in Fabric Lakehouse (assuming that you already know what star schema is). The good news is: I’ve already written about it, so go and read this article first, if you’re not sure what star schema represents in the world of data modeling…

In one of the previous articles, I also shown how to implement a star schema in Power BI, by leveraging Power Query Editor.

Now, let’s get our hands dirty and build a star schema by using PySpark in the Fabric notebook!

Click through to see how.

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Role-Playing Dimensions in Direct Lake

Published 2024-09-30 by Kevin Feasel

Chris Webb puts on a mustache and changes his shirt really quickly:

Note that the Sales fact table has two date columns, OrderDate and ShipDate.

If you create a DirectLake semantic model using the Web Editor and add these two tables you could rename the Date table to Order Date and build a relationship between it and the OrderDate column on the Sales table:

What about analysing by Ship Date though? You could create a physical copy of the Date table in your Lakehouse and add that to the model, but there’s another option.

Read on for that answer. Interesting that, as of right now, the primary way to do this is with third-party software.

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Tracking Microsoft Fabric Notebook Progress

Published 2024-09-26 by Kevin Feasel

Gilbert Quevauvilliers asks are we there yet? are we there yet?

How to view or track the progress of Notebook while it is running in Microsoft Fabric

I was recently working with a Notebook in Microsoft Fabric that was started via a Data Pipeline.

The challenge I had was that I had no idea how far the notebook had gone (as there were quite a lot of cells in this particular notebook).

In this blog post I am going to show you how I can use Microsoft Fabric to identify exactly which cell my notebook is currently on.

Click through for the answer. And so help me, if you ask that question one more time, I’m turning this thing around and we’re going back home.

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Data Ingestion with Microsoft Fabric Copy Jobs

Published 2024-09-25 by Kevin Feasel

Reitse Eskens spends a bunch of time at the copier:

The copy job is essentially an abstraction of a pipeline reading data from the source system and writing the data into either a Lakehouse or a Warehouse. It really is ingesting data and nothing else. In my opinion that what copy data flows are meant to do and are very good at too.

The big challenge we all keep facing is how to create incremental loads. We have to build some sort of metadata database where we keep the latest ID, data or other column we use to discern the increment on. In our flow, we need to get that value, compare it against the source system and get the differences. The biggest task is to find out if records are deleted.

With the Copy Job, a large part of this task is taken out of your hands. The Copy Job has a configuration GUI (or wizard) that helps you out quite quickly. So let’s not waste anymore characters and dig in!

Read on to see how it works and its capabilities and limitations. The key question, as always, is whether your workload fits into the wheelhouse. If so, this sounds really useful. If not, it’s a proper struggle.

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The Importance of Semantic Link

Published 2024-09-23 by Kevin Feasel

Nikola Ilic excerpts from a forthcoming book:

Since Microsoft Fabric was publicly unveiled in May 2023, there has been an ocean of announcements around this new platform. In full honesty, plenty of those were just a marketing or rebranding of the features and services that already existed before Fabric. Hence, in this ocean of announcements, some features went under the radar, with their true power still somehow hidden behind the glamour of those “noisy neighbors”. 

Semantic Link is probably one of the best examples of these hidden Fabric gems. 

Click through to learn more about Semantic Link and check out Nikola and Ben Weissman’s book as well.

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Documenting Microsoft Fabric Workspaces via Semantic Link Labs

Published 2024-09-23 by Kevin Feasel

Prathy Kamasani does a bit of documentation:

Documentation is a critical and tedious part of every project. However, it is essential to review existing developments or document new ones. When the Power BI API was initially released, I attempted to do similar things. I wanted to know how to use the API to obtain an inventory of a tenant – Power BI Template – Prathy’s Blog…. Now, I believe I am achieving the same goal but using my current favourite functionality, Fabric Notebooks.

In this blog post, I will discuss using Semantic Link and Semantic Labs to get an overview of workspaces and their contents within specified workspaces via Fabric Notebook. This is just a way of doing it; plenty of blogs discuss various things you could do with Semantic Link. Also, I want to use this to document what I have learned. I like how I can generate a Lakehouse and automatically create Delta Tables as needed.

Click through to learn more about how this works.

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Connecting to Power BI as a Guest User

Published 2024-09-20 by Kevin Feasel

Koen Verbeeck can only enter a tenant with explicit permission:

Sometimes your Microsoft Entra ID account (formerly known as Azure Active Directory) is added as a guest user in another tenant. This happens quite a lot when you’re a consultant and your client can’t create a new user in their own tenant, so they add the account of your own company as a guest instead. If you’re not a consultant, it can also happen after a merger or acquisition and you’re suddenly stuck with multiple tenants.

Yeah, this is a real annoyance with Microsoft Fabric / Power BI. Koen links to a 5-year-old feature request that I recommend upvoting.

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Updating the Default Lakehouse of a Notebook

Published 2024-09-20 by Kevin Feasel

Sandeep Pawar makes a change:

I have written about default lakehouse of a Fabric notebook before here and here. However, unless you used the notebook API, there was no easy/quick way of removing all/selective lakehouses or updating the default lakehouse of a notebook. But thanks to tip from Yi Lin from Notebooks product team, notebookutils.notebook.updateDefinition has two extra parameters, defaultLakehouse and defaultLakehouseWorkspace which can be used to update the default lakehouse of a notebook. You can also use it to update environment attached to a notebook. Below are some scenarios how it can be used.

Click through for those scenarios.

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