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Category: Microsoft Fabric

Data Ingestion with Microsoft Fabric Copy Jobs

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

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

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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Updating the Default Lakehouse of a Notebook

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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Connecting to Power BI as a Guest User

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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Domain Lineage in Microsoft Fabric

Sandeep Pawar creates 1000 words of value:

In Fabric, you can use the Domains to create a data mesh architecture. It allows you to organize the data and items by specific business domains within the organization and make the overall data architecture decentralized. You can create domains within domains and assign workspaces to each domain. As it grows, you may find it challenging to understand how the domains & workspaces have been organized. Below code will help you trace the domains, subdomains and the workspaces assigned to them.

Click through to see how you can use the graphviz library in Python to generate a simple domain chart.

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Microsoft Fabric Direct Lake and Reframing Operations

Reza Rad changes the frame:

Power BI offers a new type of connection to Microsoft Fabric Lakehouse or Warehouse, called Direct Lake. The Direct Lake connection acts like DirectQuery and won’t need the data to be refreshed. However, the Power BI semantic model has refresh settings that can be turned on or off. In this article and video, you will learn about the Refresh settings for the Power BI semantic model that is connected using a Direct Lake connection, what that is, and why it is called Reframe.

Read on to learn more, or to check out the video.

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Microsoft Fabric Capacities and Reserved Instances

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

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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