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Category: Microsoft Fabric

Dynamic Historical Partition Refresh in Power BI

Marc Lelijveld digs into partition refreshing:

I’ve heard the question pretty often from customers: “You told me to use incremental refresh, but how can I regularly run a full load or refresh onder partitions?” Well, there are perfect ways to do this using Tabular Editor or SQL Server Management Studio. But this often includes manual work to trigger the processing.

Today, this question was asked again to me. I thought, there should be a smarter way to do this. Since I recently explored more in the wonderful world of Fabric Notebooks and Python, decided to dive a bit deeper in this world and see if it is possible to script something like this using Semantic Link. And obviously, the answer is “Yes!”

Read on to learn how to do it with a bit of Python and Microsoft Fabric’s Semantic Link library (sempy).

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Looping through Data in Microsoft Fabric PySpark Notebooks

Gilbert Quevauvilliers builds a loop:

Continuing with my existing blog series on what I’m learning with notebooks and PySpark.

Today, I’m going to explain to you how I found a way to loop through data in a notebook.

In this example, I’m going to show you how I loop through a range of dates, which can then be used in a subsequent query to extract data by passing through each date into a DAX query.

Click through for Gilbert’s example. Here’s an alternative using something called a list comprehension. First, build a function that does what you want to do—that’d be the innards of Gilbert’s Python code, lines 31-54.

def perform_dax_query(row):
    var_Date = row["Date"]
    ...
    display(df_DAX_QueryResult)

Then, call that function for each row:

[perform_dax_query(row) for row in data_collect]

In this particular scenario, I’d personally stick with Gilbert’s composition, but in cases where you’re transforming a list of elements into a new list—for example, if you’re performing some data cleanup for each row in a list and you want the output to be a new list with cleaned-up data—then the list comprehension works really well.

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An Introduction to the Native Execution Engine in Microsoft Fabric

Sandeep Pawar gives us the gentle version:

At MS Build, Microsoft announced availability of Native Execution Engine in Fabric. The product team will have detailed documentation and technical details but I will attempt to provide an ELI5 version of what it means and how it works at a 30000 ft level.

Read on to learn what the Native Execution Engine is and why Microsoft would use it versus running everything in the Java Virtual Machine like other services in the broader Hadoop ecosystem have historically done (at least at the beginning, before they built their own native execution engines!).

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Building a Power Query Template

Nikola Ilic looks at Power Query templates:

In this “ocean” of innovations, there are certain features that don’t get the deserved limelight – as they somehow go under the radar. Some of them, I really consider “hidden gems” – you might not use them in each and every solution, but in some scenarios, they can be of immense help.

A hidden gem that I’m introducing today is called Power Query Template. As of today, this feature is still in preview (the same as many others in Microsoft Fabric), but this doesn’t minimize its potential.

Read on to see why Nikola likes capability this so much.

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Time Travel in the Microsoft Fabric Warehouse

Reza Rad hops in the Delorean:

Data changes throughout time, especially in the world of BI and data warehousing systems; the data gets updated through ETL processes frequently. This means that the data you see in the warehouse today might differ from yesterday and the day before, and so on. Some parts of this data can be retrieved on a timely basis. You can, for example, query the sales amount from the sales table where the date has been the 2nd of April. That would give you the sales amount for the 2nd of April, even if you are querying it on the 23rd of May.

However, what if some of the sales transactions on the 2nd of April got updated? The sales amount you see would likely be the updated amount, but not the original amount. It is sometimes useful to be able to see what was that original amount, or in other words, travel in time and see what that value was.

Click through for a combination video and article. The syntax isn’t quite the same as with temporal tables in SQL Server, though it’s close enough to follow along if that’s your relevant experience.

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Open Questions on Fabric Administration

Paul Andrew asks some great questions:

Microsoft Fabric is a big product with lots of different data handling capabilities. From a data engineering perspective creating and innovating with Fabric as a unified tool is a great experience, ultimately delivering data insights for the business and adding value, nice! However, as with all new developments, the creativity is the fun part. The governance and movement of code into production is less fun and can become the hard/ugly part if the change management, platform and governance aren’t mature enough.

Paul doesn’t have answers for us, though I do think many of these will eventually have answers most people find reasonable.

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Data Connections in Microsoft Fabric

Soheil Bakhshi takes us through the ins and outs of data connections:

Managing data connections in Microsoft Fabric can be challenging if you’re unsure where to start. This blog post and its detailed YouTube video will help you find, manage, and share the existing data connections, making your workflow more efficient and streamlined. A meaningful use case for this feature is to reuse the existing connections leading to more controlled connections to the data sources. More on this later in this blog.

Click through for the article and link to the video.

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Using F-SKU Power BI Capacity and Microsoft Fabric

Chris Webb has a public service announcement:

Since the announcement in March that Power BI Premium P-SKUs are being retired and that customers will need to migrate to F-SKU capacities intead I have been asked the same question several times:

Why are you forcing me to migrate to Fabric???

This thread on Reddit is a great example. What I want to make clear in this post is the following:

Moving from P-SKU capacities to F-SKU capacities is not the same thing as enabling Fabric in your tenant

Click through for Chris’s explanation. Also check out the comments section for this one, as there are plenty of questions and responses in there.

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Authenticating to Fabric APIs via Sempy and Service Principals

Gilbert Quevauvilliers links everything together:

I have been doing a fair amount of work lately with Fabric Notebooks.

I am always conscious to ensure that when I am authenticating using a Service Principal, I can make sure it is as secure as possible. To do this I have found that I can use the Azure Key Vault and Azure identity to successfully authenticate.

Read on for some of the advantages of using Azure Key Vault for this sort of credential management, as well as how to get it all working.

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