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Category: Microsoft Fabric

Data Warehouse Updates for Microsoft Fabric

Published 2023-11-09 by Kevin Feasel

Dennes Torres brings the news:

We have a specific statement to clone a table. But what exactly does it mean?

The Clone Table feature promises to create an image of the table on a specific point in time or with the current information. The documentation is not precise, because at some points it says it’s only a clone of the structure, but we can see the data on the table.

What’s the advantage of this over a simple SELECT INTO statement?

Read on for that comparison, as well as several other things recently added to Microsoft Fabric data warehouses.

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Microsoft Fabric Cost and Capacity

Published 2023-11-08 by Kevin Feasel

Soheil Bakhshi lays out the options:

Microsoft Fabric is a SaaS platform that allows users to get, create, share, and visualise data using a wide set of tools. It provides a unified solution for all our data and analytics workloads, from data ingestion and transformation to data engineering, data science, data warehouse, real-time analytics, and data visualisation. In a previous blog post, I explained the basics of the Microsoft Fabric data platform. In a separate blog post, I explained some Microsoft Fabric terminologies and personas where I explained what Tenant and Capacities are.

In this blog post, we will explore the different types of Fabric capacities, how they affect the performance and cost of our Fabric projects, and how you can control the capacity costs by pausing the capacity in Azure when it is not in use.

Click through for more information. The costs are in New Zealand Dollars, so translate as needed.

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A PBIX Report for Microsoft Fabric’s Support Page

Published 2023-11-03 by Kevin Feasel

Gilbert Quevauvilliers checks the status of Microsoft Fabric services:

What I wanted to show you is that I have created a Power BI report which shows the Microsoft Fabric Support page details.

I created one for Power BI which I receive daily, and it is great to get the subscription so that I am aware of any potential issues or changes affecting the Power BI Service.

I now have done the same thing for the Microsoft Fabric Support page; I have enabled the report subscription which I get daily.

Click through to see what it looks like and how you can get a copy of it for your own nefarious purposes.

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Fun with Tables in the Microsoft Fabric Lakehouse

Published 2023-11-03 by Kevin Feasel

Nikola Ilic dives into tables:

Probably the biggest confusion is: should I use a lakehouse or warehouse in Fabric? Or, what is the difference between Direct Lake and DirectQuery mode for Power BI reports?

And, while these two points mentioned above are of paramount importance to clarify, in this article I’ll focus on explaining another potential caveat, which is relevant when working with the lakehouse in Microsoft Fabric.

If only Nikola dove onto tables, I could make him an honorary Buffalo Bills fan.

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Formatting DAX Expressions with Python

Published 2023-11-01 by Kevin Feasel

Sandeep Pawar makes the code a bit more readable:

There is an old Italian saying “If it’s not formatted, it is not DAX”

When you get the list of measures from SemPy, it’s not formatted and is hard to read and understand. Thankfully, the SQLBI team has made the DAX parser and the formatter available via an API. I wrote a quick function to return the formatted DAX expression of a measure. You can either pass a DAX expression or the FabricDataFrame returned by fabric.list_measures()

Click through for the process, including the Python code to do the work.

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An Overview of the Current State of Microsoft Fabric

Published 2023-11-01 by Kevin Feasel

Paul Andrew pulls no punches:

Despite playing with different parts of the Fabric ecosystem for a long time. Nothing ever prepares you for the challenges and “quirks” faced when building a solution for real. In this post I’ll call out some of the pain points we’ve faced and features of the product still requiring improvement. Excluding some of the obvious gaps in the product like security, that we know to be coming.

Read on for Paul’s analysis on what Fabric is currently missing, but as you do read it, keep in mind that this is still in public preview and even after it goes GA, Microsoft will continue development on Fabric.

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Loading Data from Sharepoint Lists into Microsoft Fabric

Published 2023-10-31 by Kevin Feasel

Stepan Resl loads some data:

In a time of Fabric, it’s worth pointing out our three options for data ingestion.

  • Data Pipelines with Copy Activity
  • Dataflows Gen 2
  • Notebooks

We must compare them to understand ​​what each can offer us from different perspectives. To be able to compare them thoroughly, there are some guardrails that we need to set so that everything goes the same way.

My biggest takeaway from this is, don’t load important business data into Sharepoint Lists to begin with.

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Row- and Column-Level Security in Microsoft Fabric Warehouses

Published 2023-10-30 by Kevin Feasel

Maheswaran Arunachalam gives us an update on data security in Microsoft Fabric:

Row-Level Security (RLS) and Column-Level Security (CLS) are methods that simplify the design and coding of security in applications by imposing restrictions on data access. CLS allows for specific users to access only certain columns of a table relevant to their department, protecting sensitive data. RLS, on the other hand, restricts users to accessing only data rows pertinent to their role or department. Both methods locate the access restriction logic in the database tier, applying the restrictions every time data access is attempted from any tier, making the security system more reliable and robust.

Click through for the process. This is pretty much the same as any SQL Server-based system.

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Analyzing Dependencies in Microsoft Fabric Measures

Published 2023-10-27 by Kevin Feasel

Sandeep Pawar has an interesting library for us:

In my previous blog post, I introduced Semantic-Link, discussing its use cases and explained how it enables us to create solutions that were either not possible or not easily achievable before. In this blog post, I would like to present another powerful use case that, although possible in the past, could not be created and used seamlessly in Power BI. Allow me to introduce the MeasureMaze Python library, which helps uncover insights from a complex maze of dependencies in a Power BI semantic model using Semantic-Link and the power of network analysis.

Sandeep dives into the approach and what you get out of this library. It’s very interesting.

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