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Month: July 2024

Comparing Pie and Waffle Charts

Rita Fainshtein makes waffles:

Why is it more challenging to get an accurate answer from pie/donut charts and why do we feel less confident trying to read them?

The main reason is the difficulty in calculating the areas of the pie slices/lengths of the donut arcs.

This is much more challenging and less confident than comparing the areas of rectangular shapes.

Rita takes a look at the waffle chart custom visual available for Power BI and then builds something custom fit for the task.

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Testing GitHub Support in Microsoft Fabric

Kevin Chant gives it a try:

By the end of this post, you will see the results of my initial tests. Along the way I share plenty of links and some advice.

If you need help with any jargon used in this post, you can read my other post. Which is a Microsoft Fabric Git integration jargon guide for Fabricators.

One key point I want to highlight is that the GitHub support for Microsoft Fabric Git integration is currently in preview and the contents of this post are subject to change.

It’s been a long time coming, that’s for sure.

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Using Powershell to Browse Azure Capabilities

Kay Sauter does some digging:

In a nutshell, Azure follows a structure called the Azure Resource Manager (ARM). Unfortunately, ARM is not human-readable, so you need to a tool to be efficient in using it. There are quite some tools available, and from Microsoft, there is Azure Bicep, Azure CLI and Azure PowerShell. Since I have done some DBA stuff in the past, and I am a fan of dbatools (created by the team here), I find PowerShell the most convenient tool to use and suspect that many will see it the same way if they are using dbatools.

Click through for the post. As of right now, the images are broken, but if you open them in new tabs and remove the extraneous “browsing-azure-with-powershell/” in the URL, you’ll be able to see those images.

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Color and Power BI Themes

Allison Kennedy talks color in Power BI:

Being a good data storyteller means using all the tools at your disposal. This includes color. It is important to note that I’m not advocating the use of color only in your reports – you need to ensure that there is another method to discern what’s going on with the data for those in your audience who might be colorblind. But that doesn’t mean we can’t play around with color and use it to add meaning to our reports. 

Most people I know would agree that GREEN means ‘Good’ and RED means ‘Bad’. But colors can be very personal. For example, my favorite color is BLUE and it was also the color I chose for my math notebooks throughout school. (Yes, math was my favorite subject – I guess it’s no surprise I ended up in a career that works so much with data.) 

In addition to personal meaning of colors, there can also be cultural meanings around individual colors, and that can shape how individuals view a given color. Grace Fussell has one of my favorite articles on the topic.

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Filestream and Availability Groups

Chad Callihan kicks a hornets’ nest:

Migrating databases to new servers and configuring them for availability groups can be a complex process. It can be more complex depending on what type of sneaky features are in use by the databases being migrated. I encountered an interesting issue migrating a database that had been setup to use FILESTREAM and wanted to show the steps I took to identify and resolve it.

Read on for the issue and what happened. It was a small thing overall, but the kind of small thing that can eat up the better part of a day if you’re not aware of it.

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Using the fast_regression() Method in tidyAML

Steven Sanderson says, It’s my regression and I want it NOW:

If you’ve ever faced the daunting task of setting up multiple regression models in R, you’ll appreciate the convenience and efficiency that tidyAML brings to the table. Today, we’re diving into one of its standout functions: fast_regression(). This function is designed to streamline the regression modeling process, allowing you to quickly create and evaluate a variety of model specifications with minimal code.

Read on to see how the function works.

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Polymorphism in Python

Rajendrra Gupta talks object-orientation:

Polymorphism is a popular term in object-oriented programming (OOP) languages. An object can take multiple forms in different ways in polymorphism. For example, a woman takes different roles in her daily life, such as wife, professional, athlete, mother, and daughter, as the diagram below depicts:

Polymorphism isn’t a particularly difficult topic to understand, though because of the way that different languages implement the idea in subtly different ways, it’s good to know what you’re able to do in your language of choice.

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Row Pattern Recognition in PostgreSQL

Tatsuo Ishii makes me jealous:

Row pattern recognition (RPR) is a feature defined in the SQL standard. It allows to search for a sequence of rows by pattern.  Since I am working on this feature for PostgreSQL, I would like to give a brief introduction to RPR.

This is something I’ve wanted to see in SQL Server for the past few years. It’s not something people might use every day, but it solves a particular class of problem extremely well.

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Target Platform Error Deploying DACPAC to Azure SQL DB

Kunal Rathi troubleshoots an issue:

While deploying a DACPAC project to Azure SQL database using Azure DevOps, you may come across ‘A project which specifies SQL Server 2022 as the target platform cannot be published to Azure SQL Database v12.’ error. In this article, we will see how to fix this issue.

There are plenty of errors in Microsoft products that make little to no sense. This is, by contrast, a rather straightforward one, and Kunal shows how to resolve it.

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Reading Pipe-Delimited Files in SSIS

Greg Low does a bit of parsing:

There was a question on the Q&A forums today, asking how to read data using SSIS, when it’s in this format:

|Col1| |Col2|Col3|Col|
|101| |A|21|DC|

One of the concerns was that there was a leading pipe. This is not a problem. When you have data like that, and you set | as the delimiter, because there are 6 delimiters, then there are 7 columns output. 

Read on for Greg’s answer. This is a big part of why I recommend people to use Parquet (or ORC, if you’re an iconoclast like I am): not needing to deal with whatever silly, arbitrary file formats people come up with.

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