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Curated SQL Posts

Darling Data Stored Procedure Updates

Erik Darling takes on the Royal We to announce updates:

We here at Darling Data strive to get things right the first time, but sometimes late nights and tired eyes conspire against us.

The nice thing about using these on a wide variety of SQL Servers in various states of disrepair is that bugs get spotted and sorted pretty quickly.

You can download all of the main SQL Server troubleshooting procedures I use in one convenient file.

Here’s a breakdown of changes you can find in the most recent releases!

Click through for quick changelogs for sp_QuickieStore, sp_PressureDetector, and sp_HumanEventsBlockViewer.

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SQL Server Connection Strings and Power Apps

Deborah Melkin works through a pain point in Power Apps:

Power Platform is part of the Microsoft universe of products, for lack of a better phrase. But the one thing I find interesting is that the default connectors for data in the PowerPlatform sphere is Dataverse or Sharepoint. At least, when I see people talking about PowerApps is you’re connecting to one of those two connectors for your data. (Fun fact, PowerApps solutions use Dataverse to store configurations.) One would think that SQL Server database, wherever it may live Azure or on prem, would be part of that combination, but it’s actually considered a Premium connector.

I’ve mentioned that the PowerApp I’m building is using data in a SQL Server database. This matters because the type of connector you use makes a difference as you move apps from one environment to another.

Read on for more information around environment variables, why they won’t work, and one alternative solution.

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Adding GIFs to Power BI Reports

Riqo Chaar adds a bit of motion to cards:

This article will describe the process behind adding GIFs to card visuals in Power BI. The GIFs we will create in this article will be as follows: animated arrows, looping only once, displaying the direction of movement relating to a particular value between the current period and the previous period. These GIFs work extremely well as a visual aid, highlighting key information quickly to users, without any overstimulating effect due to a single loop being used.

This article was inspired by a video from the YouTube channel, How to Power BI.

Click through for the article. I’m pretty well on the fence about this: adding GIFs is not something I would think to do, primarily because of the distraction factor. Even so, it’s still good to know that it’s possible.

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Using strsplit() with Multiple Delimiters in R

Steven Sanderson shows off some more complex string splitting scenarios in R:

In data preprocessing and text manipulation tasks, the strsplit() function in R is incredibly useful for splitting strings based on specific delimiters. However, what if you need to split a string using multiple delimiters? This is where strsplit() can really shine by allowing you to specify a regular expression that defines these delimiters. In this blog post, we’ll dive into how you can use strsplit() effectively with multiple delimiters to parse strings in your data.

Read on for two examples of complex scenarios.

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A Primer on Transactional Replication

Steve Stedman talks transactional replication:

Ensuring that your databases are synchronized across different locations with minimal delay is not just a convenience—it’s a necessity. This is where transactional replication in SQL Server shines, making it a pivotal strategy for systems that require real-time data replication with high consistency. Our latest video, “Transactional Replication in SQL Server”, dives deep into this topic, offering insights and visual walkthroughs that are invaluable for database administrators and developers.

Click through for the video and how the pieces fit together for transactional replication at a high level.

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Understanding the Delta Lake Format

Reza Rad has a new post and video combo:

Please don’t get lost in the terminology pit regarding analytics. You have probably heard of Lake Structure, Data Lake, Lakehouse, Delta Tables, and Delta Lake. They all sound the same! Of course, I am not here to talk about all of them; I am here to explain what Delta Lake is.

Delta Lake is an open-source standard for Apache Spark workloads (and a few others). It is not specific to Microsoft; other vendors are using it, too. This open-source standard format stores table data in a way that can be beneficial for many purposes.

In other words, when you create a table in a Lakehouse in Fabric, the underlying structure of files and folders for that table is stored in a structure (or we can call it format) called Delta Lake.

Read on to learn more about this open standard and how it all fits together with Microsoft Fabric.

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Data Compression and Data Type Changes

Bob Pusateri asks the important questions:

A few different times I have been asked one or more forms of the following question:

Can datatypes be changed faster with data compression enabled?

I’ve always replied that I’m pretty sure compression will help in this situation, because based on my understanding, it should. But I’ve never had any actual data to back up this belief. Until now. I recently set up a demonstration to test this, and I’m very happy to share the results.

If you want to see the results, you’re going to have to read Bob’s article.

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Power BI Model Size and Memory Usage

Chris Webb lays out the limitations:

You probably know that semantic models in Power BI can use a fixed amount of memory. This is true of all types of semantic model – Import, Direct Lake and DirectQuery – but it’s not something you usually need to worry about for DirectQuery mode. The amount of memory they can use depends on whether you’re using Shared (aka Pro) or a Premium/Fabric capacity, and if you’re using a capacity how large that capacity is. In Shared/Pro the maximum amount of memory that a semantic model can use is 1GB; if you are using a capacity then the amount of memory available for models in each SKU is documented in the table here in the Max Memory column:

Read on to learn more.

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Evenly Spacing Month Charts in ggplot2

Jameson Marriott fixes a spacing issue:

I recently noticed that ggplot2 spaces date axes literally even when grouped by month. I’ve been using ggplot2 extensively for years and I don’t remember noticing before, so this is not really a big deal, but now that I know it bugs me a lot. Take a look below.

I don’t think I had noticed this before either, though now that Jameson has pointed it out, it certainly is annoying. H/T R-Bloggers.

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Monitoring ML Models in production

Thomas Sobolik and Leopold Boudard talk model drift:

Regardless of how much effort teams put into developing, training, and evaluating ML models before they deploy, their functionality inevitably degrades over time due to several factors. Unlike with conventional applications, even subtle trends in the production environment a model operates in can radically alter its behavior. This is especially true of more advanced models that use deep learning and other non-deterministic techniques. It’s not enough to track the health and throughput of your deployed ML service alone. In order to maintain the accuracy and effectiveness of your model, you need to continuously evaluate its performance and identify regressions so that you can retrain, fine-tune, and redeploy at an optimal cadence.

In this post, we’ll discuss key metrics and strategies for monitoring the functional performance of your ML models in production […]

Click through for the article. There’s a Datadog pitch at the end, but the info is useful regardless of which tool you’re using for monitoring.

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