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Month: September 2024

A Reminder for Server Consistency

Chad Callihan resolves an issue:

I connected to the latest SQL Server, opened SSMS, and tried to restore from there. Sure enough, I was presented with the error:

Cannot access the specified path or file on the server. Verify that you have the necessary security privileges and that the path or file exists.

If you know that the service account can access a specific file, type in the full path for the file in the File Name control in the Locate dialog box.

Read on for the solution, which was easy enough, but serves as a reminder that having (and occasionally running!) idempotent configuration scripts can be quite useful.

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Implicit Conversions in SQL Server

Vlad Drumea explains what it means implicitly to convert:

If you’re here, you most likely know what a data type conversion is, but, in short, it’s the operation of converting a value from one data type to another.

There are two types of conversions in SQL Server:

  • explicit – which are done by explicitly applying the CAST and CONVERT functions on a column, variable, or value.
  • implicit – when CAST and CONVERT are not used explicitly, but SQL Server ends up doing the conversation behind the scenes due to two distinct data types being compared.

Read on to learn more about which types of implicit conversion are relevant for performance and what you can do instead.

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Migrating Power BI Dataflows from Gen1 to Gen2

Reza Rad talks migration:

Unfortunately, there isn’t a migration tool to convert your Power BI dataflow (gen1) to Microsoft Fabric dataflow (gen2). If you have Fabric capacity licenses, it just makes sense to do that migration because Dataflow Gen2 gives you data destinations into four destinations, which we don’t have in Dataflow Gen1. However, converting Gen1 to Gen2 isn’t that complicated. The process is explained in this blog and video.

Click through for the blog post and the video.

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Query Start Times in Query Store

Hugo Kornelis describes an issue:

I was hired by a customer who had a very annoying issue with the daily data load of their data warehouse. The volume of data to be loaded is high and they were already struggling to finish the load before business opens. But that was not their biggest issue. The biggest problem, the real pain point that they hired me for, is that at unpredictable moments, the load would run much longer than normal, pushing it well into business hours. They wanted me to find out what caused those irregular delays, and find a way to stop them from happening.

Read on to learn more about the issue itself, as well as a discrepancy in what Query Store showed. Hugo also points out that the quick-and-easy solution may not be the right solution.

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Building a Test Data Generator for PostgreSQL

Mika Sutinen builds some data:

I recently had a project where I needed quickly to generate some realistic looking test data to PostgreSQL database. While I often like to go for ready-made solutions, this felt like a good opportunity to stretch my coding muscles and develop it myself. Moreover, this seemed like a fun puzzle to solve, and I could probably use the same solution later on elsewhere.

Click through for a description of the generator, as well as a link to Mika’s GitHub repo. Taking a quick peek at it, it does appear that you could probably use this for other data platforms like SQL Server with very limited modification.

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Myths and Reality of Copilot for Power BI

Kurt Buhler puts together an essay:

However, recent months reveal rising skepticism, concern and possibly even disillusionment with generative AI tools, both from investors (especially from investors) and from the public. Despite the massive investment, enthusiasm, and promotion, these tools seem to be seeing limited adoption and aren’t yet showing the measurable value that fulfills their promises. And yet, paradoxically, many professionals will agree anecdotally that they use generative AI tools regularly, and that these tools seem to help them be more productive in certain tasks. Furthermore, there are concrete success stories where generative AI is bringing value, such as the models like the latest versions of Alphafold (from Google) and ESMfold (from Meta) that aid in protein folding for pharmaceutical companies more effectively find potential new drug candidates. So, who are these tools for, what problems do they solve, and how can we use them effectively? This is too big of a topic for even Bink and Bonk the Data Goblins to solve, so let’s narrow the focus, a bit.

This is a must-read, and Kurt even provides a de-goblinified PDF version for management.

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Context Transition in DAX

Marco Russo and Alberto Ferrari draw on a cocktail napkin:

In previous articles, we introduced a visual approach to describing two important DAX concepts: the filter context and the row context. This article completes this short series by describing the context transition using a graphical visualization.

This article provides a different perspective on the context transition already covered in other articles: you should read them to get more insights on this important concept for DAX.

Read on to see how it all fits together.

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Reading Always Encrypted Data in Power BI

Rod Edwards wants to make use of encrypted data:

This is where things start to get a little more interesting compared to Pt1, as now we have a different application in the mix for reading the data. So how can that application retrieve the key needed to successfully decrypt?

Read on to see how it all works. There are a lot of working parts here, though some of it pertains to using an on-premises gateway versus Always Encrypted as such, so you get even more bang for your buck.

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