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Day: July 21, 2023

The Basics of Fact-Dimensional Modeling

Nikola Ilic gives us a primer on Kimball-style fact and dimensional modeling:

Before we come up to explain why dimensional modelling is named like that – dimensional, let’s first take a brief tour through some history lessons. In 1996, a man called Ralph Kimball published a book “The Data Warehouse Toolkit”, which is still considered a dimensional modelling “Bible”. In his book, Kimball introduced a completely new approach to modelling data for analytical workloads, the so-called “bottom-up” approach. The focus is on identifying key business processes within the organization and modelling these first, before introducing additional business processes.

This is a really good overview of the topic, though I’m saddened that “dimensional bus matrix” didn’t make the cut of things to discuss. Mostly because I like the name “dimensional bus matrix.”

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Updates to sp_QuickieStore and sp_PressureDetector

Erik Darling has been busy. FIrst, sp_QuickieStore:

The first thing on the list that I want to talk about is the ability to cycle through all databases that have Query Store enabled.

If you have a lot of databases with it turned on, it can be a real hassle to go through them all looking for doodads to diddle.

Now you can just do this:

Next, sp_PressureDetector:

I added  high-level disk metrics similar to what’s available in other popular scripts to mine. Why? Sometimes it’s worth looking at, to prove you should add more memory to a server so you’re less reliant on disk.

Especially in the cloud, where everything is an absolute hellscape of garbage performance that’s really expensive.

Click through for both sets of updates and thank Erik for his willingness to give so much to the community.

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Power BI: Git Integration vs Deployment Pipelines

Marc Lelijveld notes a chemical reaction:

Together with the introduction of Microsoft Fabric a long-awaited feature for Power BI also became available. Git integration now allows us to connect your workspace to a git repository to sync the meta data from your Power BI dataset and report between the workspace and the repository.

At the same time, Power BI deployment pipelines are around. The pipelines help you to move content between workspaces from Development to Test and finally to Production. The question that arises, when to use what? And how do they complement each other, or maybe even clash with each other?

Read on for Marc’s thoughts across these two topics.

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Connecting a SQL Server Instance to Azure Arc

Deepthi Goguri has a guide:

When you install SQL Server 2022 through the GUI, you will see an option in the features “SQL Server Extention for Azure”

This is more of a “how” than a “why.” Azure Arc-enabled SQL Server instances let you use Azure’s control plane (their graphs and some configuration options) to manage SQL Server instances, regardless of whether they’re actually in Azure or on-premises. That way, a DBA with one foot in both camps can have a consistent administrative experience for things like inventorying SQL Server instances.

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