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Day: September 8, 2026

When Ints Overflow

Aaron Bertrand hits an outage in both directions:

The Stack Overflow database has a long lineage, and a lot more warts than what’s exposed in Stack Exchange Data Explorer (SEDE). Many of the core tables were created a decade before I joined the staff in 2021, and they grew far larger than could have been envisioned back then.

One of those tables is UserHistory. This table uses an identity column as the clustered index and primary key, and records all kinds of information about each user’s activity on the site. From changing your profile picture, to earning a new privilege, to changing a preference, to something as simple as logging in or out. Each event generates at least one new row in UserHistory. At peak popularity, this table would grow quite quickly and, as the application became more complex, more and more categories of activity and state would get written there.

Click through for the story of an outage, and then another outage with a very similar shape.

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DBAs as Cost Centers

Warwick Rudd lays out the bitter truth:

That has been the problem for as long as there have been database administrators, and I don’t think we’ve ever really solved it.

Here’s what I mean. A DBA doing the job properly produces nothing you can see. The environment is up. The queries return. Nobody rings anybody at two in the morning. And because nothing appears to be happening, the people looking after it start to look like a line of cost with nothing attached to it.

In the traditional sense of how businesses think about this, they’re right. Nothing a DBA does makes money. What a DBA does is save money, which is a much harder thing to put in front of a board.

Warwick’s post moves in the direction of managed services. I’d move in the direction of understanding and vocalizing the benefits you bring to the table as a DBA.

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Scatter and Sampling in Power BI Core vs Deneb

Kerry Kolosko shows some comparisons:

In almost a decade of building Power BI reports, a common blind spot I still see from colleagues regards data point limits in core visuals — largely unnoticed until someone maps their data and finds entire regions are missing.

Compare the following lasagne plot created using a Power BI core visual scatterplot with one created using a Power BI custom visual (Deneb).

Click through for the difference. The more I see Deneb, the more impressed I am with it. I’ve seen people do some wild things with it while still working just fine in Power BI. There’s even compatibility with Power BI Report Server, if you can believe it.

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Dealing with Outages

Jeff Taylor tells a pair of stories:

It was a normal day at the start, checking on the servers, responding to email, then all of a sudden the office went dark and silent…we had just lost power!

Everyone started stirring and then getting up, checking that our phone system was on backup power, and someone called the power company to report it and get a status of when the power would be back on.

Extreme heat, smoke, and servers are not a great combination.

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Implementing SCD Type 2 in Microsoft Fabric

Nikola Ilic reminds us that the Kimball model is alive and well:

Slowly Changing Dimensions (SCD) are one of the fundamental concepts in dimensional modeling. If you are not sure what dimensional modeling is, I suggest you first check the series of articles I wrote on data modeling some time ago.

And, when it comes to SCD in particular, SCD Type 2 is rightly considered “the queen” of the SCDs for analytical workloads. Without going into details (since the main goal of this article is to show you HOW to implement the SCD Type 2 in Microsoft Fabric), I’ll just briefly introduce the general concept behind the SCD Type 2.

Click through for a primer and examples in the warehouse and lakehouse.

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Azure Databricks and Power BI Storage Modes

Chris Webb makes a choice:

In case you haven’t already seen the blog post on the Power BI blog or the discussion on LinkedIn, we at Microsoft published a new white paper last week to help you decide which storage mode to use when you’re using Power BI to create semantic models and reports on data stored in Azure Databricks. You can find the announcement and the link to the paper here.

Click through for Chris’s thoughts and check out the whitepaper.

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