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Author: Kevin Feasel

Measuring Promotion Impact in Power BI

Published 2025-12-19 by Kevin Feasel

Marco Russo and Alberto Ferrari take us through a scenario:

Marketing campaigns drive sales, but not all sales can be directly attributed to a specific campaign. A customer might see a promotion and later purchase the product without using any discount code or campaign link. How do you measure this broader influence? This article presents data modeling and DAX measures to analyze campaign effectiveness by separating attributed sales (transactions for which we can clearly identify the one campaign that generated the sale) from influenced sales (all sales of products participating in one or more campaigns, regardless of whether the sale can be attributed to one exact campaign). The solution includes several measures using a many-to-many relationship between products and campaigns, combined with dynamic CROSSFILTER manipulation, to provide a complete view of the campaign’s impact.

Read on to see how you can use DAX capabilities to build attribution measures.

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Optimized Locking in SQL Server 2025

Published 2025-12-19 by Kevin Feasel

Tomaz Kastrun continues an advent of SQL Server 2025:

Optimized locking is a new feature in SQL Server 2025. It helps to reduce lock memory as very few locks are held even for large transactions. In addition, optimized locking avoids lock escalations and can avoid certain types of deadlocks. This allows more concurrent access to the table.

Read on to understand what its purpose is and see a demo of it in action.

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The Year in SQL

Published 2025-12-19 by Kevin Feasel

Anna Hoffman writes up the year in SQL:

For the FIFTH(!!) year in a row (my heart is warm with the number, I love SQL and #SQLfamily, and time is flying), I am sharing my annual Year in Review blog with all the SQL Server, Azure SQL and SQL database in Fabric news this year. Of course, you can catch weekly episodes related to what’s new and diving deeper on the Azure SQL YouTube channel (this blog post was livestreamed there too). This year, in addition to Data Exposed (52 new episodes and over 70K views!), we saw many new series related to areas like GitHub Copilot, SSMS, VS Code, and Azure SQL Managed Instance land in the channel, in addition to Data Exposed.

Click through for plenty of links around SQL Server 2025, Azure SQL, and Fabric SQL Database.

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Multi-Column Indexes in Pandas DataFrames

Published 2025-12-18 by Kevin Feasel

Brendan Tierney has a multi-part key:

It’s a little annoying when an API changes the structure of the data it returns and you end up with your code breaking. In my case, I experienced it when a dataframe having a single column index went to having a multi-column index. This was a new experience for me, at this time, as I hadn’t really come across it before. The following illustrates one particular case similar (not the same) that you might encounter. In this test/demo scenario I’ll be using the yfinance API to illustrate how you can remove the multi-column index and go back to having a single column index.

In this case, Brendan essentially builds a hierarchy and filters down to make a single key column (in this case, a date) relevant.

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Sending Messages from SQL Server 2025 to Slack

Published 2025-12-18 by Kevin Feasel

Aaron Bertrand fires off a message:

In an earlier tip, A history of accessing REST APIs and web pages from SQL Server, I talked about reaching out to external endpoints from SQL Server, including the new sys.sp_invoke_external_rest_endpoint procedure that hit the on-premises editions in SQL Server 2025. This seemed like an ideal use case to enhance our current solution for sending a message to Slack: using xp_cmdshell to call a PowerShell script that calls Invoke-RestMethod. In this tip, I’ll describe how we changed our implementation and why it is a marked improvement for us.

When I did this same thing, I ended up using CLR, as the customer I did it for used SQL Server on Azure VMs and not Azure SQL Database.

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A Security and HA Checklist for Database Application Vendors

Published 2025-12-18 by Kevin Feasel

Andreas Wolter shares a list:

As a database application vendor, the security and reliability of your software are core competitive advantages. To help reaching this goal, we have created a checklist which is meant to serve as a blueprint for designing data applications that are secure by default and resilient to failure, ensuring your customers can trust your product in demanding enterprise environments.

I think it’s a good set of criteria. And from the customer’s side, it’s easy to convert these into questions that you can ask vendors before deploying their software.

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Gaps in Identity Columns

Published 2025-12-18 by Kevin Feasel

Brent Ozar explains why there can be gaps in identity columns:

And you use that identity number for invoice numbers, or customer numbers, or whatever, and you expect that every single number will be taken up. For example, your accounting team might say, “We see order ID 1, 3, and 4 – what happened to order ID #2? Did someone take cash money from a customer, print up an invoice for them, and then delete the invoice and pocket the cash?”

Well, that might have happened. But there are all kinds of reasons why we’d have a gap in identities. One of the most common is failed or rolled-back transactions. To illustrate it, let’s start a transaction in one window:

I have a talk on applying forensic accounting techniques using SQL and Python (as well as an older version using R) and this is one of the things I bring up. In cases where you absolutely need contiguous numbers, the best I can do for you is no identity column and a stored procedure that runs in a SERIALIZED transaction isolation level, using an app lock to prevent anybody else from calling the stored procedure concurrently, taking a table lock out on the relevant table prior to doing any real work, and hard blocking everybody else until your transaction either succeeds or fails. And I’m not even 100% sure on that if you have enough concurrency to matter.

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