This article looks at one of the killers of performance at scale, SELECT *.
Build scalable data pipelines by pushing transformations into SQL and keeping Python focused on analysis.
Steve notes that building great software isn't easy, and there is a lot of work that goes into this. Even in today's age of AI.
In Part 2 of this series we learn how OUTER APPLY can be used in your queries to return data, even when there are no matches between tables.
SQL Server Availability Groups are great for DR and HA purposes. In this article, we look at how to setup a SQL Server 2025 Availability Group using the features in SQL Server Management Studio.
See how a small local model performs on some SQL tasks. This shows how Ollama can run a model on your laptop.
Today Steve notes that he often compares the work a computer does to what might happen if the same actions occurred in the physical world.
The article covers four connected areas: over-privileged database users, msdb and SQL Server Agent exposure, privileged maintenance jobs, and trigger-based permission hijacking.
Managing incidents as a DBA /DB manager and some of the key things you should be doing.
By Steve Jones
I caught this interesting item over on Pinal Dave’s blog: Eleven Interview Questions that...
By Hemantgiri
I use color-coded connections in SSMS to distinguish Production, Pre-Production, UAT, and Development. But...
Comments posted to this topic are about the item Building a SQL Server Fleet...
Comments posted to this topic are about the item Smart AI Agents and Data...
Comments posted to this topic are about the item RegEx Functions IV
I have this data in a table in a SQL Server 2025 database:
EmailAddressID EmailAddress 7 [email protected] 8 [email protected]If I run this query, which row(s) are returned?
SELECT top 10 * FROM person.EmailAddress WHERE REGEXP_LIKE(EmailAddress, '^D', 'i') AND BusinessEntityID IN (7,8)See possible answers