Database migration scripts are a popular and effective way to check database code into version control.
In this post I describe the most common features of popular migration script runners for database code deployment, along with the top gotchas that folks hit when versioning their database code with migrations.
There are lots of jobs for data folks. In this episode, I discuss three hot job titles: Database Administrator (DBA), Database Reliability Engineer (DBRE), and Data Engineer (DE).
Sometimes people are annoyed by the term ‘Database DevOps’. Why not call it simply ‘DevOps’? After all, Database DevOps follows the same core principles.
The answer is simple: implementing DevOps is tricky by itself, but most teams are set up to fail when it comes to implementing DevOps for databases. This makes it worth defining as a specialization.
Twenty years ago, database administrators (DBAs) were the primary career path when it came to specializing in data management.
Much has changed: development patterns transformed from Waterfall to Agile, DevOps drives automation and shared ownership of code, and cloud services have made many more kinds of PaaS databases, data lakes, and data lakehouses available to organizations of all sizes.
These changes have introduced new and varied career paths for data folks which have different emphases on skill sets. In this post, I talk through the commonalities and differences between DBAs, Database Reliability Engineers (DBREs), and Data Engineers (DEs). Whether you’re a hiring manager or data professional, it’s worth knowing about these roles.
Have you ever received advice that was technically correct, but it was too hard to understand?
I think of this as “accidental bad advice,” because it can lead to confusion and bad outcomes. There’s a LOT of accidental bad advice out there on index maintenance for SQL Server and cloud versions like Azure SQL, even in the official documentation.
In this post I’m answering a common index maintenance question, and we’re going to keep it simple.
I was doing a bit of data analysis, and the resulting numbers didn’t quite add up.
I double-checked my queries. Had I goofed in my sql? Nope. Next, I looked into if some of the data was in an inconsistent state.
What I found was worse than what I’d imagined. As a data person, it made me feel sad and icky.
I’m thrilled to be heading to Seattle in November for the PASS Data Community Summit. My favorite things about the PASS Summit are making connections, learning from folks, broading my horizons, helping build a vibrant community, and teaching.
Teaching is a great privilege, and I’m excited to be giving both a pre-conference session and a regular session. I chat about the sessions in this ~4 minute video.
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