Design and develop database solutions: Review

The T-SQL syntax for a stored procedure just sat there on the screen. I get what it is in theory—a saved chunk of SQL code. But the path just listed out the syntax and moved on. There was no 'here’s a situation where this saves your team 10 hours a week,' or 'if you see your engineers doing X, ask if a trigger is a better way.' It was pure technical description, like reading a car manual for a single part without knowing how the engine works.

My goal wasn't to write T-SQL myself. I just wanted to understand the building blocks well enough to have intelligent conversations with the data team about tradeoffs. Why choose a managed instance over a standard SQL database? What's the real-world difference between a view and a materialized view in terms of performance and cost? This path tells you they exist but doesn't give you the mental model to reason about them. It's a vocabulary list, not a strategy guide.

The AI module with GitHub Copilot was the most interesting bit, probably because it was the most concrete. Watching it generate code from a plain-English comment is exactly the kind of thing I can see impacting our team's workflow. But that was one small part of a 7-hour slog through syntax diagrams. The whole thing felt like seven different product docs stitched together, all assuming I already cared about the technical details.