Data

You ever stare at a dataset so clean it almost makes you suspicious? I was working on this internal report, years ago, a clean pull, plenty of rows, the kind of structure that makes your inner developer exhale. The task was simple: find out which section of a local news site was most engaging. Click-through rate, time on page, bounce rate, the usual suspects. And the numbers spoke. Loudly. “Pets” crushed “Politics.” “Recipes” danced circles around “Real Estate.” The graph basically threw glitter at “Pets.” So I built the dashboard, shared it, and our PM lit up. “Let’s double down on Pet content,” he said. “People love it!” ...

You know that moment when you write a query, and it doesn’t return what you expected? Not because it’s broken, the syntax is fine, but because it exposes that your understanding of the data, or the world behind it, is off. That happened to me last week. I was trying to build a clean report from a dataset I thought I knew well. I wrote a query, confident, structured, even elegant, and ran it. The result was almost right, which is worse than completely wrong. That’s when I realized: every SQL query is a little philosophical act. It’s a belief made code. ...