Data Analysis in the Age of AI: Good, Better, Best
In the past, whenever I joined a new team or switched analytics platforms, the first week was always the same: figuring out table structures, adjusting to whatever SQL dialect the new data used, and writing throwaway queries just to understand what the data looked like. This was the job. If you were a PM who wanted to have the flexibility and reactivity that comes with pulling your own data, you accepted that a good chunk of your time would be spent on the mechanical side of analysis. Writing queries, debugging joins, building charts, formatting reports. The actual thinking about what the numbers meant often came last, squeezed into whatever time was left. ...