Don't Code Before You Know Why — Translating Business Problems into Data Solutions
Show Notes
In this episode of the medavers podcast, I unpack the brutal jump from tidy classroom datasets to real, messy business problems. Instead of another algorithm deep-dive, I focus on the one skill that actually creates value: translation and turning vague business pain into a clear, solvable data problem.
I walk through three common failure points:
The Diagnosis (Execution Trap): I explain why jumping straight to models wastes time and share my go-to question: “If I give you this result tomorrow, what will you change?” If they hesitate, it’s a red flag.
The Metrics (Compass): I show how to pick one North Star metric that truly moves the business and how to spot vanity metrics that only look good on dashboards.
The Solution (Hammer Syndrome): I argue for pragmatic engineering — simple rules often deliver 80% of the value for 1% of the effort and when heavy AI is unnecessary.
Who this episode is for: junior data practitioners, product managers, and anyone who wants their data work to actually matter.
What you’ll leave with: a short, practical checklist to diagnose projects, choose the right metric, and pick the simplest effective solution.