Most data problems do not begin with a tidy table. They begin with a question, a few partial sources, and a suspicion that something important is hidden in the gaps.
This is a sample post, included to demonstrate the publishing workflow. Replace it with your first article before launch.
Start with the decision
Before choosing a model, scraper, or dashboard, ask what someone needs to decide differently. That question establishes the useful unit of analysis and reveals which omissions matter.
Make provenance part of the work
Keep a record of where each important field came from, when it was collected, and what transformations were applied. Provenance is not paperwork after the fact; it is what makes a tool credible when the data is incomplete.
Build the smallest useful view
The first useful output is often a notebook, a short research memo, or a narrow prototype. Let it teach you what the durable system needs to be.