Series
Data Modeling
Modeling decisions are the ones you live with longest, because every metric downstream inherits them. This series covers slowly changing dimensions, then the modeling mistakes that quietly corrupt metrics.
2 posts
Slowly Changing Dimensions, Actually Explained
Slowly Changing Dimensions get taught as trivia: Type 1 overwrites, Type 2 keeps history, Type 3 keeps the previous value, and so on. Memorizing the list misses the only thing that matters - which version of a dimension your fact rows join to when someone asks 'what was revenue by region last quarter.' Get that wrong and your dashboard reports a number that was never true. This is SCD framed around that question, with a free playground that lets you replay a change timeline and watch facts attach to the right (or wrong) version.
Read more →7 Data Modeling Mistakes That Silently Corrupt Your Metrics
The worst data modeling bugs don't throw. The query parses, the dashboard renders, the number has six significant digits and looks confident, and it's wrong. Revenue doubles because a join fanned out. Cash is off by $84M because a balance got summed across days. Two dashboards disagree by 3 points and a board meeting stalls. None of these are SQL typos - they're modeling decisions that were wrong from the start and only surface at reconciliation. This is a production field guide to the big ones: what the symptom looks like, why it happens, and the exact fix for each.
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