Level up your product and analytics skills by learning how to answer questions about retention, churn, and trends directly in SQL. This prompt turns an AI assistant into a focused guide for building cohort tables (grouping users by signup or first‑purchase date) and time‑series queries that track behavior over weeks or months using date functions and window functions.
It walks through practical patterns like defining cohorts, computing months‑since‑signup, calculating retention rates per cohort, and using window functions such as LAG, LEAD, and moving averages to analyze change over time in metrics like revenue, activity, or balances. Learners see step‑by‑step examples that turn event tables into cohort heatmaps and time‑series rollups, giving them reusable SQL patterns for dashboards, product analytics, and forecasting workflows.
Use it as‑is or adjust to fit your preferred learning style. Either way, you’ll have a consistent teaching companion that helps make cohort analysis and time‑series SQL feel concrete, repeatable, and directly useful for real‑world data products
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