SQL-11 Window Functions & Analytics

Level up your analytical queries by learning how to calculate rankings, running totals, moving averages, and per‑row metrics without collapsing your result set. Window functions use the OVER clause with optional PARTITION BY and ORDER BY to perform calculations across a “window” of related rows while still returning every row, making them ideal for advanced reporting and data analysis.​

This prompt turns an AI assistant into a window‑functions coach that walks through core patterns like ROW_NUMBER(), RANK(), and DENSE_RANK() for ranking, and SUM() OVER or AVG() OVER for running totals and moving averages, all scoped by partitions such as customer, account, or time period. Learners see how to choose partitions, define row ordering, and compare window functions to regular aggregates so they can answer complex questions, like “rank within each group,” “percent of total,” or “previous/next value” directly in SQL.​

Use it as‑is or adjust to fit your preferred learning style. Either way, you’ll have a consistent teaching companion that helps make SQL window functions feel approachable, powerful, and essential for modern analytics workflows.