← Capital One Interview Insights
The no-window-functions constraint is what got me.
First, use a single CTE to compute total delivered revenue per region, category, and month (filtering to August 2025 and delivered orders). Then, in the main query, join that CTE to a subquery that finds the maximum revenue per region, and use a tie-breaker (lexicographically smallest category) to select the top category per region.
Pro tip: When breaking ties, use a window function alternative like ROW_NUMBER() with ORDER BY revenue DESC, category ASC—but since window functions are disallowed, you can achieve the same with a correlated subquery or a self-join on the aggregated CTE, ensuring deterministic results.
Identify the relevant tables (customers, orders, order_items, products) and the join keys. Clarify that revenue = qty * unit_price, only delivered orders, and filter to August 2025.
Write a CTE that joins orders, order_items, and products, filters for delivered orders in August 2025, and computes SUM(qty * unit_price) grouped by region and category.
In the main query, use a subquery to get the max total_revenue for each region from the CTE, then join back to the CTE to get the category(ies) that achieve that max.
If multiple categories tie for max revenue in a region, pick the lexicographically smallest category. Use ORDER BY region, category and a LIMIT 1 per region (e.g., via a correlated subquery or DISTINCT ON in some dialects) to return one row per region.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.