Felt fine at first, inner joins on orders and inventory tables, nothing wild.
Start by clarifying the schema and the specific business questions, then break each question into required tables, join conditions, and aggregation logic. Write queries incrementally, validating each join and aggregation step, and optimize with indexes and EXPLAIN plans.
Pro tip: Always clarify ambiguous terms like 'sales' (revenue vs. units) and confirm whether to include returns or discounts; this shows attention to detail and prevents incorrect assumptions.
Ask about table structures, relationships, and exact metrics needed (e.g., total sales, top customers). Confirm edge cases like date ranges, returns, and null handling.
Determine which tables are needed and the join keys (e.g., orders.customer_id = customers.id). Choose join types (INNER, LEFT) based on whether you need unmatched rows.
Decide on aggregate functions (SUM, COUNT, AVG) and GROUP BY columns. Use HAVING for filtering aggregated results and consider window functions for rankings.
Compose the SQL incrementally, testing each join and aggregation. Use sample data or EXPLAIN to verify correctness and performance.
Suggest indexes on join and filter columns, and discuss trade-offs between readability and performance (e.g., subqueries vs. joins).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.