Start by clarifying the schema: identify the revenue column, the department column, and the join path between them. Then write a query that groups by department and sums revenue, using appropriate joins and handling NULLs. Finally, consider edge cases like departments with no revenue and discuss performance implications.
Pro tip: At Amazon, always clarify ambiguous terms like 'revenue' (gross vs net, refunds, currency) and mention indexing or partitioning strategies for large datasets. This shows you think about data quality and scalability.
Ask about the tables involved, the revenue column, and how departments are linked. Confirm whether revenue should be net of returns or discounts.
Determine how to join the revenue table to the department table, possibly through intermediate tables. Consider using LEFT JOIN to include departments with no revenue.
Use GROUP BY on department and SUM on revenue. Handle NULLs with COALESCE or IFNULL to show 0 for departments with no revenue.
Mention departments with no sales, multiple revenue streams, and how indexes or partitioning can optimize the query for large datasets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.