Calculate churn rate per user
Last updated: March 8, 2026
Quick Overview
Write a query to compute churn rate grouped by user, handling edge cases like nulls and duplicates.
OpenAI
March 8, 2026108
6
4,369 solved
Write a query to compute churn rate grouped by user, handling edge cases like nulls and duplicates.
This question from OpenAI's Take-home Project tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.
What the Interviewer Expects
- Write syntactically correct SQL with proper JOIN and WHERE clauses
- Use GROUP BY and aggregate functions appropriately
- Handle NULL values correctly in your queries
- Explain the query execution plan at a high level
Key Topics to Cover
How to Approach This
- Clarify the schema and expected output format before writing queries.
- Use CTEs (WITH clauses) to break complex queries into readable steps.
- Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
- Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
- For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
- How would you validate the correctness of your query results?
- What would you do if this query needs to run every 5 minutes?
- Can you rewrite this without using subqueries?
- How would you handle slowly changing dimensions in this scenario?
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