Calculate churn rate per region
Last updated: August 9, 2025
Quick Overview
Write a query to compute churn rate grouped by region, handling edge cases like nulls and duplicates.
Twitter/X
August 9, 2025259
6
1,951 solved
Write a query to compute churn rate grouped by region, handling edge cases like nulls and duplicates.
Twitter/X asks this during the Onsite because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.
What the Interviewer Expects
- Use advanced SQL features: window functions, CTEs, subqueries
- Write efficient queries that avoid common performance pitfalls
- Handle complex data transformations with multiple joins and aggregations
- Discuss indexing strategy and query optimization
- Address data quality issues: duplicates, missing values, outliers
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 optimize this query for a table with 100 million rows?
- What would you do if this query needs to run every 5 minutes?
- What indexes would you create to support this query?
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Practice SQL ProblemsSample Answer
Problem Understanding
To calculate the churn rate per region for Twitter/X, we need to analyze user activity data that typically consists of user IDs, their regions, and timestamps indicating when users were active or inac...
Approach
- Identify Active Users: Filter out users who have been inactive for more than 30 days based on
last_active_date. - Count Users: Count total users in each region and those who have churn...
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