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
Data Manipulation (SQL/Python)
Data Scientist
Twitter/X
August 9, 2025
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

259

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
NULL handling and COALESCE
Common Table Expressions (CTEs)
Aggregate functions and GROUP BY
Data cleaning and transformation
Date/time manipulation
Index optimization and query performance
How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. 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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