Join transactions and sessions to find churn rate

Last updated: August 28, 2025

Quick Overview

Write a query joining transactions and messages to produce the combined churn rate.

Meta
Data Manipulation (SQL/Python)
Data Scientist
Meta
August 28, 2025
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Medium

9

12

164 solved


Write a query joining transactions and messages to produce the combined churn rate.

Meta asks this during the Take-home Project 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
Common Table Expressions (CTEs)
Aggregate functions and GROUP BY
Index optimization and query performance
JOIN types and when to use each
Date/time manipulation
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
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 handle this if the data was spread across multiple databases?
  • What indexes would you create to support this query?
  • How would you validate the correctness of your query results?
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