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, 2025Data 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
- 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 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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Practice SQL ProblemsSample Answer
Problem Understanding
In this scenario, we need to analyze user churn by joining two tables: 'transactions' and 'sessions'. The 'transactions' table contains records of user purchases, while the 'sessions' table logs user ...
Approach
- Identify Relevant Data: Determine the key columns in both tables. We will need user ID, transaction date from 'transactions', and session date from 'sessions'.
- Define Churn Criteria: Se...
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