Calculate churn rate per region

Last updated: March 4, 2026

Quick Overview

Write a query to compute churn rate grouped by date, handling edge cases like nulls and duplicates.

Coinbase
Data Manipulation (SQL/Python)
Data Scientist
Coinbase
March 4, 2026
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Easy

129

7

2,276 solved


Write a query to compute churn rate grouped by date, handling edge cases like nulls and duplicates.

Coinbase asks this during the Technical Screen 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
  • 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
Aggregate functions and GROUP BY
Subqueries and correlated subqueries
Index optimization and query performance
JOIN types and when to use each
Date/time manipulation
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 indexes would you create to support this query?
  • How would you validate the correctness of your query results?
Sharpen Your Skills on Codemia

Practice similar problems with our interactive workspace, get AI feedback, and track your progress.

Practice SQL Problems
Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


Submit Your Answer
Markdown supported

Related Questions