Calculate average revenue per user

Last updated: August 19, 2025

Quick Overview

Write a query to compute average revenue grouped by region, handling edge cases like nulls and duplicates.

Visa
Data Manipulation (SQL/Python)
Data Scientist
Visa
August 19, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium

105

0

3,728 solved


Write a query to compute average revenue grouped by region, handling edge cases like nulls and duplicates.

Visa 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
  • 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
Pandas vectorized operations and groupby
Date/time manipulation
Index optimization and query performance
Aggregate functions and GROUP BY
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
  • What would you do if this query needs to run every 5 minutes?
  • How would you optimize this query for a table with 100 million rows?
  • Can you rewrite this without using subqueries?
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