Calculate average revenue per user

Last updated: February 3, 2026

Quick Overview

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

Coinbase

Data Manipulation (SQL/Python)

Data Scientist

Coinbase

February 3, 2026

Data Scientist

Phone Screen

Data Manipulation (SQL/Python)

Hard

1,496 solved

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

Data manipulation questions at Coinbase test your ability to work with real-world datasets. This Phone Screen question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.

What the Interviewer Expects

Solve complex analytical problems with elegant, readable SQL
Optimize queries for large-scale datasets with partitioning and indexing
Use recursive CTEs, lateral joins, and advanced window functions
Design the data model alongside the query solution
Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
Consider the operational aspects: query scheduling, incremental processing

Key Topics to Cover

Date/time manipulation

Common Table Expressions (CTEs)

Subqueries and correlated subqueries

Index optimization and query performance

JOIN types and when to use each

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

Can you rewrite this without using subqueries?
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?

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Sample Answer

Problem Understanding

To calculate the average revenue per user grouped by region, we need to consider a dataset that includes user revenue data and their corresponding regions. The query should handle potential edge cases...

Approach

Identify the Relevant Tables: Assume we have a users table containing user information, including user_id, region, and a revenues table with user_id, revenue, and transaction_date...

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