Join users and orders to find conversion rate

Last updated: January 15, 2026

Quick Overview

Write a query joining users and sessions to produce the combined conversion rate.

Brex

Data Manipulation (SQL/Python)

Data Scientist

Brex

January 15, 2026

Data Scientist

Take-home Project

Data Manipulation (SQL/Python)

Medium

144

3,314 solved

Write a query joining users and sessions to produce the combined conversion rate.

This question from Brex's Take-home Project tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.

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

JOIN types and when to use each

Date/time manipulation

Common Table Expressions (CTEs)

Window functions (ROW_NUMBER, RANK, LAG, LEAD)

Index optimization and query performance

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 validate the correctness of your query results?
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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Practice SQL Problems

Sample Answer

Problem Understanding

We need to analyze the conversion rate of users who have made purchases (orders) based on their sessions. The relevant data involves two tables: users and orders. The users table contains user d...

Approach

Identify Relevant Data: Extract necessary fields from both users and orders tables. For users, we will need user_id, and for orders, we will need user_id and the order timestamp. 2....

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