Join transactions and clicks to find conversion rate

Last updated: February 20, 2026

Quick Overview

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

NVIDIA
Data Manipulation (SQL/Python)
Data Scientist
NVIDIA
February 20, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Medium

9

8

4,372 solved


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

This question from NVIDIA'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
Date/time manipulation
Pandas vectorized operations and groupby
Common Table Expressions (CTEs)
JOIN types and when to use each
Aggregate functions and GROUP BY
NULL handling and COALESCE
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 handle slowly changing dimensions in this scenario?
  • What indexes would you create to support this query?
  • What would you do if this query needs to run every 5 minutes?
  • Can you rewrite this without using subqueries?
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