Join orders and products to find conversion rate

Last updated: March 29, 2026

Quick Overview

Write a query joining orders and clicks to produce the combined conversion rate.

MongoDB
Data Manipulation (SQL/Python)
Data Scientist
MongoDB
March 29, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

0

11

1,349 solved


Write a query joining orders and clicks to produce the combined conversion rate.

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

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
Aggregate functions and GROUP BY
Common Table Expressions (CTEs)
Subqueries and correlated subqueries
NULL handling and COALESCE
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Pandas vectorized operations and groupby
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?
  • How would you validate the correctness of your query results?
  • What indexes would you create to support this query?
  • How would you handle this if the data was spread across multiple databases?
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