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, 2026Data 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
- 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 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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Practice SQL ProblemsSample Answer
Problem Understanding
In this problem, we have two key datasets: orders and clicks. The orders table contains information about completed purchases, including fields like order_id, user_id, and product_id. The ...
Approach
- Identify Unique Clicks: First, aggregate the
clickstable to get the count of unique clicks per product. UseCOUNT(DISTINCT click_id)to ensure we are counting unique interactions. - **Ide...
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