Write a query to find DAU/MAU ratio from events
Last updated: August 3, 2025
Quick Overview
Write a SQL query to calculate DAU/MAU ratio from the events table, considering nulls and duplicates.
Workday
Data Manipulation (SQL/Python)
Data Scientist
Workday
August 3, 2025Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium
232
8
4,364 solved
Write a SQL query to calculate DAU/MAU ratio from the events table, considering nulls and duplicates.
This question from Workday's Onsite 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
Index optimization and query performance
Common Table Expressions (CTEs)
Subqueries and correlated subqueries
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
NULL handling and COALESCE
Date/time manipulation
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 handle slowly changing dimensions in this scenario?
- How would you validate the correctness of your query results?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this problem, we need to calculate the Daily Active Users (DAU) and Monthly Active Users (MAU) from an 'events' table. Each record in the events table represents an interaction by a user, which we ...
Approach
- Extract Unique Users: Use a Common Table Expression (CTE) to first extract unique active users per day (DAU). This can be achieved by grouping by the date and user ID, ensuring we only count di...
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