Calculate DAU/MAU ratio per product

Last updated: January 2, 2026

Quick Overview

Write a query to compute DAU/MAU ratio grouped by user, handling edge cases like nulls and duplicates.

xAI
Data Manipulation (SQL/Python)
Data Scientist
xAI
January 2, 2026
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

44

2

2,650 solved


Write a query to compute DAU/MAU ratio grouped by user, handling edge cases like nulls and duplicates.

This question from xAI's Phone Screen 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
Pandas vectorized operations and groupby
Data cleaning and transformation
Date/time manipulation
Index optimization and query performance
Subqueries and correlated subqueries
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
  • What indexes would you create to support this query?
  • Can you rewrite this without using subqueries?
  • What would you do if this query needs to run every 5 minutes?
Sharpen Your Skills on Codemia

Practice similar problems with our interactive workspace, get AI feedback, and track your progress.

Practice SQL Problems
Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


Submit Your Answer
Markdown supported

Related Questions