Calculate average revenue per date

Last updated: January 3, 2026

Quick Overview

Write a query to compute average revenue grouped by region, handling edge cases like nulls and duplicates.

Adobe
Data Manipulation (SQL/Python)
Data Scientist
Adobe
January 3, 2026
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Easy

15

11

2,017 solved


Write a query to compute average revenue grouped by region, handling edge cases like nulls and duplicates.

This question from Adobe's Technical 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
  • Write syntactically correct SQL with proper JOIN and WHERE clauses
  • Use GROUP BY and aggregate functions appropriately
  • Handle NULL values correctly in your queries
  • Explain the query execution plan at a high level
Key Topics to Cover
Subqueries and correlated subqueries
Data cleaning and transformation
Pandas vectorized operations and groupby
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
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 this if the data was spread across multiple databases?
  • How would you handle slowly changing dimensions in this scenario?
  • What would you do if this query needs to run every 5 minutes?
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Sample Answer
Problem Understanding

The task requires calculating the average revenue per date, grouped by region. The relevant data likely resides in a table that includes columns for date, region, and revenue. We need to ensure ...

Approach
  1. Identify Relevant Data: Determine the table that contains the date, region, and revenue fields.
  2. Handle NULLs: Use a filtering condition to exclude rows where revenue is NULL. 3...

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