Join sessions and rides to find average revenue

Last updated: October 31, 2025

Quick Overview

Write a query joining sessions and products to produce the combined average revenue.

Splunk
Data Manipulation (SQL/Python)
Data Scientist
Splunk
October 31, 2025
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

191

6

1,966 solved


Write a query joining sessions and products to produce the combined average revenue.

This question from Splunk'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
Date/time manipulation
Common Table Expressions (CTEs)
NULL handling and COALESCE
Pandas vectorized operations and groupby
JOIN types and when to use each
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
  • Can you rewrite this without using subqueries?
  • What indexes would you create to support this query?
  • How would you validate the correctness of your query results?
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