Calculate retention rate per region

Last updated: January 26, 2026

Quick Overview

Write a query to compute retention rate grouped by date, handling edge cases like nulls and duplicates.

Elastic
Data Manipulation (SQL/Python)
Data Scientist
Elastic
January 26, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Easy

28

14

3,516 solved


Write a query to compute retention rate grouped by date, handling edge cases like nulls and duplicates.

Data manipulation questions at Elastic test your ability to work with real-world datasets. This Take-home Project question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.

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
Data cleaning and transformation
NULL handling and COALESCE
JOIN types and when to use each
Aggregate functions and GROUP BY
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
  • How would you handle slowly changing dimensions in this scenario?
  • How would you handle this if the data was spread across multiple databases?
  • How would you optimize this query for a table with 100 million rows?
  • How would you validate the correctness of your query results?
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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 ...


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