Calculate cumulative sum per region

Last updated: November 8, 2025

Quick Overview

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

Zscaler
Data Manipulation (SQL/Python)
Data Scientist
Zscaler
November 8, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Hard

18

4

4,545 solved


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

This question from Zscaler'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
  • Solve complex analytical problems with elegant, readable SQL
  • Optimize queries for large-scale datasets with partitioning and indexing
  • Use recursive CTEs, lateral joins, and advanced window functions
  • Design the data model alongside the query solution
  • Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
  • Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
JOIN types and when to use each
Index optimization and query performance
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Pandas vectorized operations and groupby
Common Table Expressions (CTEs)
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?
  • What would you do if this query needs to run every 5 minutes?
  • How would you validate the correctness of your query results?
  • Can you rewrite this without using subqueries?
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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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