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Identify the top 5 customers with the highest purchases in the last quarter.

General/Othermedium0.5 min readPremium

Use window/ranking with clear assumptions. SQL (BigQuery/Snowflake): WITH quarterly AS (SELECT customer_id, SUM(amount) total FROM transactions WHERE transaction_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 3 MONTH) GROUP BY customer_id), ranked AS (SELECT customer_id, total,...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
243
questions in General/Other
Difficulty Split
151E|43M|49H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Aarete
Key Concepts Tested
bigquerypartitionsnowflakesqlwindow

Why This Question Matters

This medium-level General/Other question appears frequently in data engineering interviews at companies like Aarete. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (bigquery, partition, snowflake) will help you answer variations of this question confidently.

How to Approach This

Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.

Expert Answer
93 words

Use window/ranking with clear assumptions. SQL (BigQuery/Snowflake): WITH quarterly AS (SELECT customer_id, SUM(amount) total FROM transactions WHERE transaction_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 3 MONTH) GROUP BY customer_id), ranked AS (SELECT customer_id, total, RANK() OVER (ORDER BY total DESC) rk FROM quarterly) SELECT customer_id, total, rk FROM ranked WHERE rk <= 5. WHY RANK vs DENSE_RANK: RANK gaps on ties; DENSE_RANK is continuous—choose per business (e.g., 'exactly 5' vs 'top tier'). SCALABILITY: Index transaction_date and customer_id; partition large fact tables by date. COST: Full scan of transactions—use partition pruning; materialize quarterly aggregates if queried often.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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