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What is normalization and denormalization? When would you use each?

SQLmedium0.4 min read

**Architectural Logic**: Normalization (1NF→3NF): Remove redundancy, enforce integrity. OLTP optimized for writes, consistency. Denormalization: Add redundancy for read performance. OLAP/data marts optimized for analytics. **Why**: Normalized = single source of truth, easier...

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Frequency
Low
Asked at 2 companies
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
PresidioSwiggy
Key Concepts Tested
etljoin

Why This Question Matters

This medium-level SQL question appears frequently in data engineering interviews at companies like Presidio, Swiggy. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (etl, join) will help you answer variations of this question confidently.

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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
85 words

Architectural Logic: Normalization (1NF→3NF): Remove redundancy, enforce integrity. OLTP optimized for writes, consistency. Denormalization: Add redundancy for read performance. OLAP/data marts optimized for analytics. Why: Normalized = single source of truth, easier updates. Denormalized = fewer joins, faster queries, larger storage. Scalability: Normalized scales for writes; denormalized scales for reads but requires ETL to maintain. Cost: Normalized saves storage; denormalized increases storage and refresh cost. Trade-off: Start 3NF for source; denormalize in warehouse based on query patterns. Flattened fact tables are standard in star schemas.

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