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Normalization: Concepts and its importance

SQLmedium0.3 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
ZS Associates
Key Concepts Tested
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Expert AnswerPremium
69 wordsInterview-ready
Normalization reduces redundancy, update anomalies, and inconsistencies. Enforces data integrity via dependencies. Steps: identify dependencies, decompose into smaller tables, ensure each table has single theme. Important for OLTP; less for analytics. Over-normalization can hurt query performance (many joins). **Why it matters**: Design choices compound at scale—wrong approach can cause 100× overhead. **Scalability trade-offs**: Profile before optimizing; validate on sample then full....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like ZS Associates. The answer also includes follow-up discussion points that interviewers commonly explore.

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