# Overview There are various forms of normalization: #flashcard - Unnormalized Form (UNF) - Data may contain repeating groups and multi-valued attributes - First Normal Form (1NF) - Eliminate repeating groups (each field contains only atomic values) and each record must be unique - Second Normal Form (2NF) - Already in 1NF - Eliminate partial dependences. Non-key attributes must depend entirely on the primary key, not just part of it. - Third Normal Form (3NF) - Already in 2NF - Eliminate transitive dependencies. Non-key attributes must depend only on the primary key and not on other non-key attributes. # Key Considerations # Pros #flashcard - Minimizes data redundancy - Enhances data integrity and consistency - Optimized for transactional updates - Provides flexibility for data integration # Cons - Query performance tradeoffs (require multiple joins) - Slower analytical processing - Requires ETL effort for denormalization - Not always ideal for AI & ML Workloads # Use Cases # Related Topics ## Normalization vs. Denormalization