Normalization_in_DBMS.pptxsdjdhsjksjdfdjdagdg

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1. Normalization in DBMS A Complete Guide with Detailed Explanation

2. What is Normalization? Normalization is the process of organizing data in a database. It reduces data redundancy and improves data integrity. Main goals: - Eliminate redundant data - Ensure data dependencies make sense - Simplify queries

3. Why Normalization is Needed? 1. Avoid data redundancy 2. Prevent update anomalies 3. Prevent insertion anomalies 4. Prevent deletion anomalies 5. Efficient storage and better organization

4. Types of Anomalies 1. Update Anomaly – Changing data in multiple places. 2. Insertion Anomaly – Cannot insert data due to missing fields. 3. Deletion Anomaly – Deleting one record removes useful information.

5. First Normal Form (1NF) Rules: - Each table cell must contain a single value. - Each record must be unique. Example: Unnormalized table → Split repeating groups into separate rows.

6. Second Normal Form (2NF) Rules: - Must be in 1NF. - No partial dependency (non-key attributes must depend on the whole primary key). Example: Split composite key dependencies into separate tables.

7. Third Normal Form (3NF) Rules: - Must be in 2NF. - No transitive dependency (non-key attributes must depend only on primary key). Example: Remove columns that depend on non-primary attributes.

8. Boyce-Codd Normal Form (BCNF) Rules: - A stronger version of 3NF. - Every determinant must be a candidate key. Ensures stricter removal of redundancy and anomalies.

9. Higher Normal Forms (4NF & 5NF) 4NF: - Must be in BCNF. - No multi-valued dependencies. 5NF: - Must be in 4NF. - Deals with join dependency to ensure no redundant data after decomposition.

10. Advantages of Normalization 1. Eliminates data redundancy 2. Improves data consistency 3. Easier to maintain database 4. Saves storage space 5. Improves query performance

11. Disadvantages of Normalization 1. Too many tables → Complex queries 2. Requires joins, which may slow performance 3. Sometimes denormalization is preferred for faster access

12. Conclusion Normalization is essential for efficient database design. It ensures data integrity, reduces redundancy, and prevents anomalies. However, balance is needed between normalization and performance.