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Data normalization is the process of organizing and structuring a database to minimize data redundancy and dependency by dividing large tables into smaller, related tables. It follows a set of rules known as normal forms (NF) to ensure data integrity, consistency, and efficient data retrieval.
Data normalization is essential in relational database management systems (RDBMS) to eliminate duplicate data, prevent anomalies, and ensure efficient data storage. The process involves breaking down complex tables into simpler ones, establishing relationships using primary keys (PK) and foreign keys (FK) while maintaining data integrity.
Normalization follows a series of rules known as normal forms (NF), where each level progressively improves database organization.
A table is in 1NF if:
Example Before 1NF (Unnormalized Table):
| Order_ID | Customer_Name | Items Ordered |
|---|---|---|
| 101 | John Doe | Laptop, Mouse |
| 102 | Jane Smith | Keyboard |
After 1NF (Atomic Values Applied):
| Order_ID | Customer_Name | Item_Ordered |
|---|---|---|
| 101 | John Doe | Laptop |
| 101 | John Doe | Mouse |
| 102 | Jane Smith | Keyboard |
A table is in 2NF if:
Example Before 2NF:
| Order_ID | Customer_Name | Item_Ordered | Customer_Phone |
|---|---|---|---|
| 101 | John Doe | Laptop | 123-456-7890 |
| 101 | John Doe | Mouse | 123-456-7890 |
| 102 | Jane Smith | Keyboard | 987-654-3210 |
Issue: Customer_Name and Customer_Phone depend only on Order_ID, causing redundancy.
After 2NF (Splitting into Two Tables):
Orders Table:
| Order_ID | Customer_ID | Item_Ordered |
|---|---|---|
| 101 | 1 | Laptop |
| 101 | 1 | Mouse |
| 102 | 2 | Keyboard |
Customers Table:
| Customer_ID | Customer_Name | Customer_Phone |
|---|---|---|
| 1 | John Doe | 123-456-7890 |
| 2 | Jane Smith | 987-654-3210 |
A table is in 3NF if:
Example Before 3NF:
| Customer_ID | Customer_Name | Customer_Zip | Customer_City |
|---|---|---|---|
| 1 | John Doe | 10001 | New York |
| 2 | Jane Smith | 90001 | Los Angeles |
Issue: Customer_City depends on Customer_Zip, not on Customer_ID.
After 3NF (Splitting Tables to Remove Transitive Dependency):
Customers Table:
| Customer_ID | Customer_Name | Customer_Zip |
|---|---|---|
| 1 | John Doe | 10001 |
| 2 | Jane Smith | 90001 |
Zip_Code Table:
| Customer_Zip | Customer_City |
|---|---|
| 10001 | New York |
| 90001 | Los Angeles |
A table is in BCNF if:
BCNF is a stricter version of 3NF, ensuring no dependencies exist except for super keys.
A table is in 4NF if:
A table is in 5NF if:
Eliminates duplicate data, saving storage space and improving efficiency.
Maintains data consistency across related tables, reducing errors.
Minimizes insertion, deletion, and update anomalies.
Optimized data retrieval with structured relationships.
Easier database maintenance and future expansion.
Joining multiple normalized tables may slow down performance.
More foreign key dependencies require careful database design.
Additional indexing and constraints may require more processing power.
Used in MySQL, PostgreSQL, SQL Server, and Oracle databases.
Ensures data consistency in transactions, accounts, and records.
Maintains structured patient records and medical histories.
Organizes customer, order, and inventory data efficiently.
Manages structured business operations and supply chains.
With big data and NoSQL databases, denormalization is sometimes preferred for faster performance. However, hybrid models combining normalization with caching strategies are becoming more common in modern data management.
Data normalization is the process of organizing a database to reduce redundancy and improve data integrity. It involves structuring tables and relationships using normalization rules, such as First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF), to ensure efficiency and consistency.
The main normal forms in data normalization are:
Data normalization is important because it:
The disadvantages of data normalization include:
Data normalization should be avoided in cases where:
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