Chapter 10 - Database Normalization - Full Lecture

Introduction

This tutorial covers the concepts of database normalization, a fundamental process in database design that aims to reduce data redundancy and improve data integrity. Understanding normalization is crucial for anyone involved in database management, as it directly impacts the efficiency and reliability of data storage and retrieval.

Step 1: Understand the Purpose of Normalization

Normalization is the process of organizing a database to minimize redundancy and dependency. It helps to:

• Ensure data integrity and accuracy.
• Simplify data management.
• Enhance query performance.

Familiarize yourself with the reasons why normalization is essential, as it sets the foundation for effective database design.

Step 2: Learn About Normal Forms

Normalization is typically achieved through a series of stages known as normal forms. The primary normal forms to understand are:

1. First Normal Form (1NF)

   • Ensure all columns in a table contain atomic values.
   • Each entry must be unique and not repeat groups.

2. Second Normal Form (2NF)

   • Meet all requirements of 1NF.
   • Remove partial dependencies; ensure that all non-key attributes are fully functionally dependent on the primary key.

3. Third Normal Form (3NF)

   • Meet all requirements of 2NF.
   • Eliminate transitive dependencies; non-key attributes should not depend on other non-key attributes.

4. Boyce-Codd Normal Form (BCNF)

   • A stronger version of 3NF; every determinant must be a candidate key.

Familiarize yourself with these forms and their requirements.

Step 3: Identify Functional Dependencies

Understanding functional dependencies is key to normalization. A functional dependency occurs when one attribute uniquely determines another.

• Example: In a table of students, if a student ID uniquely identifies a student's name, then there’s a functional dependency from student ID to name.

Practical Tips

• Create a list of attributes and identify how they depend on one another.
• Use diagrams to visualize these dependencies.

Step 4: Apply Normalization to a Sample Database

Practice normalization with a sample database. Follow these steps:

1. Start with an Unnormalized Table

   • Collect data that may have redundancies, such as customer orders.

2. Convert to 1NF

   • Ensure all columns have atomic values.
   • Remove repeating groups.

3. Convert to 2NF

   • Identify partial dependencies and separate them into new tables.

4. Convert to 3NF

   • Remove transitive dependencies by creating additional tables.

Example

-- Sample SQL for creating a normalized table
CREATE TABLE Customers (
    CustomerID INT PRIMARY KEY,
    CustomerName VARCHAR(100),
    ContactEmail VARCHAR(100)
);

CREATE TABLE Orders (
    OrderID INT PRIMARY KEY,
    CustomerID INT,
    OrderDate DATE,
    FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID)
);

Step 5: Test Your Normalization

After normalizing your database, test it by performing common queries. Check for:

• Data integrity - ensure no redundant data exists.
• Performance efficiency - queries should execute quickly.

Common Pitfalls to Avoid

• Over-normalization can lead to excessive joins and complexity.
• Not considering performance trade-offs.

Conclusion

Database normalization is a critical skill that enhances data management practices. By understanding and applying the various normal forms and functional dependencies, you can design efficient databases that minimize redundancy and maintain data integrity.

Next steps include practicing normalization on different datasets and exploring denormalization strategies for specific use cases where performance is prioritized over data integrity.