# Activity: Research  Normalization and Denormalization in Databases

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### **Step 1: Research Database Normalization**

1. **What is Normalization?**
    
    * Research the purpose of **normalization** in database design. Understand how it reduces **data redundancy** and improves **data integrity**.
        
    * Document why normalization is important for maintaining an efficient and consistent database structure.
        
2. **Normal Forms**:
    
    * Research the different levels of **normal forms** (1NF, 2NF, 3NF, BCNF).
        
        * **First Normal Form (1NF)**: Ensures that each column contains atomic (indivisible) values, and each record is unique.
            
        * **Second Normal Form (2NF)**: Builds on 1NF by ensuring that all non-key attributes are fully dependent on the primary key.
            
        * **Third Normal Form (3NF)**: Ensures that there are no transitive dependencies, meaning non-key attributes depend only on the primary key.
            
        * **Boyce-Codd Normal Form (BCNF)**: A stricter version of 3NF that ensures even more precise handling of functional dependencies.
            
3. **Advantages of Normalization**:
    
    * Research the benefits of normalization, such as reducing redundancy, ensuring data consistency, and improving data organization.
        

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### **Step 2: Research Denormalization**

1. **What is Denormalization?**
    
    * Research **denormalization** and understand its purpose in database design. Learn how denormalization intentionally adds **redundancy** to optimize data retrieval speed.
        
    * Document why denormalization is sometimes necessary to improve performance, especially in large-scale databases where read-heavy operations are common.
        
2. **When to Use Denormalization**:
    
    * Research scenarios where denormalization is beneficial, such as in **data warehousing**, **reporting systems**, and **read-optimized databases**.
        
    * Understand the trade-offs, including how denormalization can speed up queries but may lead to data anomalies and increased storage requirements.
        

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### **Step 3: Compare Normalization vs. Denormalization**

1. **Differences**:
    
    * Research and document the key differences between normalization and denormalization. Understand the trade-offs between the two approaches in terms of **data redundancy**, **query performance**, and **data integrity**.
        
2. **Practical Examples**:
    
    * Find real-world examples or case studies where both normalization and denormalization are applied.
        
    * Research situations where databases are first normalized for data integrity and then selectively denormalized to optimize performance.