📊 Day 36 of My Data Analytics Journey – Normalization !

Today I learned about Normalization in databases.

🔎 What is Normalization?

Normalization is the process of organizing data in a database to eliminate redundancy and improve data integrity. It helps ensure that data is consistent, accurate, and easy to maintain.

✅ Why do we need Normalization?

• Reduces data duplication


• Ensures consistency across tables


• Saves storage space


• Makes queries more efficient

🔧 Example:

Without normalization:

OrderID | CustomerName | CustomerPhone | Product  

1       | Ramya        | 9876543210    | Laptop  

2       | Ramya        | 9876543210    | Keyboard  

Here, customer details repeat for every order.

With normalization (using separate tables):

Customers Table

CustomerID | Name   | Phone  

1          | Ramya  | 9876543210  

Orders Table

OrderID | CustomerID | Product  

1       | 1          | Laptop  

2       | 1          | Keyboard  

📚 Normal Forms (Levels of Normalization)

1. 
   1NF – Remove repeating groups, keep atomic values.


2. 
   2NF – Remove partial dependency (depends on part of a composite key).


3. 
   3NF – Remove transitive dependency (non-key depends on non-key).

🚀 Key takeaway:

Normalization makes databases clean, consistent, and scalable – a must-have skill for any Data Analyst.