📊 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, …


This content originally appeared on DEV Community and was authored by Ramya .C

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.

âś… Why do we need Normalization?

  • Reduces data duplication
  • Ensures consistency across tables
  • Saves storage space
  • Makes queries more efficient

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🔧 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

đź“š 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.


This content originally appeared on DEV Community and was authored by Ramya .C


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