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.
✅ 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)
- 1NF – Remove repeating groups, keep atomic values.
- 2NF – Remove partial dependency (depends on part of a composite key).
- 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
Ramya .C | Sciencx (2025-09-15T13:09:52+00:00) 📊 Day 36 of My Data Analytics Journey – Normalization !. Retrieved from https://www.scien.cx/2025/09/15/%f0%9f%93%8a-day-36-of-my-data-analytics-journey-normalization/
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