Data redundancy means storing the same data multiple times.
It occurs when information is repeated in different rows or tables.
Redundant data increases database size.
Redundancy can cause data inconsistency.
If one value is updated and others are not, the database becomes unreliable.
Redundant data makes maintenance difficult.
It increases update, insert, and delete problems.
These issues are called anomalies.
In this structure, student information is repeated for every course.
This causes unnecessary duplication.
Reducing redundancy improves database quality.
Normalization helps eliminate redundant data.
Understanding redundancy is essential for good design.