Data Redundancy and associated problems

Data Redundancy and associated problems

Redundancy means having multiple copies of same data in the database. This problem arises when a database is not normalized.

Example:

Consider Student relation

Studentid	Name	College	Course	Colrank
200	Raju	RDC	BCom	1
201	Ramu	RDC	BCom	1
201	Nani	RDC	BCom	1

As it can be observed that values of attribute college name, college rank, course is being repeated which can lead to problems.

Problems caused due to redundancy are:

• Insertion anomaly, 
• Deletion anomaly, and 
• Updation anomaly.

Insertion anomaly: An Insert Anomaly occurs when certain attributes cannot be inserted into the database without the presence of other attributes.

For example if a student detail has to be inserted whose course is not being decided then insertion will not be possible till the course is decided for student.

Deletion anomaly: This anomaly happens when deletion of data record results in losing some unrelated information that was stored as part of the record that was deleted from a table.

For example if the details of students in the table are deleted then the details of college will also get deleted.

Updation anomaly: An update anomaly is a data inconsistency that results from data redundancy and a partial update.

For example if the rank of the college changes then changes will have to be all over the database which will be time-consuming and computationally costly. If update does not occur at all places then database will be in inconsistent state.