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.
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