Data redundancy can cause data anomalies in a database - most commonly insertion, deletion and update errors. The process of data normalization helps to eliminate data redundancy and its resultant anomalies.Continue Reading
Data redundancy occurs when a specific piece of data can be found in more than one area of the database. A common example would be a university or college's database of current enrollment in courses. One student might be enrolled in several different courses, so their individual student record may be reproduced several times. In a manufacturing scenario, a single vendor may be used for various projects and products.
It is important to eliminate the occurrence of data redundancy while still maintaining data integrity through the multi-step normalization process. Redundancy typically results in three common data anomalies - or instances where the data is inconsistent.