Redundancy in a database refers to the duplication of data in one or more tables. This duplication can lead to a variety of problems and inefficiencies, including:
Data inconsistency: When the same data is stored in multiple places, it becomes difficult to ensure that all copies are consistent with each other. If one copy is updated or deleted, the other copies may not be, leading to inconsistencies in the data.
Increased storage requirements: Storing the same data in multiple places requires more storage space than if the data were stored only once.
Update anomalies: When data is duplicated, it can become difficult to update it in a way that preserves data consistency. For example, if a customer's address is stored in two different tables, updating one table but not the other can result in inconsistencies.
Deletion anomalies: When data is duplicated, deleting it from one place but not another can result in inconsistencies and loss of data.
Increased processing time: When the same data is stored in multiple tables, it can take longer to retrieve and process the data, especially if the data needs to be updated in multiple places.
To avoid these problems, it is important to normalize the database and eliminate redundancy. Normalization involves organizing the data into tables in a way that minimizes duplication and ensures that each table has a well-defined primary key. By doing so, we can improve data consistency, reduce storage requirements, and eliminate update and deletion anomalies.
