Database Normalisation Questions Medium
Data redundancy refers to the duplication of data within a database. In the context of database normalization, it is considered undesirable as it can lead to several issues.
Firstly, data redundancy increases storage requirements. When the same data is stored multiple times, it occupies more space than necessary, resulting in inefficient use of storage resources.
Secondly, data redundancy can lead to inconsistencies and anomalies. If the same data is updated in one place but not in others, it can result in inconsistencies and discrepancies within the database. For example, if a customer's address is stored in multiple tables and it is updated in one table but not in others, it can lead to conflicting information.
Thirdly, data redundancy can impact data integrity. When redundant data exists, it becomes difficult to maintain data integrity and ensure that the data is accurate and consistent. It becomes challenging to enforce constraints and rules on redundant data, leading to potential data quality issues.
To address data redundancy, database normalization techniques are employed. Normalization involves organizing data into multiple tables and eliminating redundant data by establishing relationships between these tables. By breaking down data into smaller, more manageable units and linking them through relationships, redundancy can be minimized or eliminated. This helps in improving storage efficiency, reducing inconsistencies, and enhancing data integrity within the database.