Database Normalisation Questions Medium
Data anomalies refer to inconsistencies or irregularities that can occur in a database when it is not properly normalized. These anomalies can affect the accuracy, integrity, and reliability of the data stored in the database.
There are three main types of data anomalies that can occur:
1. Insertion Anomalies: Insertion anomalies occur when it is not possible to add new data to the database without also adding unrelated data. For example, if a database is not properly normalized and a new customer record cannot be added without also providing information about the customer's orders, it would be an insertion anomaly. This can lead to data duplication and inefficiency in data storage.
2. Update Anomalies: Update anomalies occur when updating data in the database results in inconsistencies or inaccuracies. For instance, if a customer changes their address and the database is not properly normalized, the address would need to be updated in multiple places, leading to potential inconsistencies if the update is not performed correctly in all instances.
3. Deletion Anomalies: Deletion anomalies occur when deleting data from the database unintentionally removes other related data. For example, if a customer record is deleted and the database is not properly normalized, it could also delete the customer's order history, resulting in the loss of valuable information.
By normalizing a database, these anomalies can be minimized or eliminated. Database normalization involves organizing the data into multiple tables and establishing relationships between them through primary and foreign keys. This helps to ensure data integrity, reduce redundancy, and improve overall database performance.