Normalisierungsanomalien

Normalisierungsanomalien, or normalization anomalies, are issues that can arise when a database is designed using the principles of normalization. Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. However, excessive normalization can lead to several anomalies, which are problems that can occur during data insertion, updating, or deletion.

There are three main types of normalization anomalies:

1. Insertion Anomalies: These occur when new data cannot be inserted into the database without adding redundant or unnecessary information. For example, if a database is designed to store information about students and their courses, an insertion anomaly might occur if a new course is added without any students enrolled, as the course information would need to be duplicated.

2. Update Anomalies: These happen when updating a single piece of data requires multiple updates in different places within the database. For instance, if a student's address is changed, the address would need to be updated in multiple records if the database is not properly normalized.

3. Deletion Anomalies: These occur when deleting a piece of data results in the unintended loss of other data. For example, if a student drops a course and the course information is deleted, the information about the course itself would also be lost if the database is not properly designed.

To mitigate these anomalies, database designers often use a balance between normalization and denormalization. Denormalization involves intentionally introducing redundancy into the database to improve performance and reduce the complexity of queries. This approach can help to avoid the anomalies associated with excessive normalization while still maintaining a level of data integrity.