Normalization in DBMS

Data duplication may occur in a big database defined as a single relation. This data repetition may result in:
Increasing the size of relationships.
It is difficult to manage and update data because it requires searching through several records in relation.
Wastage and inefficient use of disk space and resources.
Errors and inconsistencies become more likely.
To address these issues, we should examine and breakdown the redundant data relations into smaller, simpler, and well-structured relations that satisfy desirable qualities. Normalization is the practice of breaking down relationships into those with fewer properties.

Normalization in DBMS is a strategy for designing the schema of a database by altering the existing schema, which also eliminates data redundancy and reliance. As a result, using Normalization, the undesirable duplication in data is removed, as are the abnormalities. Values such as null are not permitted to be input for a column in insert anomalous.
The data cannot be updated correctly in an update anomaly because the same values appear numerous times in a column, and in a delete anomaly, the deletion of a record causes inconsistency since it is erased from more than one row. As a result, the goal of normalization is to eliminate redundant data while still storing only related data in the database. This reduces the database size and logically stores the data in the database.