Final answer:
Normalization in database management refers to dividing a single table into two or more related tables to reduce redundancy and improve data integrity. Normal forms dictate the levels of normalization by setting criteria to avoid anomalies, with the aim to have a more maintainable and organized database.
Step-by-step explanation:
In the context of database management, the process of normalization best describes dividing a single table into two or more tables. This process is implemented to reduce data redundancy and improve data integrity. By separating data into multiple tables and creating relationships between these tables, normalization allows for a more organized data structure.
Normalization involves creating tables that store a minimal amount of redundant data, which can help in maintaining the consistency of the data. There are different normal forms, and each form has specific criteria that must be met to achieve a higher level of normalization. Advancing through the normal forms generally increases the complexity of the database design, but it enhances the ability to manage data without encountering anomalies or integrity issues.
Data redundancy is minimized because normalization often involves eliminating duplicate information and creating relationships through foreign keys. Each normal form aims to handle specific types of anomalies. Generally, tables are not considered more correct than others based on the level of normalization, but higher normal forms can lead to better organized and more maintainable data structures.
When grouping the data, you could consider aspects such as functional dependencies and the nature of the data. The advantage of normalized data is that it tends to be easier to update and can lead to more efficient queries, especially when the database grows in size and complexity. On the flip side, more complex queries might be needed to reconstitute data spread across multiple tables.