In data management, what does normalization refer to?

Normalization in data management is fundamentally about the process of organizing data to reduce redundancy and improve data integrity. This process involves structuring a database in such a way that it reduces the chances of data anomalies, such as update anomalies, insertion anomalies, and deletion anomalies.

When a database is normalized, it is typically divided into multiple tables that are linked through relationships. This means that instead of storing repetitive data across several areas, data is stored in a structured manner, with related data located together. The goal is to ensure that each piece of information is stored only once, which not only saves space but also ensures that any changes made to that data are maintained consistently across the database.

This approach enhances the efficiency and effectiveness of data management, allowing for better data retrieval and storage. Normalization also aids in achieving a logical data model that simplifies the understanding and manipulation of the data. As a result, businesses can maintain a cleaner dataset that is less prone to errors and inconsistencies, thus ensuring higher data reliability.