What does data normalization primarily aim to achieve?

Data normalization is a systematic process in database management that primarily focuses on organizing data to reduce redundancy and improve data integrity. By structuring a database effectively, normalization eliminates unnecessary duplicate data, ensuring that each piece of information is stored only once. This approach not only minimizes storage space but also enhances the efficiency of data manipulation and retrieval.

Normalizing data allows for clearer relationships among tables within a database, facilitating easier updates and maintenance. For example, if customer data is normalized, any changes to customer information need to be made in only one place rather than in multiple records scattered throughout the database. This significantly decreases the chances of inconsistencies and errors, leading to a more reliable and coherent dataset.

While protecting sensitive information, transforming data formats, and increasing data access are important functions in data management, they are not the primary goals of data normalization. Their focus lies elsewhere, while normalization is distinctly centered on reducing redundancy as a method to achieve a more streamlined and efficient database structure.