What does data normalization help achieve in a relational database?

Data normalization in a relational database is primarily aimed at organizing data to reduce redundancy and improve data integrity. By structuring the data in such a way that dependencies are properly enforced, normalization helps ensure that each piece of information is stored only once, minimizing the likelihood of anomalies during data updates, deletions, or insertions.

Through normalization processes, such as dividing a database into tables and establishing relationships between them, it becomes easier to maintain the accuracy and consistency of the data. This structured approach aids in streamlining data access, as queries can be more efficient when the database design reflects the logical relationships of the data. As a result, an application querying the database can retrieve and manipulate data with less complexity and increased reliability.

While increased data redundancy, complex data structures, and reduced need for data backups are aspects not typically associated with the goals of normalization, they highlight the importance of focusing on an efficient and consistent data management system. Therefore, the emphasis on streamlined data access and integrity is what makes normalization a vital practice in database design.