Normalization is primarily used in databases for what purpose?

Normalization in databases is primarily utilized to eliminate redundant data fields. This process involves organizing the database structure in a way that reduces data duplication, which enhances data integrity and consistency. By breaking down tables into smaller, related tables and defining relationships between them, normalization minimizes the risk of anomalies during data operations such as insertion, updating, and deletion.

Through normalization, data is stored more efficiently and retrieves related data without redundancy. This leads to a more streamlined database design, where any change in data needs to occur in a single place, thereby maintaining data accuracy and reducing storage costs.

Other options suggest purposes that do not align with the primary goals of normalization. For instance, enhancing query performance may be a benefit of a well-structured, normalized database, but it is not the primary objective of normalization itself. Converting a database to a hierarchical format is an entirely different database model and isn't relevant to the normalization process, which is generally related to relational databases. Increasing data redundancy runs contrary to the principles of normalization, which fundamentally aims to reduce redundancy in data storage.