What is the purpose of normalization in data management?

Normalization in data management is primarily focused on organizing datasets to minimize redundancy and dependency. By eliminating redundant data, normalization reduces the risk of data anomalies, ensures data integrity, and leads to more efficient data management practices.

When a database is normalized, it is structured in a way that each piece of data is stored in one place, which decreases the chances of inconsistencies and redundancy. This process often involves dividing large tables into smaller ones and defining relationships between them, which helps in maintaining a consistent and accurate representation of the data.

The other choices, while related to data management, do not capture the essence of normalization. The creation of complex data structures can occur in various database designs, but it's not the objective of normalization. Enhancing data security can be a concern in database management, but it is not a direct result of normalization. Similarly, the integration of various data formats pertains to data interoperability and conversion, rather than the structural organization that normalization provides.