What effect does data normalization have on database operations?

Data normalization is a process used in database design to organize data and eliminate redundancy by ensuring that dependencies are properly enforced. When data is normalized, it is structured in such a way that each piece of data is stored only once, which streamlines how data is accessed and manipulated.

Improving query performance is achieved through normalization because it allows databases to operate more efficiently. By reducing the amount of duplicate data and ensuring that related data is properly structured across tables, queries can be executed more quickly. This structured approach enables the database to find and retrieve the desired information with fewer resources and less processing time, ultimately leading to faster response times for users making queries.

Moreover, normalization helps maintain data integrity by reducing the chances of anomalies that can occur when data is duplicated. By organizing the data into tables that relate properly to one another, any updates or changes can be made in a single location without causing inconsistencies.

In contrast, other choices highlight potential misconceptions regarding normalization. For example, while some might think normalization complicates data retrieval, it actually organizes data in a way that often makes retrieval easier and more logical. The belief that it leads to increased redundancy is directly opposed to the purpose of normalization itself, which seeks to minimize redundancy. Lastly, the idea that it reduces