What process is used to organize data in order to minimize redundancy?

Data normalization is a systematic approach that organizes data within a database to minimize redundancy and dependency. This process involves structuring data into appropriate tables and defining relationships between them in such a way that each piece of information is stored only once, thus reducing duplicate data entries and potential inconsistencies.

By implementing normalization, the integrity of the database is improved because the same data isn’t repeated in multiple places. This makes data management more efficient, enhances data retrieval times, and ensures that any changes made to the data are reflected throughout the database without introducing errors associated with duplication.

In contrast, data accuracy relates to the correctness and precision of the data within the database but does not specifically address redundancy. Data architecture refers to the overall structure and design of data systems, which includes how data is organized but is a broader concept. Data integrity concerns the accuracy, consistency, and reliability of data over its lifecycle, which is essential but again, does not specifically target the organization of data to reduce redundancy.