The process of breaking data tables apart into related entities in order to reduce redundancy in the data is called _________.

• A. Normalization
• B. Denormalization
• C. Aggregation
• D. Data Integration

Answer: (A)

Normalization is the process of organizing data to minimize redundancy and maintain data integrity by separating data into related entities. By splitting a large table into smaller, logical tables—such as separate ones for customers, products, and orders—you store each fact in one place and link the pieces with keys. This reduces duplicated information and prevents anomalies when updating, inserting, or deleting data, since changes cascade through the related tables rather than needing updates in multiple places. You can still fetch the full picture by joining the tables when needed. Denormalization reintroduces redundancy for faster reads, aggregation focuses on summarizing data, and data integration combines data from different sources; these approaches don’t primarily aim to reduce redundancy by splitting data into related entities, so normalization is the best fit.