What is the process of organizing data to eliminate redundancy called?

The process of organizing data to eliminate redundancy is known as normalization. Normalization involves structuring a database in a way that reduces data duplication and enhances data integrity. This is achieved through the application of various normal forms, which provide guidelines on how to separate and link data effectively.

By identifying and organizing related data into separate tables, normalization ensures that each piece of information is stored only once, which minimizes the chances of anomalies during insertion, update, or deletion processes. This makes the database more efficient and easier to maintain, as changes only need to be made in one place rather than across multiple records where the same data might be duplicated.

In contrast, the other options serve different purposes. Denormalization is the opposite process, where data is intentionally combined for performance reasons, often leading to redundancy. Data warehousing refers to the storage of large amounts of data from various sources for analysis and reporting, rather than focusing on eliminating redundancy. Data mining involves extracting useful patterns and information from large data sets, which is another distinct activity different from the process of structuring data to eliminate redundancies.