What is the term for the process of streamlining data to minimize redundancy?

Normalization is the correct term for the process of streamlining data to minimize redundancy. It is a fundamental concept in database design that involves organizing the fields and tables of a database in such a way that redundancy and dependency are reduced. The goal of normalization is to ensure that each piece of data is stored only once, which increases data integrity and efficiency.

By eliminating duplicate data, normalization helps to improve the clarity and coherence of the database structure, making it easier to maintain and less prone to errors. This process typically involves dividing large tables into smaller, interconnected tables and defining relationships among them, thus ensuring that data is logically stored and can be retrieved efficiently.

In contrast, data scrubbing and data cleansing involve correcting or removing inaccurate, incomplete, or irrelevant data from a dataset. While both are essential for maintaining the quality of data, they do not specifically focus on the structural aspect of minimizing redundancy as normalization does. Data defining, on the other hand, is more about establishing what data elements mean or how they should be used, rather than reorganizing data to minimize overlap.