The process of adding redundancy back into a physical data model is known as denormalization.

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Denormalization involves adding redundancy back into a data model to improve performance or simplify queries, typically by duplicating data in multiple tables or columns. This can include merging tables, adding calculated fields, or storing aggregated data alongside detailed records. Denormalization is often used in data warehousing and analytical applications, where complex queries may require significant processing power and speed is a priority.

The Process of Adding Redundancy Back into a Physical Data