Data Model Enhancement refers to the process of refining and improving the structure and organization of a data model. This involves optimizing data relationships, adding or modifying attributes, and ensuring data integrity and consistency. Common uses include improving data quality, simplifying data access, enhancing data analysis capabilities, and supporting evolving business requirements. It may also involve techniques like normalization, denormalization, and the introduction of new entities or relationships to better reflect the real-world entities being modeled.
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