This process keeps data models up-to-date with evolving requirements and business processes, ensuring consistency across conceptual, logical, and physical levels through regular updates and automated tools. This includes reverse engineering the latest physical data models to maintain alignment with their logical counterparts and documenting all changes. This process ensures that data models remain accurate, relevant, and consistent over time, supporting improved data quality and governance.