Part 11/12:
Model Derivation & Refinement: Suggests and refines conceptual, logical, and physical models, adhering to organizational standards—all with minimal manual input.
Iterative & Dynamic Updates: Supports seamless updates, versioning, and documentation, streamlining ongoing data maintenance.
The platform’s success demonstrates a 60–80% effort reduction in typical data modeling activities, translating into faster project delivery and more reliable models.
The Road Ahead: AI as an Enabler, Not a Replacement
While AI can automate many aspects of data modeling, the human role remains indispensable. Expertise is vital for:
Validating model accuracy.
Incorporating domain insights.
Handling complex scenarios requiring nuanced judgment.