Create data models
How create data models are reshaped as AGI capability advances.
The bottom line
Roughly 95% of the work in Create data models is information-shaped — already within reach of AI delivery. The question here is not whether it shifts, but which tasks go first and who staffs the residual.
Why: With no child occupations seeded, the score is derived from the process lens and description. Although the overarching lens is 'Manage environmental health and safety (EHS)', the specific process—creating conceptual and physical data models for data structure and storage—is pure computer-based information transformation, anchoring it firmly in the digital band.
grounded in the economy graph · digital scalar 0.95 · digital
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How the work flows
Trigger: A new business requirement, application development project, or analytics initiative requests a structured data schema for information storage and retrieval.
- Gather data requirements from business stakeholders
- Draft the conceptual data model to map core entities and relationships
- Translate the conceptual design into a detailed logical data model
- Develop the physical data model optimized for the target database management system
- Validate the data models against business rules and performance constraints
- Document and publish the models to the enterprise data dictionary
Outcome: A validated physical data model is approved, documented, and ready for deployment in the target database environment.