PREPARE YOUR DATA / DA-07

Data Management

0.36Adaptability average

Without structured cataloguing, AI work duplicates itself across teams, version control collapses, and the audit trail required for both regulatory and engineering purposes becomes impossible to maintain at scale. Google Cloud's AI Adoption Framework treats discovery of data and ML artefacts as a foundational capability, recommending enterprise tooling — Vertex AI Feature Store, Dataplex, MLflow and equivalents — that catalogues datasets, models, pipelines and experiments to keep them searchable and reproducible. Implementation typically involves significant platform investment, dedicated catalogue management, and metadata standards that teams across the organisation are expected to maintain.

Potential across the 5 Future Positive Principles

Self-Directed

Agency-Centered

Impact-Led

System-Focused

Evolution-Driven

Industry Standard baseline

Future Positive potential

Source Frameworks