Domain 5

Data Domain

Manages data as a strategic asset, establishing canonical data models that enable a consistent semantic interpretation across the entire organization and generative AI.

Data

Purpose of the Domain

To establish a canonical, semantically consistent data architecture that enables the organization to understand, share, and exploit the meaning of the business, enabling advanced analytics, automation, and GenAI effectively.

What Does It Govern / What Does It Design?

  • Enterprise-wide canonical data models
  • Common semantic definitions of the business
  • Key entities, attributes, and relationships
  • Data quality, consistency, and governance rules
  • Data preparation for human and AI consumption

Value and Advantages for the Organization

  • A common business language across systems and functional areas
  • Simpler, decoupled integrations
  • Less ambiguity and rework
  • A solid foundation for analytics, automation, and GenAI
  • More reliable and traceable decisions

Role of Artificial Intelligence in This Domain

GenAI does not understand tables or databases; it understands meaning.

Canonical models are the language of the business for AI.

Risks of Not Managing It Properly

  • Inconsistent and contradictory data across applications
  • Fragile and costly integrations
  • Erroneous or unreliable GenAI results
  • Intelligent agents operating with incomplete context
  • Automated decisions without business coherence

Dependencies and Relationships with Other Domains

  • Business Defines the meaning and the entities of the business
  • Agents Consume canonical models to operate and decide
  • Applications Implement and respect the defined semantics
  • Integration Uses the canonical model as the exchange contract
  • Security Governs access, privacy, and use of data
  • Platform Provides managed capabilities for data storage, governance, and processing
Key message: Without canonical models, AI improvises. With clear semantics, AI generates value.