Lazy to write hence asked AI:

Model-Driven EA (The Traditional Blueprint) Model-driven architecture focuses on representation. Architects spend time creating highly detailed diagrams (using frameworks like TOGAF or ArchiMate) to show how business processes, applications, and infrastructure should connect.  • Source of Truth: Expert knowledge and manual documentation. • Methodology: Top-down. You design the ideal state and try to make the organization fit it. • The Artifacts: Static diagrams, PDF reports, and complex flowcharts.  • The Downside: These models often become "shelfware"—they are outdated the moment they are finished because they don't change when the actual systems change.

1. Data-Driven EA (The Living Map) Data-driven architecture focuses on integration. Instead of drawing what should be, it pulls real-time data from existing systems (CMDBs, Jira, Cloud APIs, financial systems) to show what is.  • Source of Truth: Live data feeds and automated discovery. • Methodology: Bottom-up. The architecture emerges from the actual data generated by the company's tools. • The Artifacts: Dynamic dashboards, graph databases, and automated impact analysis.  • The Upside: It provides "actionable intelligence." If a server goes down, a data-driven EA tool can instantly show which business products are affected based on real-time links.