
Enterprise architecture governance is often fragmented, with strategy, structure, and execution treated as separate concerns rather than an integrated system. As organizations scale data, analytics, and AI initiatives, this fragmentation creates unclear decision rights, inconsistent standards, and limited visibility into how architectural choices support business outcomes. Effective governance requires a coherent, capability-based approach that connects architectural intent to operational reality across business, data, and application domains.
This course, instructed by data management expert Irina Steenbeek, examines how enterprise architecture can be governed in a structured yet adaptable way. It focuses on the design of governance frameworks for business, data, and application architecture, clarifying required inputs, deliverables, standards, and role responsibilities. Participants develop detailed capability maps, define RACI-based role structures, assess maturity, and establish KPIs to measure progress and outcomes. Practical exercises and templates support the creation of governance frameworks that align architectural decisions with organizational goals, data architecture choices, and AI integration needs.
Course Highlights
Pricing and Credits
By the End of This Course, You’ll Be Able To:
Why Take This Course?
This course provides a structured approach to governing enterprise architecture in a way that aligns business strategy, data, and AI initiatives. It equips learners with practical tools to translate architectural complexity into clear governance structures and measurable outcomes.
Is This Course Right for You or Your Team?
This course is ideal for:
No technical experience is required. This course is designed for business-focused professionals seeking a structured, capability-driven approach to governing enterprise architecture across data and AI initiatives.
This Course Includes: