
Metadata is the connective tissue that gives data meaning, trust, and usability across an organization. Without clear governance, metadata initiatives often become fragmented, limiting transparency, accountability, and the ability to scale analytics and AI. This course, led by data management expert Irina Steenbeek, examines how a well-designed metadata governance framework establishes clarity and responsibility across data and AI initiatives.
The course presents a structured methodology for defining metadata management capabilities, deliverables, policies, processes, and role responsibilities. It addresses the design of metamodels, data catalogs, lineage, and supporting tools, alongside maturity assessment and KPI development to track progress and effectiveness. Through practical frameworks and examples, participants develop a governance approach suited to their organization’s architecture, business needs, and long-term objectives.
Course Highlights
Pricing and Credits
By the End of This Course, You’ll Be Able To:
Why Take This Course?
Strong metadata governance is critical for trusted, discoverable, and usable data. This course provides a practical framework for building metadata governance aligned with business and data strategy.
Is This Course Right for You or Your Team?
This course is ideal for:
No technical background is required. This course is designed for professionals focused on establishing clear, business-aligned metadata governance capabilities rather than implementing specific tools.
This Course Includes: