AI agents can only work with data they can understand. This course shows you how to design that clarity into your data systems. Learn how to resolve ambiguity in your data models so AI agents can navigate and interpret data correctly, then craft AI-readable metadata—clear column descriptions, metric definitions, and routing triggers—to guide query behavior. Along the way, gather insights to establish data ownership, apply governance frameworks, and deprecate redundant tables to keep datasets organized. Finally, you’ll validate your work by running AI navigation tests that confirm reliability before deployment. A single end-to-end case study runs throughout, showing you how a disorganized warehouse can become an efficient, AI-friendly system. Designed for data professionals, this course equips you with the skills you need to govern data warehouses effectively in the AI age.
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