Fabric Data Engineering: Preparing AI-Ready Analytics Data

Modern AI agents and generative tools are only as good as the data they access. To unlock their true potential, data professionals must structure and enrich their analytics platforms so AI can interpret them accurately. This text-based course guides you through the process of transforming raw analytics into AI-ready semantic layers. You will learn how to enrich gold-layer data stores in Fabric, define relationships, and provide the linguistic context necessary for AI agents to deliver reliable business insights. What you'll learn: Understand the fundamentals of AI-ready data architecture and semantic modeling; Configure gold-layer data stores in Fabric to support natural language querying; Define clear semantic models and establish robust relationships between tables; Apply linguistic context and metadata to help AI agents interpret business terms correctly; Generate ontologies that bridge the gap between technical data structures and business logic; Practice designing clean, accessible schemas through written scenarios and structured examples. The course starts with essential terminology and foundational definitions of semantic layers before moving into practical design patterns for gold-layer data enrichment and AI integration. You will follow a structured learning path from basic concepts to advanced ontology generation. Designed for beginner data analysts, database administrators, and aspiring data engineers, this course requires no prior experience with advanced AI modeling. Start building the semantic foundation that powers the future of automated business intelligence today.