Agentic Dimensional Modeling: Designing Analytical Data Models for AI Agents, Semantic Systems and Autonomous Decisions (Agentic Data Management)
English | October 18, 2026 | ASIN: B0HNH95L6P | 517 Pages | EPUB (True) | 2.97 MB
What happens to dimensional modeling when the consumer is no longer only a human analyst-but an AI agent that can recommend, decide and act?For decades, dimensional modeling has helped organizations turn operational data into understandable facts, dimensions and business measures. That foundation remains essential. But agentic systems expose a new problem: much of the meaning that humans once supplied implicitly can no longer remain implicit.An AI agent needs more than a technically correct star schema. It needs to know what a business term means, which source is authoritative, what was known at the time of a decision, which policy applied, whether evidence was sufficient, who had authority to act and whether an attempted action became a real business outcome.Agentic Dimensional Modeling develops a practical architecture for that new requirement.Rather than replacing dimensional modeling, the book introduces Agent-Ready Dimensional Modeling (ARDM)-an approach that preserves the strengths of grain, facts, dimensions, conformance and history while extending the analytical contract for machine consumers.The book's distinctive contribution is the way it connects classical dimensional design with the realities of agentic systems. It shows how to model and govern:business events, state and machine decisions at the correct grainsemantic contracts that make enterprise meaning explicitdecision-time knowledge separately from current truthidentity, MDM, source authority, provenance and evidenceagent recommendations, decisions, approvals, attempts, commitments and outcomes as distinct analytical eventssemantic layers, knowledge graphs, vector retrieval, documents and operational APIs without forcing every concern into the warehousecontext gateways that serve governed business context to agent runtimesfreshness, correction, replay, testing, observability and reconciliation for agent-ready analytical systemsmigration from an existing BI or lakehouse estate toward an agent-ready analytical platformThe book follows a continuous Atlas Industrial Group case rather than relying on disconnected examples. The same inventory, supplier, revenue and service decisions evolve across the chapters, allowing readers to see how semantics, time, authority, evidence and operational boundaries interact in a realistic enterprise architecture.It also introduces an important design discipline: not every agentic requirement belongs in the dimensional model. The book explicitly separates the responsibilities of dimensional models, semantic layers, MDM, graphs, vector stores, document retrieval, policy services and operational systems.Across 22 chapters, the reader moves through four practical stages
efine the business problem → Define the solution → Design the model → Deliver the platform.A downloadable Reader Edition companion pack provides ten ARDM workbooks containing supplied inputs, blank practitioner exercises, worked reference solutions and design rationales for the ADM01-ADM22 activities in the book.This is not a book about adding an AI layer on top of a warehouse.It is about redesigning the analytical contract so that enterprise data remains understandable, reconstructable and governable when software itself becomes part of the decision process.Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
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