Design-Driven Data Engineering From Business Design to Database Architecture and Analytics Systems

1. Front Matter
   1. Title Page
   2. Copyright
   3. Dedication
   4. Acknowledgments
   5. About the Author
   6. Preface
   7. How to Use This Book
2. Introduction
   1. Why Design Matters
   2. From Requirements to Results
   3. Overview of the Design-Driven Framework
3. Part I — Business Design
   1. Chapter 1 — Discovering Decisions
      1. Interview Techniques that Reveal Decisions
      2. Mapping Actors, Actions, and Outcomes
   2. Chapter 2 — Value Chains & Decision Flows
      1. Value Chain Mapping
      2. Decision Workflows and KPIs
   3. Chapter 3 — Domain Language & Concept Maps
      1. Capturing Vocabulary and Business Rules
      2. Building Concept Maps
   4. Chapter 4 — From Narratives to Questions
      1. Translating Business Narratives into Analytical Questions
      2. Prioritizing Use Cases
4. Part II — Information Design
   1. Chapter 5 — Canonical Models & Boundaries
      1. Canonical vs Operational Models
      2. Bounded Contexts
   2. Chapter 6 — Dimensional & Event Modeling
      1. Fact and Dimension Design
      2. Event-Driven Models and State Machines
   3. Chapter 7 — Semantic Layers & Information Products
      1. Designing a Semantic Layer
      2. Packaging Data as Products
   4. Chapter 8 — Integration Strategies
      1. Cross-Domain Integration Patterns
      2. Handling Duplication and Conflicts
5. Part III — System Design
   1. Chapter 9 — Architecture Patterns
      1. Medallion / Lakehouse Architectures
      2. Batch, Micro-batch, and Streaming
   2. Chapter 10 — Ingestion & Transformation
      1. Source Patterns and Connectors
      2. Transformations, Idempotency, and CDC
   3. Chapter 11 — Governance, Quality & Lineage
      1. Data Contracts and Schemas
      2. Lineage, Observability and Testing
   4. Chapter 12 — Automation & CI/CD for Data
      1. Infrastructure-as-Code
      2. Reusable Pipelines and Templates
   5. Chapter 13 — Analytics, Semantic Models & Self-Service
      1. Designing Semantic Models (Power BI, Looker, etc.)
      2. Enabling Self-Service Without Chaos
   6. Chapter 14 — AI-Ready & Real-Time Architectures
      1. Model Inputs, Feature Stores, and MLOps Basics
      2. Designing for Real-Time Decisioning
6. Practical Tools, Templates & Patterns
   1. Business Design Blueprints
   2. Canonical Entity Templates
   3. Dimensional Modeling Guidelines
   4. Pipeline & Orchestration Blueprints
   5. DevOps / DataOps Automation Scripts
   6. Governance & Observability Checklists
7. Case Studies
   1. Retail Analytics — From Concept to Production
   2. Financial Services — Real-Time Risk Monitoring
   3. Healthcare — Secure Interoperable Models
8. Appendices
   1. Appendix A — Glossary
   2. Appendix B — Tools & References
   3. Appendix C — Companion Course Overview
   4. Appendix D — Suggested Reading
   5. Appendix E — Templates & Sample Code Index
9. Back Matter
   1. Notes
   2. References
   3. Index
   4. Credits

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