فهرست مطالب

• Copyright
• Table of Contents
• Foreword
• Preface
• Part I. Foundation
• Chapter 1. Big Data
• What Is Big Data, and How Can It Help You?
• Data Maturity
• Self-Service Business Intelligence
• Summary
• Chapter 2. Types of Data Architectures
• Evolution of Data Architectures
• Relational Data Warehouse
• Data Lake
• Modern Data Warehouse
• Data Fabric
• Data Lakehouse
• Data Mesh
• Summary
• Chapter 3. The Architecture Design Session
• What Is an ADS?
• Why Hold an ADS?
• Before the ADS
• Conducting the ADS
• After the ADS
• Tips for Conducting an ADS
• Summary
• Part II. Common Data Architecture Concepts
• Chapter 4. The Relational Data Warehouse
• What Is a Relational Data Warehouse?
• What a Data Warehouse Is Not
• The Top-Down Approach
• Why Use a Relational Data Warehouse?
• Drawbacks to Using a Relational Data Warehouse
• Populating a Data Warehouse
• The Death of the Relational Data Warehouse Has Been Greatly Exaggerated
• Summary
• Chapter 5. Data Lake
• What Is a Data Lake?
• Why Use a Data Lake?
• Bottom-Up Approach
• Best Practices for Data Lake Design
• Multiple Data Lakes
• Summary
• Chapter 6. Data Storage Solutions and Processes
• Data Storage Solutions
• Data Processes
• Summary
• Chapter 7. Approaches to Design
• Online Transaction Processing Versus Online Analytical Processing
• Operational and Analytical Data
• Symmetric Multiprocessing and Massively Parallel Processing
• Lambda Architecture
• Kappa Architecture
• Polyglot Persistence and Polyglot Data Stores
• Summary
• Chapter 8. Approaches to Data Modeling
• Relational Modeling
• Dimensional Modeling
• Common Data Model
• Data Vault
• The Kimball and Inmon Data Warehousing Methodologies
• Methodology Myths
• Summary
• Chapter 9. Approaches to Data Ingestion
• ETL Versus ELT
• Reverse ETL
• Batch Processing Versus Real-Time Processing
• Data Governance
• Summary
• Part III. Data Architectures
• Chapter 10. The Modern Data Warehouse
• The MDW Architecture
• Pros and Cons of the MDW Architecture
• Combining the RDW and Data Lake
• Stepping Stones to the MDW
• Case Study: Wilson & Gunkerk’s Strategic Shift to an MDW
• Summary
• Chapter 11. Data Fabric
• The Data Fabric Architecture
• Why Transition from an MDW to a Data Fabric Architecture?
• Potential Drawbacks
• Summary
• Chapter 12. Data Lakehouse
• Delta Lake Features
• Performance Improvements
• The Data Lakehouse Architecture
• What If You Skip the Relational Data Warehouse?
• Relational Serving Layer
• Summary
• Chapter 13. Data Mesh Foundation
• A Decentralized Data Architecture
• Data Mesh Hype
• Dehghani’s Four Principles of Data Mesh
• The “Pure” Data Mesh
• Data Domains
• Data Mesh Logical Architecture
• Different Topologies
• Data Mesh Versus Data Fabric
• Use Cases
• Summary
• Chapter 14. Should You Adopt Data Mesh? Myths, Concerns, and the Future
• Myths
• Concerns
• Organizational Assessment: Should You Adopt a Data Mesh?
• Recommendations for Implementing a Successful Data Mesh
• The Future of Data Mesh
• Zooming Out: Understanding Data Architectures and Their Applications
• Summary
• Part IV. People, Processes, and Technology
• Chapter 15. People and Processes
• Team Organization: Roles and Responsibilities
• Why Projects Fail: Pitfalls and Prevention
• Tips for Success
• Summary
• Chapter 16. Technologies
• Choosing a Platform
• Cloud Service Models
• Software Frameworks
• Summary
• Index
• About the Author
• Colophon