目錄
Preface.
Part Ⅰ. Foundation and Building Blocks
1. Data Engineering Described..
What Is Data Engineering?
Data Engineering Defined
The Data Engineering Lifecycle
Evolution of the Data Engineer
Data Engineering and Data Science
Data Engineering Skills and Activities
Data Maturity and the Data Engineer
The Background and Skills of a Data Engineer
Business Responsibilities
Technical Responsibilities
The Continuum of Data Engineering Roles, from A to B
Data Engineers Inside an Organization
Internal-Facing Versus External-Facing Data Engineers
Data Engineers and Other Technical Roles
Data Engineers and Business Leadership
Conclusion
Additional Resources
2. The Data Engineering Lifecycle..
What Is the Data Engineering Lifecycle?
The Data Lifecycle Versus the Data Engineering Lifecycle
Generation: Source Systems
Storage
Ingestion
Transformation
Serving Data
Major Undercurrents Across the Data Engineering Lifecycle
Security
Data Management
DataOps
Data Architecture
Orchestration
Software Engineering
Conclusion
Additional Resources
3. Designing Good Data Architecture..
What Is Data Architecture?
Enterprise Architecture Defined
Data Architecture Defined
"Good" Data Architecture
Principles of Good Data Architecture
Principle 1: Choose Common Components Wisely
Principle 2: Plan for Failure
Principle 3: Architect for Scalability
Principle 4: Architecture Is Leadership
Principle 5: Always Be Architecting
Principle 6: Build Loosely Coupled Systems
Principle 7: Make Reversible Decisions
Principle 8: Prioritize Security
Principle 9: Embrace FinOps
Major Architecture Concepts
Domains and Services
Distributed Systems, Scalability, and Designing for Failure
Tight Versus Loose Coupling: Tiers, Monoliths, and Microservices
User Access: Single Versus Multitenant
Event-Driven Architecture
Brownfield Versus Greenfield Projects
Examples and Types of Data Architecture
Data Warehouse
Data Lake
Convergence, Next-Generation Data Lakes, and the Data Platform
Modern Data Stack
Lambda Architecture
……
Part Ⅱ The Data Engineering Lifecycle in Depth
Part Ⅲ Security,Privacy,and the Future of Data Engineering
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