数据工程基础(影印版)

数据工程在过去十年间发展迅速，许多软件工 程师、数据科学家和分析师都在寻找相关实践的全 面观点。通过这本实践用书，你将学习如何通过评 估数据工程生命周期框架中可用的最佳技术来规划 和构建系统，以满足你的组织和客户的需求。 作者Joe Reis和Matt Housley将为你介绍数 据工程的生命周期，向你展示如何综合运用各种云 技术，以满足下游数据消费者的需求。你将理解如 何应用数据生成、摄取、编排、转换、存储和治理 的概念，无论底层技术是什么，这些概念在任何数 据环境中都至关重要。

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