1.5 补充资料

• “The AI Hierarchy of Needs”(https://oreil.ly/1RJOR) by Monica Rogati

• The AlphaGo research web page (https://oreil.ly/mNB6b)

• “Big Data Will Be Dead in Five Years”(https://oreil.ly/R2Rus) by Lewis Gavin

• Building Analytics Teams by John K.Thompson (Packt)

• Chapter 1 of What Is Data Engineering? by Lewis Gavin (O'Reilly)

• “Data as a Product vs.Data as a Service”(https://oreil.ly/iOUug) by Justin Gage

• “Data Engineering: A Quick and Simple Definition” (https://oreil.ly/eNAnS) by James Furbush (O'Reilly)

• Data Teams by Jesse Anderson (Apress)

• “Doing Data Science at Twitter”(https://oreil.ly/8rcYh) by Robert Chang

• “The Downfall of the Data Engineer” (https://oreil.ly/qxg6y) by Maxime Beauchemin

• “The Future of Data Engineering Is the Convergence of Disciplines” (https://oreil.ly/rDiqj) by Liam Hausmann

• “How CEOs Can Lead a Data-Driven Culture” (https://oreil.ly/7Kp6R) by Thomas H.Davenport and Nitin Mittal

• “How Creating a Data-Driven Culture Can Drive Success”(https://oreil.ly/UgzIZ) by Frederik Bussler

• The Information Management Body of Knowledge website (https://www.imbok.info)

• “Information Management Body of Knowledge”Wikipedia page (https://oreil.ly/Jk0KW)

• “Information Management”Wikipedia page (https://oreil.ly/SWj8k)

• “On Complexity in Big Data”(https://oreil.ly/r0jkK) by Jesse Anderson (O'Reilly)

• “OpenAI's New Language Generator GPT-3 Is Shockingly Good—and Completely Mindless”(https://oreil.ly/hKYeB) by Will Douglas Heaven

• “The Rise of the Data Engineer”(https://oreil.ly/R0QwP) by Maxime Beauchemin

• “A Short History of Big Data”(https://oreil.ly/BgzWe) by Mark van Rijmenam

• “Skills of the Data Architect”(https://oreil.ly/gImx2) by Bob Lambert

• “The Three Levels of Data Analysis:A Framework for Assessing Data Organization Maturity”(https://oreil.ly/bTTd0) by Emilie Schario

• “What Is a Data Architect? IT's Data Framework Visionary” (https://oreil.ly/2QBcv) by Thor Olavsrud

• “Which Profession Is More Complex to Become, a Data Engineer or a Data Scientist?”thread on Quora (https://oreil.ly/1MAR8)

• “Why CEOs Must Lead Big Data Initiatives” (https://oreil.ly/Zh4A0) by John Weathington

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[1]“Data Engineering and Its Main Concepts,”AlexSoft，最近更新于2021年8月26日，https://oreil.ly/e94py。

[2]ETL代表抽取（extract）、转换（transform）、加载（load），这是我们在本书中介绍的一种常见模式。

[3]Jesse Anderson,“The Two Types of Data Engineering,”June 27, 2018, https://oreil.ly/dxDt6.

[4]Maxime Beauchemin,“The Rise of the Data Engineer,”January 20, 2017, https://oreil.ly/kNDmd.

[5]Lewis Gavin, What Is Data Engineering? (Sebastapol, CA:O'Reilly, 2020), https://oreil.ly/ELxLi.

[6]Cade Metz,“How Yahoo Spawned Hadoop, the Future of Big Data,”Wired, October 18, 2011, https://oreil.ly/iaD9G.

[7]Ron Miller,“How AWS Came to Be,”TechCrunch, July 2, 2016, https://oreil.ly/VJehv.

[8]DataOps是数据运维（Data Operations）的缩写。我们将在第2章中介绍这个主题。要了解更多信息，请阅读DataOps Manifesto（https://oreil.ly/jGoHM）。

[9]这些首字母缩略词分别代表《加利福尼亚消费者隐私法案》（California Consumer Privacy Act）和《通用数据保护条例》（General Data Protection Regulation）。

[10]Robert Chang,“Doing Data Science at Twitter,”Medium, June 20, 2015, https://oreil.ly/xqjAx.

[11]Paramita (Guha) Ghosh,“Data Architect vs.Data Engineer,”Dataversity, November 12, 2021,https://oreil.ly/TlyZY.

[12]这个概念有多种参考。尽管这种陈词滥调广为人知，但围绕其在不同实际环境中的有效性展开了一场有益的辩论。更多详细信息，请参阅Leigh Dodds,“Do Data Scientists Spend 80% of Their Time Cleaning Data? Turns Out, No?”Lost Boy博客，January 31, 2020, https://oreil.ly/szFww，以及Alex Woodie,“Data Prep Still Dominates Data Scientists'Time, Survey Finds,”Datanami, July 6, 2020, https://oreil.ly/jDVWF。