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第171行： − 数据科学是一个跨学科的领域，专注于从数据集中提取知识，这些数据集通常都很大(见大数据)。这个领域包括分析，为分析准备数据，以及为组织的高层决策提供结果。因此，它融合了来自计算机科学、数学、统计学、信息可视化、平面设计和商业的技能。统计学家 Nathan Yau 借鉴 Ben Fry 的观点，也把数据科学和人机交互联系起来: 用户应该能够直观地控制和探索数据。2015年，美国统计协会确定数据库管理、统计和机器学习，以及分布式和并行系统为三个新兴的基础专业社区。+ − + − + − + − + − + − −
→Foundations背景
Data science is an interdisciplinary field focused on extracting knowledge from data sets, which are typically large (see big data). The field encompasses analysis, preparing data for analysis, and presenting findings to inform high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic design, and business. Statistician Nathan Yau, drawing on Ben Fry, also links data science to human-computer interaction: users should be able to intuitively control and explore data. In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.
Data science is an interdisciplinary field focused on extracting knowledge from data sets, which are typically large (see big data). The field encompasses analysis, preparing data for analysis, and presenting findings to inform high-level decisions in an organization. As such, it incorporates skills from computer science, mathematics, statistics, information visualization, graphic design, and business. Statistician Nathan Yau, drawing on Ben Fry, also links data science to human-computer interaction: users should be able to intuitively control and explore data. In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.
数据科学是一个跨学科的领域，致力于从数据集中提取知识，这些数据集通常都很大(请参阅[[大数据]])。<ref>
{{Cite web|url=http://www.datascienceassn.org/about-data-science|title=About Data Science {{!}} Data Science Association|website=www.datascienceassn.org|access-date=2020-04-03}}
</ref> 该领域包括分析，准备分析数据，及呈现结果，以此为组织的高层决策提供依据。因此，它融合了来自计算机科学、数学、统计学、信息可视化、图形设计和商业技能。<ref>{{Cite web|url=https://www.oreilly.com/library/view/doing-data-science/9781449363871/ch01.html|title=1. Introduction: What Is Data Science? - Doing Data Science [Book]|website=www.oreilly.com|language=en|access-date=2020-04-03}}</ref><ref>{{Cite web|url=https://medriscoll.com/post/4740157098/the-three-sexy-skills-of-data-geeks|title=the three sexy skills of data geeks|website=m.e.driscoll: data utopian|language=en|access-date=2020-04-03}}
</ref>统计学家丘南森 Nathan Yau 借鉴本•弗莱 Ben Fry 的观点，将数据科学和[[人机交互]]联系起来: 用户应该能够直观地控制和探索数据。<ref>
{{Cite web|url=https://flowingdata.com/2009/06/04/rise-of-the-data-scientist/|title=Rise of the Data Scientist|last=Yau|first=Nathan|date=2009-06-04|website=FlowingData|language=en|access-date=2020-04-03}}</ref><ref>{{Cite web|url=https://benfry.com/phd/dissertation/2.html|title=Basic Example|last=|first=|date=|website=benfry.com|url-status=live|archive-url=|archive-date=|access-date=2020-04-03}}
</ref> 2015年，美国统计协会 the American Statistical Association 确定数据库管理、统计和机器学习，以及分布式和并行系统为三个新兴的基础专业社区。<ref>{{Cite web|url=https://magazine.amstat.org/blog/2015/10/01/asa-statement-on-the-role-of-statistics-in-data-science/|title=ASA Statement on the Role of Statistics in Data Science|date=2015-10-01|website=AMSTATNEWS|publisher=[[American Statistical Association]]|access-date=2019-05-29|archive-url=https://web.archive.org/web/20190620184935/https://magazine.amstat.org/blog/2015/10/01/asa-statement-on-the-role-of-statistics-in-data-science/|archive-date=20 June 2019|url-status=live}}</ref>
== Etymology 术语词义衍变==
== Etymology 术语词义衍变==