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'''Data science''' is an [[inter-disciplinary]] field that uses scientific methods, processes, algorithms and systems to extract [[knowledge]] and insights from many structural and [[unstructured data]].<ref>{{Cite journal | last1 = Dhar | first1 = V. | title = Data science and prediction | doi = 10.1145/2500499 | journal = Communications of the ACM | volume = 56 | issue = 12 | pages = 64–73 | year = 2013 | pmid =  | pmc =  | url = http://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/fulltext | access-date = 2 September 2015 | archive-url = https://web.archive.org/web/20141109113411/http://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/fulltext | archive-date = 9 November 2014 | url-status = live }}</ref><ref>{{cite web | url=http://simplystatistics.org/2013/12/12/the-key-word-in-data-science-is-not-data-it-is-science/ | title=The key word in "Data Science" is not Data, it is Science | publisher=Simply Statistics | date=2013-12-12 | author=[[Jeffrey T. Leek|Jeff Leek]] | access-date=1 January 2014 | archive-url=https://web.archive.org/web/20140102194117/http://simplystatistics.org/2013/12/12/the-key-word-in-data-science-is-not-data-it-is-science/ | archive-date=2 January 2014 | url-status=live }}</ref> Data science is related to [[data mining]] and [[big data]].
 
'''Data science''' is an [[inter-disciplinary]] field that uses scientific methods, processes, algorithms and systems to extract [[knowledge]] and insights from many structural and [[unstructured data]].<ref>{{Cite journal | last1 = Dhar | first1 = V. | title = Data science and prediction | doi = 10.1145/2500499 | journal = Communications of the ACM | volume = 56 | issue = 12 | pages = 64–73 | year = 2013 | pmid =  | pmc =  | url = http://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/fulltext | access-date = 2 September 2015 | archive-url = https://web.archive.org/web/20141109113411/http://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/fulltext | archive-date = 9 November 2014 | url-status = live }}</ref><ref>{{cite web | url=http://simplystatistics.org/2013/12/12/the-key-word-in-data-science-is-not-data-it-is-science/ | title=The key word in "Data Science" is not Data, it is Science | publisher=Simply Statistics | date=2013-12-12 | author=[[Jeffrey T. Leek|Jeff Leek]] | access-date=1 January 2014 | archive-url=https://web.archive.org/web/20140102194117/http://simplystatistics.org/2013/12/12/the-key-word-in-data-science-is-not-data-it-is-science/ | archive-date=2 January 2014 | url-status=live }}</ref> Data science is related to [[data mining]] and [[big data]].
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Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining and big data.
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   --[[用户:趣木木|趣木木]]([[用户讨论:趣木木|讨论]])下为旧版相对应的引言内容的参考 可进行一下整及或填充
 
   --[[用户:趣木木|趣木木]]([[用户讨论:趣木木|讨论]])下为旧版相对应的引言内容的参考 可进行一下整及或填充
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Data science is a "concept to unify [[statistics]], [[data analysis]], [[machine learning]] and their related methods" in order to "understand and analyze actual phenomena" with data.<ref>{{Cite book|chapter-url=https://www.springer.com/book/9784431702085|title=Data Science, Classification, and Related Methods|last=Hayashi|first=Chikio|date=1998-01-01|publisher=Springer Japan|isbn=9784431702085|editor-last=Hayashi|editor-first=Chikio|series=Studies in Classification, Data Analysis, and Knowledge Organization|location=|pages=40–51|language=en|chapter=What is Data Science? Fundamental Concepts and a Heuristic Example|doi=10.1007/978-4-431-65950-1_3|editor-last2=Yajima|editor-first2=Keiji|editor-last3=Bock|editor-first3=Hans-Hermann|editor-last4=Ohsumi|editor-first4=Noboru|editor-last5=Tanaka|editor-first5=Yutaka|editor-last6=Baba|editor-first6=Yasumasa}}</ref> It uses techniques and theories drawn from many fields within the context of [[mathematics]], [[statistics]], [[computer science]], and [[information science]]. [[Turing award]] winner [[Jim Gray (computer scientist)|Jim Gray]] imagined data science as a "fourth paradigm" of science ([[Empirical research|empirical]], [[Basic research|theoretical]], [[computational science|computational]] and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the [[information explosion|data deluge]].<ref name="TansleyTolle2009">{{cite book|author1=Stewart Tansley|author2=Kristin Michele Tolle|title=The Fourth Paradigm: Data-intensive Scientific Discovery|url=https://books.google.com/?id=oGs_AQAAIAAJ|year=2009|publisher=Microsoft Research|isbn=978-0-9825442-0-4|access-date=16 December 2016|archive-url=https://web.archive.org/web/20170320193019/https://books.google.com/books?id=oGs_AQAAIAAJ|archive-date=20 March 2017|url-status=live}}</ref><ref name="BellHey2009">{{cite journal|last1=Bell|first1=G.|last2=Hey|first2=T.|last3=Szalay|first3=A.|title=COMPUTER SCIENCE: Beyond the Data Deluge|journal=Science|volume=323|issue=5919|year=2009|pages=1297–1298|issn=0036-8075|doi=10.1126/science.1170411|pmid=19265007}}</ref>
 
Data science is a "concept to unify [[statistics]], [[data analysis]], [[machine learning]] and their related methods" in order to "understand and analyze actual phenomena" with data.<ref>{{Cite book|chapter-url=https://www.springer.com/book/9784431702085|title=Data Science, Classification, and Related Methods|last=Hayashi|first=Chikio|date=1998-01-01|publisher=Springer Japan|isbn=9784431702085|editor-last=Hayashi|editor-first=Chikio|series=Studies in Classification, Data Analysis, and Knowledge Organization|location=|pages=40–51|language=en|chapter=What is Data Science? Fundamental Concepts and a Heuristic Example|doi=10.1007/978-4-431-65950-1_3|editor-last2=Yajima|editor-first2=Keiji|editor-last3=Bock|editor-first3=Hans-Hermann|editor-last4=Ohsumi|editor-first4=Noboru|editor-last5=Tanaka|editor-first5=Yutaka|editor-last6=Baba|editor-first6=Yasumasa}}</ref> It uses techniques and theories drawn from many fields within the context of [[mathematics]], [[statistics]], [[computer science]], and [[information science]]. [[Turing award]] winner [[Jim Gray (computer scientist)|Jim Gray]] imagined data science as a "fourth paradigm" of science ([[Empirical research|empirical]], [[Basic research|theoretical]], [[computational science|computational]] and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the [[information explosion|data deluge]].<ref name="TansleyTolle2009">{{cite book|author1=Stewart Tansley|author2=Kristin Michele Tolle|title=The Fourth Paradigm: Data-intensive Scientific Discovery|url=https://books.google.com/?id=oGs_AQAAIAAJ|year=2009|publisher=Microsoft Research|isbn=978-0-9825442-0-4|access-date=16 December 2016|archive-url=https://web.archive.org/web/20170320193019/https://books.google.com/books?id=oGs_AQAAIAAJ|archive-date=20 March 2017|url-status=live}}</ref><ref name="BellHey2009">{{cite journal|last1=Bell|first1=G.|last2=Hey|first2=T.|last3=Szalay|first3=A.|title=COMPUTER SCIENCE: Beyond the Data Deluge|journal=Science|volume=323|issue=5919|year=2009|pages=1297–1298|issn=0036-8075|doi=10.1126/science.1170411|pmid=19265007}}</ref>
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Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science. Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.
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数据科学类似于[https://en.wikipedia.org/wiki/Data_mining 数据挖掘],是一个通过科学的方法、过程、算法和系统,从有结构或无结构的各种形式的[https://en.wikipedia.org/wiki/Data 数据]中提炼[https://en.wikipedia.org/wiki/Knowledge 知识]和见解的跨学科领域。
 
数据科学类似于[https://en.wikipedia.org/wiki/Data_mining 数据挖掘],是一个通过科学的方法、过程、算法和系统,从有结构或无结构的各种形式的[https://en.wikipedia.org/wiki/Data 数据]中提炼[https://en.wikipedia.org/wiki/Knowledge 知识]和见解的跨学科领域。
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