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001 978-3-319-95092-1
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020 _a9783319950921
_9978-3-319-95092-1
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072 7 _aUNF
_2bicssc
072 7 _aCOM021030
_2bisacsh
072 7 _aUNF
_2thema
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082 0 4 _a006.312
_223
100 1 _aCao, Longbing.
_eauthor.
_0(orcid)0000-0002-2396-0405
_1https://orcid.org/0000-0002-2396-0405
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aData Science Thinking
_h[electronic resource] :
_bThe Next Scientific, Technological and Economic Revolution /
_cby Longbing Cao.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXX, 390 p. 62 illus., 61 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aData Analytics,
_x2520-1859
500 _aAcceso multiusuario
505 0 _a1 The Data Science Era -- 2 What is Data Science -- 3 Data Science Thinking -- 4 Data Science Challenges -- 5 Data Science Discipline -- 6 Data Science Foundations -- 7 Data Science Techniques -- 8 Data Economy and Industrialization -- 9 Data Science Applications -- 10 Data Profession -- 11 Data Science Education -- 12 Prospects and Opportunities in Data Science.
520 _aThis book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. The topics cover an extremely wide spectrum of essential and relevant aspects of data science, spanning its evolution, concepts, thinking, challenges, discipline, and foundation, all the way to industrialization, profession, education, and the vast array of opportunities that data science offers. The book's three parts each detail layers of these different aspects. The book is intended for decision-makers, data managers (e.g., analytics portfolio managers, business analytics managers, chief data analytics officers, chief data scientists, and chief data officers), policy makers, management and decision strategists, research leaders, and educators who are responsible for pursuing new scientific, innovation, and industrial transformation agendas, enterprise strategic planning, a next-generation profession-oriented course development, as well as those who are involved in data science, technology, and economy from an advanced perspective. Research students in data science-related courses and disciplines will find the book useful for positing their innovative scientific journey, planning their unique and promising career, and competing within and being ready for the next generation of science, technology, and economy.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aData mining.
650 0 _aBig data.
650 0 _aArtificial intelligence.
650 1 4 _aData Mining and Knowledge Discovery.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I18030
650 2 4 _aBig Data/Analytics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/522070
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319950914
776 0 8 _iPrinted edition:
_z9783319950938
776 0 8 _iPrinted edition:
_z9783030069759
830 0 _aData Analytics,
_x2520-1859
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-95092-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cLIBRO_ELEC
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