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Enterprise big data engineering, ana...
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Atzmueller, Martin,
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Enterprise big data engineering, analytics, and management
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Enterprise big data engineering, analytics, and management/ Martin Atzmueller, Samia Oussena and Thomas Roth-Berghofer, editors.
其他作者:
Atzmueller, Martin,
出版者:
Hershey, Pennsylvania :IGI Global, : [2016],
面頁冊數:
1 online resource (272 p.) :ill.
內容註:
How big does big data need to be? / Martin Stange, Burkhardt Funk -- Strategic management of data and challenges for organizations: strategy development and business value / Stephen Andrew Roberts, Bruce Laurie -- Data stream mining of event and complex event streams: a survey of existing and future technologies and applications in big data / Chris Wrench [and 4 others] -- Research challenges in big data analytics / Sivamathi Chokkalingam, Vijayarani S. -- Descriptive and predictive analytical methods for big data / Sema A. Kalaian, Rafa M. Kasim, Nabeel R. Kasim -- A framework to analyze enterprise social network data / Janine Viol Hacker, Freimut Bodendorf, Pascal Lorenz -- Big data analytics using local exceptionality detection / Martin Atzmueller, Dennis Mollenhauer, Andreas Schmidt -- Statistical features for extractive automatic text summarization / Yogesh Kumar Meena, Dinesh Gopalani -- Data modeling and knowledge discovery in process industries / Benjamin Klöpper [and 3 others] -- Data preparation for big data analytics: methods and experiences / Andreas Schmidt, Martin Atzmueller, Martin Hollender -- Semantification of large corpora of technical documentation / Sebastian Furth, Joachim Baumeister -- Application of complex event processing techniques to big data related to healthcare: a systematic literature review of case studies / Fehmida Mohamedali, Samia Oussena -- Using big data in collaborative learning / Liz Sokolowski, Samia Oussena.
標題:
Big data. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-0293-7
ISBN:
9781522502944 (ebk.)
Enterprise big data engineering, analytics, and management
Enterprise big data engineering, analytics, and management
[electronic resource] /Martin Atzmueller, Samia Oussena and Thomas Roth-Berghofer, editors. - Hershey, Pennsylvania :IGI Global,[2016] - 1 online resource (272 p.) :ill.
Includes bibliographical references and index.
How big does big data need to be? / Martin Stange, Burkhardt Funk -- Strategic management of data and challenges for organizations: strategy development and business value / Stephen Andrew Roberts, Bruce Laurie -- Data stream mining of event and complex event streams: a survey of existing and future technologies and applications in big data / Chris Wrench [and 4 others] -- Research challenges in big data analytics / Sivamathi Chokkalingam, Vijayarani S. -- Descriptive and predictive analytical methods for big data / Sema A. Kalaian, Rafa M. Kasim, Nabeel R. Kasim -- A framework to analyze enterprise social network data / Janine Viol Hacker, Freimut Bodendorf, Pascal Lorenz -- Big data analytics using local exceptionality detection / Martin Atzmueller, Dennis Mollenhauer, Andreas Schmidt -- Statistical features for extractive automatic text summarization / Yogesh Kumar Meena, Dinesh Gopalani -- Data modeling and knowledge discovery in process industries / Benjamin Klöpper [and 3 others] -- Data preparation for big data analytics: methods and experiences / Andreas Schmidt, Martin Atzmueller, Martin Hollender -- Semantification of large corpora of technical documentation / Sebastian Furth, Joachim Baumeister -- Application of complex event processing techniques to big data related to healthcare: a systematic literature review of case studies / Fehmida Mohamedali, Samia Oussena -- Using big data in collaborative learning / Liz Sokolowski, Samia Oussena.
Restricted to subscribers or individual electronic text purchasers.
"This book presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation"--Provided by publisher.
Mode of access: World Wide Web.
ISBN: 9781522502944 (ebk.)Subjects--Topical Terms:
2045508
Big data.
Subjects--Index Terms:
Automatic text summarization (ATS)
LC Class. No.: QA76.9.B45 / E58 2016e
Dewey Class. No.: 005.7
Enterprise big data engineering, analytics, and management
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Martin Atzmueller, Samia Oussena and Thomas Roth-Berghofer, editors.
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How big does big data need to be? / Martin Stange, Burkhardt Funk -- Strategic management of data and challenges for organizations: strategy development and business value / Stephen Andrew Roberts, Bruce Laurie -- Data stream mining of event and complex event streams: a survey of existing and future technologies and applications in big data / Chris Wrench [and 4 others] -- Research challenges in big data analytics / Sivamathi Chokkalingam, Vijayarani S. -- Descriptive and predictive analytical methods for big data / Sema A. Kalaian, Rafa M. Kasim, Nabeel R. Kasim -- A framework to analyze enterprise social network data / Janine Viol Hacker, Freimut Bodendorf, Pascal Lorenz -- Big data analytics using local exceptionality detection / Martin Atzmueller, Dennis Mollenhauer, Andreas Schmidt -- Statistical features for extractive automatic text summarization / Yogesh Kumar Meena, Dinesh Gopalani -- Data modeling and knowledge discovery in process industries / Benjamin Klöpper [and 3 others] -- Data preparation for big data analytics: methods and experiences / Andreas Schmidt, Martin Atzmueller, Martin Hollender -- Semantification of large corpora of technical documentation / Sebastian Furth, Joachim Baumeister -- Application of complex event processing techniques to big data related to healthcare: a systematic literature review of case studies / Fehmida Mohamedali, Samia Oussena -- Using big data in collaborative learning / Liz Sokolowski, Samia Oussena.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-0293-7
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