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Applied big data analytics in operat...
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Kumar, Manish,
Applied big data analytics in operations management
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Applied big data analytics in operations management/ Manish Kumar [editor].
other author:
Kumar, Manish,
Published:
Hershey, Pennsylvania :IGI Global, : [2017],
Description:
1 online resource (250 p.) :ill. :
Subject:
Data mining. -
Online resource:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-0886-1
ISBN:
9781522508878 (ebk.)
Applied big data analytics in operations management
Applied big data analytics in operations management
[electronic resource] /Manish Kumar [editor]. - Hershey, Pennsylvania :IGI Global,[2017] - 1 online resource (250 p.) :ill.
Includes bibliographical references and index.
Big data in operation management / Arushi Jain, Vishal Bhatnagar -- Application of artificial neural networks in predicting the degradation of tram tracks using maintenance data / Sara Moridpour, Ehsan Mazloumi, Reyhaneh Hesami -- ZAMREN big data management (ZAMBiDM) envisaging efficiency and analytically manage IT resources / Jameson Mbale -- Predictive analytics in operations management / Harsh Jain, Amrit Pal, Manish Kumar -- Pros and cons of applying opinion mining on operation management: a big data perspective / Mahima Goyal, Vishal Bhatnagar -- A conceptual framework for educational system operation management synchronous with big data approach / Ganeshayya Ishwarayya Shidaganti, Prakash S -- Management of SME's semi structured data using semantic technique / Saravjeet Singh, Jaiteg Singh -- An overview of big data security with Hadoop framework / Jaya Singh, Ashish Maruti Gimekar, S. Venkatesan.
Restricted to subscribers or individual electronic text purchasers.
"This book addresses the issues surrounding the search for each organization's unique data management needs, defining the tools necessary to fulfill them within their technological ecosystem, along with the selection, interoperability, and integration of these tools"--Provided by publisher.
Mode of access: World Wide Web.
ISBN: 9781522508878 (ebk.)Subjects--Topical Terms:
528622
Data mining.
Subjects--Index Terms:
Business analytics
LC Class. No.: QA76.9.D343 / A67 2017e
Dewey Class. No.: 006.312
Applied big data analytics in operations management
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Applied big data analytics in operations management
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[electronic resource] /
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Manish Kumar [editor].
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Hershey, Pennsylvania :
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IGI Global,
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[2017]
300
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1 online resource (250 p.) :
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ill.
504
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Includes bibliographical references and index.
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Big data in operation management / Arushi Jain, Vishal Bhatnagar -- Application of artificial neural networks in predicting the degradation of tram tracks using maintenance data / Sara Moridpour, Ehsan Mazloumi, Reyhaneh Hesami -- ZAMREN big data management (ZAMBiDM) envisaging efficiency and analytically manage IT resources / Jameson Mbale -- Predictive analytics in operations management / Harsh Jain, Amrit Pal, Manish Kumar -- Pros and cons of applying opinion mining on operation management: a big data perspective / Mahima Goyal, Vishal Bhatnagar -- A conceptual framework for educational system operation management synchronous with big data approach / Ganeshayya Ishwarayya Shidaganti, Prakash S -- Management of SME's semi structured data using semantic technique / Saravjeet Singh, Jaiteg Singh -- An overview of big data security with Hadoop framework / Jaya Singh, Ashish Maruti Gimekar, S. Venkatesan.
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Restricted to subscribers or individual electronic text purchasers.
520
3
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"This book addresses the issues surrounding the search for each organization's unique data management needs, defining the tools necessary to fulfill them within their technological ecosystem, along with the selection, interoperability, and integration of these tools"--Provided by publisher.
530
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Also available in print.
538
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Mode of access: World Wide Web.
588
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Description based on title screen (IGI Global, viewed 10/12/2016).
650
0
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Data mining.
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528622
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Big data.
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Operations research.
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Business analytics
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Customer-centric business
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Educational systems
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Maintenance data
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Neural networks
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Opinion mining
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Predictive analytics
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Semi-structured data
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Kumar, Manish,
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editor.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-0886-1
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