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Highlighting the Importance of Big Data Management and Analysis for Various Applications [electronic resource] /

Contributor(s): Moshirpour, Mohammad [editor.] | Far, Behrouz [editor.] | Alhajj, Reda [editor.] | SpringerLink (Online service).
Series: Studies in Big Data: 27Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: VI, 168 p. 29 illus., 11 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319602554.Subject(s): Computer Engineering | Sociophysics | Econophysics | Big Data/Analytics | Data-driven Science, Modeling and Theory BuildingDDC classification: 658.4038 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.) In: Springer Nature eBookSummary: This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field. .
List(s) this item appears in: Springer Nature eBooks
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This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field. .

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