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Guide to big data applications Edited by S. Srinivasan

Contributor(s): Material type: TextTextSeries: Studies in Big Data ; 26 | Studies in Big DataPublication details: New York, NY : Springer Science+Business Media, c2018.Description: xvii, 565 p. : ill. ; 25 cmISBN:
  • 9783319538167
Subject(s): DDC classification:
  • 005.7 GU ID
Online resources: Summary: This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.
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Holdings
Item type Current library Call number Status Notes Date due Barcode
REGULAR University of Wollongong in Dubai Main Collection 005.7 GU ID (Browse shelf(Opens below)) Available Mar2018 T0057894

This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

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