Guide to Big Data Applications

Nonfiction, Computers, Computer Hardware, Input-Output Equipment, Science & Nature, Technology, Telecommunications
Cover of the book Guide to Big Data Applications by , Springer International Publishing
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Author: ISBN: 9783319538174
Publisher: Springer International Publishing Publication: May 25, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319538174
Publisher: Springer International Publishing
Publication: May 25, 2017
Imprint: Springer
Language: English

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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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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