Handbook of Research on Big Data Storage and Visualization Techniques (Advances in Data Mining and Database Management)

Richard S. Segall

ISBN 10: 1522531424 ISBN 13: 9781522531425

Editorial: IGI Global, 2018

Idioma: Ingl�s

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Detalles bibliogr�ficos

T�tulo

Handbook of Research on Big Data Storage and Visualization Techniques (Advances in Data Mining and Database Management)

Editor

IGI Global

Fecha de publicaci�n

2018

Idioma

Ingl�s

ISBN 10

1522531424

ISBN 13

9781522531425

Encuadernaci�n

Hardcover

Estado

Very Good

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Sinopsis

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

Rese�a del editor

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

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