Big Data Technologies and Applications (Paperback, Softcover reprint of the original 1st ed. 2016)

The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems (R)) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	June 2018
First published:	2016
Authors:	Borko Furht • Flavio Villanustre
Dimensions:	235 x 155 x 26mm (L x W x T)
Format:	Paperback
Pages:	400
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-83077-3
Categories:	Books > Computing & IT > Computer programming > Software engineering Books > Computing & IT > Computer communications & networking > General Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Promotions
LSN:	3-319-83077-5
Barcode:	9783319830773

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