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.
