Big Data Technologies and Applications
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Beschreibung
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®) 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.
Describes real-life solutions using big data analytics Focuses on LexisNexis’ platform and its solutions to big data Covers wide-ranging applications such as security, fraud, and machine learning Includes supplementary material: sn.pub/extras
Autor*in
Borko Furht
Themen in »Big Data Technologies and Applications«
Big data technologies Big data applications HPCC systems Big data analytics Big data components Visualization of big data Models of big data Social network analytics ECL language Big data software Machine learning techniques Deep learning techniques Data security and privacy Data intensive supercomputing
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“The book offers a good overview of big data technologies, which keeps a live link between theoretical background and live applications. As such, the text rises up as a starting point for engineers and researchers in the field of big data applications.” (Alexander Tzanov, Computing Reviews, June, 2017)
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