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Bahga A., Madisetti V. Big Data Analytics: A Hands-On Approach

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Bahga A., Madisetti V. Big Data Analytics: A Hands-On Approach
Arshdeep Bahga & Vijay Madisetti, 2019. — 542 p. — ISBN 978-1-949978-00-1.
We are living in the dawn of what has been termed as the "Fourth Industrial Revolution", which is marked through the emergence of "cyber-physical systems" where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT). Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This new area of technology has been defined as Big Data Analytics, and the industrial and academic communities are realizing this as a competitive technology that can generate significant new wealth and opportunity. Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. Big data analytics deals with collection, storage, processing and analysis of massive-scale data. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. We have written this textbook, as part of our expanding "A Hands-On Approach"(TM) series, to meet this need at colleges and universities, and also for big data service providers who may be interested in offering a broader perspective of this emerging field to accompany their customer and developer training programs. The typical reader is expected to have completed a couple of courses in programming using traditional high-level languages at the college-level, and is either a senior or a beginning graduate student in one of the science, technology, engineering or mathematics (STEM) fields.
Contents
Big data analytics concepts
Introduction to Big Data
Setting up Big Data Stack
Big Data Patterns
NoSQL
Big data analytics implementations
Data Acquisition
Big Data Storage
Batch Analysis
Real-time Analysis
Interactive Querying
Serving Databases & Web Frameworks
Advanced topics
Analytics Algorithms
Data Visualization
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