Big Data Essentials - PDF free download eBook

Introduction

This books fills the need for an easy and holistic book on essential Big Data technologies. Written in a lucid and simple language free from jargon and code, this book provides an intuition for Big...

Some brief overview of this book

This books fills the need for an easy and holistic book on essential Big Data technologies. Written in a lucid and simple language free from jargon and code, this book provides an intuition for Big Data from business as well as technological perspectives. This book is designed to provide the reader with the intuition behind this evolving area, along with a solid toolset of This books fills the need for an easy and holistic book on essential Big Data technologies.

Written in a lucid and simple language free from jargon and code, this book provides an intuition for Big Data from business as well as technological perspectives. This book is designed to provide the reader with the intuition behind this evolving area, along with a solid toolset of the major big data processing technologies such as Hadoop, MapReduce, Spark Streaming, and NoSql databases. A complete case study of developing a web log analyzer is included.

The book also contains two primers on Cloud computing and Data Mining. It also contains two tutorials on installing Hadoop and Spark. The book contains caselets from real-world stories.

Students across a variety of academic disciplines including business, computer science, statistics, engineering, and others attracted to the idea of harnessing Big Data for new insights and ideas from data, can use this as a textbook. Professionals in various domains, including executives, managers, analysts, professors, doctors, accountants, and others can use this book to learn in a few hours how to make the most of Big Data to monitor their infrastructure, discover new insights, and develop new data-based products. It is a flowing book that one can finish in one sitting, or one can return to it again and again for insights and techniques.

Table of Contents 1. Wholeness of Big Data 2. Big Data Applications 3.

Big Data Architectures 4. Distributed Systems with Hadoop 5. Parallel Programming with MapReduce 6.

Advanced NoSQL databases 7. Stream programming with Spark 8. Data Ingest with Kafka 9.

Cloud Computing Primer 10. Web Log Analyzer development 11. Data Mining Primer 12.

Appendix 1 on Installing Hadoop on AWS cloud 13. Appendix 2 on Installing Spark