Big Data A Tutorial-Based Approach
Big Data: A Tutorial-Based Approach explores the tools and techniques used to bring about the marriage of structured and unstructured data. It focuses on Hadoop Distributed Storage and MapReduce Processing by implementing (i) Tools and Techniques of Hadoop Eco System, (ii) Hadoop Distributed File System Infrastructure, and (iii) efficient MapReduce processing. The book includes Use Cases and Tutorials to provide an integrated approach that answers the ‘What’, ‘How’, and ‘Why’ of Big Data.
- Identifies the primary drivers of Big Data
- Walks readers through the theory, methods and technology of Big Data
- Explains how to handle the 4 V’s of Big Data in order to extract value for better business decision making
- Shows how and why data connectors are critical and necessary for Agile text analytics
- Includes in-depth tutorials to perform necessary set-ups, installation, configuration and execution of important tasks
- Explains the command line as well as GUI interface to a powerful data exchange tool between Hadoop and legacy r-dbms databases
Chapter 1: Introduction to Big Data
Chapter 2: Big Data Implementation
Chapter 3: Big Data Use Cases
Chapter 4: Big Data Migration
Chapter 5: Big Data Ingestion, Integration, and Management
Chapter 6: Big Data Repository
Chapter 7: Big Data Visualization
Chapter 8: Structured and Un-Structured Data Analytics
Chapter 9: Data Virtualization
Chapter 10: Cloud Computing
[Big Data: A Tutorial-Based Approach] is a well thought-out guide, comprising of tutorials and graphic illustrations, that builds an integrated approach which clearly answers the ‘What’ and the ‘How’ and the ‘Why’ of ‘Big Data’. It takes the readers on an inquisitive journey through the information wonderland of data lakes and provides the tools and techniques to bring about the marriage of structured and unstructured data.
It is a must-read primer that keeps its eyes always set on the end goal of extracting useful business insight from ‘Big Data’ by fully exploiting the potential of Hadoop Distributed File System Infrastructure, MapReduce processing, and Agile Data Analytics to implement proper Data Migration, Data Ingestion, Data Management, Data Analytics, Data Visualization and Data Virtualization processes.
Last but not the least, this book finally tests the readers on their understanding of ‘Big Data’ in the form of a QUIZ.
-Dr. Sohail Subhani, Winona State University