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.
Features
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
Features
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
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