Pro Hadoop Data Analytics - Designing and Building Big Data Systems using the Hadoop Ecosystem

Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation.
In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.
The book emphasizes four important topics:

• The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. 
Best practices and structured design principles. This will include strategic topics as well as the how to example portions.
• The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples.
Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system.

What You'll Learn 

• The what, why, and how of building big data analytic systems with the Hadoop ecosystem
• Libraries, toolkits, and algorithms to make development easier and more effective
• Best practices to use when building analytic systems with Hadoop, and metrics to measure performance and efficiency of components and systems
• How to connect to standard relational databases, noSQL data sources, and more
Useful case studies and example components which assist you in creating your own systems

Who This Book Is For

Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.

Kerry Koitzsch is a software engineer and student of history interested in the early history of science, particularly chemistry. He frequently publishes papers and attends conferences on scientific and historical topics, including early chemistry and alchemy, sociology of science, and other historical subjects. He has presented many lectures, talks, and demonstrations on a variety of subjects for the United States Army, the Society for Utopian Studies, American Association for Artificial Intelligence (AAAI), Association for Studies in Esotericism (ASE), and others, and has published many papers, with two books on historical subjects to be published in 2016. His most recent published work is a chapter in 'The Individual and Utopia', a collection of sociological papers, published by Ashgate Press.

He was educated at Interlochen Arts Academy, MIT, and the San Francisco Conservatory of Music. He served in the United States Army and United States Army Reserve, and is the recipient of the United States Army Achievement Medal.  For the last thirty years he has been a software engineer specializing in computer vision, machine learning, and database technologies, and currently lives and works in Sunnyvale, California.