Learn advanced analytical techniques and leverage existing tool kits 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 that go beyond the basics of classification, clustering, and recommendation.

Pro Hadoop Data Analytics emphasizes best practices to ensure coherent, efficient development. A complete example system will be developed using standard third-party components that consist of the tool kits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.

The book also highlights the importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. You'll discover the importance of mix-and-match or hybrid systems, using different analytical components in one application. This hybrid approach will be prominent in the examples.

What You'll Learn 

Build big data analytic systems with the Hadoop ecosystemUse libraries, tool kits, and algorithms to make development easier and more effectiveApply metrics to measure performance and efficiency of components and systemsConnect to standard relational databases, noSQL data sources, and moreFollow case studies with example components to create your own systemsWho 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 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, and sociology of science. 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. He has also published several papers and written two historical books.
Kerry 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. He has been a software engineer specializing in computer vision, machine learning, and database technologies for 30 years, and currently lives and works in Sunnyvale, California.

Chapter 1: Overview: Building Data Analytic Systems with Hadoop.- Chapter 2: A Scala and Python Refresher.- Chapter 3: Standard Toolkits for Hadoop and Analytics.- Chapter 4: Relational, noSQL, and Graph Databases.- Chapter 5: Data Pipelines and How to Construct Them.- Chapter 6: Advanced Search Techniques with Hadoop, Lucene, and Solr.- Chapter 7: An Overview of Analytical Techniques and Algorithms.- Chapter 8: Rule Engines, System Control, and System Orchestration.- Chapter 9: Putting it All Together: Designing a Complete Analytical System.- Chapter 10: Data Visualizers: Seeing and Interacting with the Analysis.- Chapter 11: A Case Study in Bioinformatics: Analyzing Microscope Slide Data.- Chapter 12: A Bayesian Analysis Software Component: Identifying Credit Card Fraud.- Chapter 13: Searching for Oil: Geological Data Analysis with Mahout.- Chapter 14: Image as Big Data Systems: Some Case Studies.- Chapter 15:A Generic Data Pipeline Analytical System.- Chapter 16: Conclusions and The Future of Big Data Analysis.