Includes bibliographical references and index.

Overview: Building data analytic systems with Hadoop -- A Scala and Python refresher -- Standard toolkits for Hadoop and analytics -- Relational, NoSQL, and graph databases -- Data pipelines and how to construct them -- Advanced search techniques with Hadoop, Lucene, and Solr -- An overview of analytical techniques and algorithms -- Rule engines, system control, and system orchestration -- Putting it all together: designing a complete analytical system -- Data visualizers: seeing and interacting with the analysis -- A case study in bioinformatics: analyzing microscope slide data -- A bayesian analysis component: identifying credit card fraud -- Searching for oil: geographical data analysis with Apache Mahout -- "Image as big data" systems: some case studies -- Building a general purpose data pipeline -- Conclusions and the future of big data analysis -- A setting up the distributed analytics environment -- Getting, installing, and running the example analytics system.

"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" -- All IT eBooks website.