Practical Data Science With Hadoop and Spark ─ Designing and Building Effective Analytics at Scale

As adoption of Hadoop accelerates in the enterprise and beyond, there's soaring demand for those who can solve real world problems by applying advanced data science techniques in Hadoop environments. Now there's a complete and up-to-date guide to data science with Hadoop: high-level concepts, deep-dive techniques, practical applications, hands-on tutorials, and real-world use cases. Drawing on their immense experience with Hadoop in enterprise Big Data environments, this book's authors bring together all the practical knowledge you'll need to do real, useful data science with Hadoop. Coverage includes:

• What data science is, what data scientists do, and how to build or join a data science team
• Core data science applications in retail, healthcare, insurance, banking, education, and beyond
• How Hadoop has evolved into an outstanding environment for doing data science
• A day in the life of a data scientist: exploration, iteration, and more
• Getting your data into Hadoop: data lakes, Sqoop, Flume, Falcon, and more
• Preparing your data, from start to finish
• Data modeling and machine learning
• Visualization: how (and how not) to use it
• Start-to-finish case studies: recommender systems, customer segmentation, sentiment analysis, and predictive risk modeling
• The future: Storm online scoring, GIRAPH graph algorithms, Solr/Elastic search, and more

Ofer Mendelevitch is Vice President of Data Science at Lendup, where he is responsible for Lendup’s machine learning and advanced analytics group. Prior to joining Lendup, Ofer was Director of Data Science at Hortonworks, where he was responsible for helping Hortonwork’s customers apply Data Science with Hadoop and Spark to big data across various industries including healthcare, finance, retail and others. Before Hortonworks, Ofer served as Entrepreneur in Residence at XSeed Capital, VP of Engineering at Nor1, and Director of Engineering at Yahoo!.

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Casey Stella is a Principal Software Engineer focusing on Data Science at Hortonworks, which provides an open source Hadoop distribution. Casey’s primary responsibility is leading the analytics/data science team for the Apache Metron (Incubating) Project, an open source cybersecurity project. Prior to Hortonworks, Casey was an architect at Explorys, which was a medical informatics startup spun out of the Cleveland Clinic.? In the more distant past, Casey served as a developer at Oracle, Research Geophysicist at ION Geophysical and as a poor graduate student in Mathematics at Texas A&M.

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Douglas Eadline, PhD, began his career as analytical chemist with an interest in computer methods. Starting with the first Beowulf how-to document, Doug has written hundreds of articles, white papers, and instructional documents covering many aspects of HPC and Hadoop computing. Prior to starting and editing the popular ClusterMonkey.net website in 2005, he served as editor?in?chief for ClusterWorld Magazine and was senior HPC editor for Linux Magazine. He has practical hands-on experience in many aspects of HPC and Apache Hadoop, including hardware and software design, benchmarking, storage, GPU, cloud computing, and parallel computing. Currently, he is a writer and consultant to the HPC/analytics industry and leader of the Limulus Personal Cluster Project (http://limulus.basement-supercomputing.com). He is author of the Apache HadoopR Fundamentals LiveLessons and Apache HadoopR YARN Fundamentals LiveLessons videos from Pearson, and is book co-author of Apache HadoopR YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 and author of HadoopR 2 Quick Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem, also from Addison-Wesley, and is author of High Performance Computing for Dummies.