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 Practical Data Science with Hadoop(R) and Spark provides 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