The increasing amount of scientific data being collected through sensors or computational simulations may take advantage of new analytics techniques for being processed in order to extract new meanings out of raw data. The purpose of this workshop is to present scientists tools and techniques, open issues, recent developments, applications and enhancements for MapReduce, and similar systems. Over the years, MapReduce has become one of the main programming models of choice for processing large data sets. Although it was originally developed for processing web information, the technique has gained a lot of attention from the scientific community for its applicability in large parallel data analysis. Participants will learn how to combine tools and techniques from statistics and computer science to solve their problems more efficiently. The course will consist of introductory lectures held by guest data-analyst experts, and hands-on sessions.
3 editions are scheduled for 2016 in Italian:
Click on the date to register (Subscription are opened about 3 months before the starting date).