Big Data Analysis: Concepts, Methods, and Computation

• Activity Number: 258
• Type: Roundtables
• Date/Time: Tuesday, August 5, 2014 : 7:00 AM to 8:15 AM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Sijian Wang*+
• Companies: University of Wisconsin
• Keywords: Computation ; Big Data ; Statistical Analysis

Abstract

The rapid growth in the size and dimensionality of data sets in science and technology is driving the need for novel statistical models and methods that can handle these "Big Data." Some aspects of classical statistics---including concepts, methods, theories, and algorithms---may not be adequate to address emerging problems in "Big Data." We will discuss the challenges associated with data sets of massive size and dimensionality, including settings in which the dimensionality of the data is growing faster than the number of data points. Framed by examples of Big Data applications in science (e.g., genomics and meuroimaging) and industry (e.g., Google and Facebook), we will review a set of recently developed statistical models and methods to tackle these challenges. We also will explore the computational issues associated with conducting these analyses in the context of parallel and cloud architectures.