Big Data: Challenges and Opportunities

• Activity Number: 52
• Type: Invited
• Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Nicole Lazar*+
• Companies: University of Georgia
• Keywords: Big Data ; functional neuroimaging

Abstract

"Big Data" is a common buzz-phrase these days. Massive amounts of data arise from both the usual scientific enterprises such as genomics and medical imaging, and from new social arenas such as Facebook and Twitter. We live in a data-rich age, where data are a valuable commodity, and this is not likely to change in the foreseeable future. This new state of reality poses both challenges and opportunities for the statistical community. Challenges, because we are not alone in having an interest in the analysis of Big Data. Computer scientists, engineers, and the evolving class of "data scientists" as distinct from statisticians, all stake a claim in this fast evolving landscape. Another set of challenges is more basic, and involves the development of statistical techniques for Big Data analysis, methods that can easily scale up with the size of the data. Together with the challenges, then, come many opportunities: to devise and validate new statistical procedures, to collaborate with computer scientists and others, and to raise the profile of our profession. In this talk I will discuss these challenges and opportunities, with an emphasis on Big Data in a scientific context.