Small Summaries for Big Data

In dealing with big data, we often need to look at a small summary to get the big picture. Over recent years, many new techniques have been developed which allow important properties of large distributions to be extracted from compact and easy-to-build summaries. In this talk, I'll highlight some examples of different types of summarization: sampling, sketching, and special-purpose. Then I'll outline the road ahead for further development of such summaries.

Graham Cormode is a Principal Member of Technical Staff in the Database Management Group at AT&T Shannon Laboratories in New Jersey. Previously, he was a researcher at Bell Labs, after postdoctoral study at the DIMACS center in Rutgers University from 2002-2004. His PhD was granted by the University of Warwick in 2002. His work considers aspects of managing and working with large amounts of data, with particular emphasis on privacy and anonymization, and large scale analytics.