2013 IBM Business Analytics Workshop

IBM Business Analytics Workshop

Friday, April 19, 2013 ● 8:30 a.m. - 5 p.m.

Sponsored by: IBM

Download: Agenda | Speaker Bios

The Internet has become an indispensable tool and environment of communication and connection in contemporary life. Particularly, with the advent of social media and social networks – such as Facebook, Twitter, and P2P websites – public availability of new information from social interactions and communications increased dramatically. This availability creates unprecedented opportunities to analyze, extract, and utilize large amounts of data to identify patterns, and channel this information to better decision making. Business analytics techniques such as statistical analysis, data mining, and network modeling are uniquely valuable in taking advantage of these new and extremely rich sources information. Potential related applications cover a wide range, including homeland security and intelligence, disaster relief, improved communications with citizenry, disease control, fraud detection, and improving process efficiency both in public and private sectors.

This workshop brings together thought leaders from the Robert H. Smith School of Business, IBM and the Federal Government to provide perspectives and share ideas on how to utilize the wealth of information and data on the Internet through Business Analytics techniques. The presentations will focus on leveraging analytics methodologies utilizing Internet data, communicating insights from existing studies, and identifying potential applications of similar techniques to new problems.

A panel discussion will examine the topic "How much data is enough". The internet and the digitization of every-day processes have generated a nearly limitless supply of data. Cheap storage of various types, including cloud storage, together with fast and flexible retrieval mechanisms have enabled much of this data to be stored for later examination and analysis. The goal of this panel is examine these trends and consider the benefits that accrue from storing and analyzing this data versus the challenges it might create.

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