Cloud Computing and Virtualization 2011

We all know there is more data than ever. But there's not just more of it, it is much less predictable in format, and it's also hitting data centers at great speed as bandwidth increases and access becomes more pervasive.  These demands are resulting in vital and vibrant innovation to not only grapple with the problem, but to gain more and better insights into the data content. This talk will discuss the challenges, trends, directions, architectures, and solutions that are emerging in big data management and content analytics—from highly scalable, real-time analytics, to deep historical machine learning and pattern models. These techniques are broadly in use across the Internet and in commercial industry. There is still more to be done, but these innovations will help government organizations not only handle future data stores, but also derive the information they critically need for decision support, customer services, and other essential public sector functions.

Attendees will learn:

• How agencies can avoid getting crushed by the volume, velocity, and variety of information flowing into their organizations
• Why the data volume is increasing exponentially and the role of wireless end points in this process
• How the experience of commercial enterprises can be transported to streamline government data management strategie
• Methods to forecast the anticipated amount and type of data that will face government agencies as the world becomes ever more inter-connected