Washington, DC – June 15, 2012 The amount of data each organization deals with today has been rapidly growing. However, analyzing large datasets commonly referred to as "big data" has been a huge challenge due to lack of suitable tools and adequate computing resources. Why are organizations, both in public sector and private sector, so keen on unlocking business insights from all structured and unstructured data? What is the current state of big data solutions and service providers? How effective are some of the solutions that have been put into real world practices? What is the current state of cloud computing technologies? What impacts have cloud computing technologies available in public clouds and private clouds had on the way organizations addressing big data challenges? How to secure big data in the clouds? What are the future roadmaps for cloud-based big data solutions, especially for geospatial related applications?
This panel discussion will include a short presentation or discussion related to big data and cloud computing by each panelist, followed by questions and questions from the audience and the panel.
Moderator:
Dr. Zhiming Xue, Senior Architect Evangelist for Windows Azure cloud computing at
Microsoft
Panelists:
Dr. Simon Y. Berkovich: Professor at
George Washington University, Senior Advisor at
COM.Geo
Dr. Larry Feldman: Lead Associate at
Booz Allen Hamilton
Dr. Olli-Pekka Tossavainen: Researcher at Nokia
Dr. Shyam Parhi: Computer Scientist for Airport GIS at
U.S. DOT - FAA
Dr. Kevin Montgomery, CEO,
Intelesense Technologies
Read more at: http://www.com-geo.org/conferences/2012/index.htm
About COM.Geo Conference
COM.Geo Conference is the leading-edge computing for geospatial conference, focusing on the latest computing technologies for multidisciplinary research and development that enables the exploration in geospatial areas. Innovative geospatial research and application technologies are the brightest spotlights at COM.Geo conference. COM.Geo is playing a guiding role to advancing the technologies in computing for geospatial fields.