Tag Archives: MongoDB
Researchers today need to deal with an avalanche of data—from environmental sensor networks (both on land and at sea), social media feeds, LiDAR, and outputs from global- and regional-scale atmospheric circulation and general climate models and simulations. Because of this, “big data” is emerging as a major research theme for the academic community.
I recently had the opportunity to attend GIScience 2012, which is convened every two years and brings together leading researchers from around the world to reflect on a wide spectrum of geographic information science research areas. Attendees are normally university academics and graduate students working in the areas of geography, computer science, information science, cognitive science, mathematics, philosophy, psychology, social science, environmental sciences, and spatial statistics.
The technology tides have shifted again and, as the notion of cloud computing is becoming mainstream across most industries, a new buzzword is emerging: Big Data. Never heard of it? Simply put, the term refers to the ever-growing mountain of data, generated from myriad sources, that organizations must effectively address.
For instance, according to a recent MeriTalk survey, 96% of Federal IT professionals expect their agency’s stored data to grow in the next two years by an average of 64 percent.
Big Data is often described using the Three “V”s: Velocity, Volume, and Variety. By example, let’s take a few of the real world case studies gathered by IBM and provided by Mike Rhodin, Senior Vice President at IBM Software Solutions: