One of the challenges with Big Data is how to find value hidden in all that volume. Experts generally recommend approaching it as an explorer rather than simply querying the data to find specific answers.
As an astrophysicist, Dr. Kirk Borne knows a thing or two about probing the unknown. Borne, professor of Astrophysics and Computational Science at George Mason University, began tinkering with large data sets because of science, but soon became an advocate for Big Data. Now, in addition to his work as a professor and astrophysicist, Borne is a transdisciplinary data scientist.
According to Borne’s May post for the MapR.blog, he has identified four major types of Big Data discoveries (data-to-discovery, he terms it):