Visual analytics is defined as the science of analytical reasoning facilitated by visual
interactive interfaces. Since its inception in 2006, the field has grown to encompass
a wide array of topics relating to the theory, design, and development of interactive
visual interfaces for the purposes of data exploration, data analysis, sense making, and
decision making.
While the scope of visual analytics is broad, one principle that has emerged over the
years is the need for visual analytics systems to leverage computational methods in
statistics, data mining, knowledge discovery, and machine learning for large-scale data
analysis. In these systems, the human operator works alongside the computational
processes in an integrated fashion—the computer can sift through large amounts of
data and identify the relevant information, while the human interactively explores the
reduced data space to discover trends and patterns and make informed decisions. The
two components operate in coordination, allowing for a continuous and cooperative
analytical loop.