Visual analytics is a form of inquiry in which data that provides insight into solving a problem is displayed in an interactive, graphical manner.
The approach uses data visualization technologies to help data scientists and other professionals identify trends, patterns and relationships in the data they are working with. Packaged visual analytics software tools make it easier for non-technical users to use by including drag-and-drop options for setting and modifying analytical parameters.
Like other types of business intelligence (BI) and business analytics (BA) initiatives, visual analytics applications must incorporate effective data management strategies in order to integrate, unify and standardize data coming from different source systems. Visual analytics is especially helpful in applications involving large, complex data sets and analytical processes that require a high degree of monitoring and interaction -- for example, big data analytics and data mining uses.
Opportunities for deploying visual analytics capabilities continue to evolve and grow with the broader adoption of technologies such as mobile business intelligence and location intelligence software.