"[2] It can attack certain problems whose size, complexity, and need for closely coupled human and machine analysis may make them otherwise intractable.
Analytical reasoning is central to the analyst’s task of applying human judgments to reach conclusions from a combination of evidence and assumptions.
Information visualization forms part of the direct interface between user and machine, amplifying human cognitive capabilities in six basic ways:[2][5] These capabilities of information visualization, combined with computational data analysis, can be applied to analytic reasoning to support the sense-making process.
Visual analytics must facilitate high-quality human judgment with a limited investment of the analysts’ time.
The structures of underlying data representations are generally neither accessible nor intuitive to the user of the visual analytics tool.
Visual representations translate data into a visible form that highlights important features, including commonalities and anomalies.
Insight is either directly obtained from the set of created visualizations V or through confirmation of hypotheses H as the results of automated analysis methods.
or visualization methods VS : S → V, VS = {fv1, ..., fvs} are applied to the data, in order to reveal patterns as shown in the figure above.