Visual analytics is especially concerned with sense making and reasoning. It combines techniques from information visualization (that deals with abstract data structures) with techniques of data analysis, in particular transformation and decomposition, so that the research problem becomes manageable.
Visual analytics is also an opportunity for the business community. It can facilitate evidence based decision making by means of extending the box of tools of currently popular software, like spreadsheets. Having available data analysis tools that enable business analysis by visualizing hidden associations between variables could be beneficial for the decision making process. Moreover, the vast and ever growing amount of data stored in transactional and accounting information systems, drives the need for more (and better) analytical and representational tools.
Visual analytics is the science of analytical reasoning, an outgrowth of the fields information visualization and scientific visualization, made possible by interactive visual software interfaces. Visual analytics tools and techniques are used to:
1) synthesize information and derive insight from dynamic, ambiguous, and often conflicting data;
2) detect the expected and discover the unexpected;
3) provide timely, defensible, and understandable assessments;
4) formulate research hypothesis as well as deliver evidence in their support; and
5) communicate assessments effectively for decision making and scientific progress.
Some interesting websites about data and data visualization to visit are:
Free Statistics book Elements of Statistical Learning