Visual Analytics (VA) [1] is an emerging multi-disciplinary area that takes into account both ad-hoc and classical Data Mining (DM) algorithms and Information Visualization IV (IV) techniques, combining the strengths of human and electronic data processing. Visualisation becomes the medium of a semi-automated analytical process, where human beings and machines cooperate using their respective distinct capabilities for the most effective results. Decisions on which direction analysis should take in order to accomplish a certain task are left to the user. Although IV techniques have been extensively explored [2], combining them with automated data analysis for specific application domains is still a challenging activity [3]. This chapter provides an introduction of the main concepts behind VA and presents some practical examples on how apply it to Information Retrieval (IR).