In business intelligence visual analytics plays a key role in decision making. With the help of visualization it allows quicker and more reliable decisions. Since man is always more effective in research, development and interaction between users, when in a set system, it is reasonable to ask ourselves what types of visualizations we know and how we can classify them according to different criteria. In this thesis we aim to facilitate the understanding, use and construction of automatically generated visualizations with the goal to define the taxonomy of visualizations in business intelligence, according to various criteria. Through various examples of visualization programs, we compared a variety of visualizations and as such on the basis of criteria we identified areas of visualization according to criteria depending on the type of data, shape, communications and interactive techniques.