Where business intelligence (BI) tools can take huge swaths of data and parse that into digestible data points, data visualization is the presentation portion of that equation. Think of it as the pie chart function of your favorite spreadsheet, only much more powerful. The purpose of such imagery is to quickly transfer information from the machine to the human brain, not only efficiently but also in the most meaningful manner possible. Therefore, it is not the aesthetic value of a visualization that counts but the clarity of the message it conveys.
However, the conciseness necessary for clarity does not preclude complexity in the message. Since much of the information humans must consume is complex and nuanced, data visualizations are configured alone and in groups to tell a larger story through images. An example of a single configuration is any visualization that reveals more granular or related information when the viewer clicks on or performs a mouseover on a section of the illustration. Examples of group visualizations include just about every BI app dashboard ever made.
Indeed, data visualization is such an integral part of self-service BI tools that the tools to make and publish them largely share common feature sets. As expected, in our recent review roundup of the best self-service BI products, we found the vast majority to be capable of data visualization operations.