In the introductory chapter of Kieran Healy’s book “Data Visualization for Social Science” the power of data visualization is described. Data visualization can be - and usually is much more successful for conveying a better understanding of data to the human mind. Successful data visualization can rely on many things, including aesthetics, accuracy, and understanding of your audience. The design of Data visualization however, is easily thrown off. There are endless nuances one must consider while designing that are based on human perception. These nuances can range from “bad taste”, to psychological human tendencies. How humans perceive things naturally is a huge factor to consider when designing data, but is endlessly complicated. Furthermore successful data visualization must not mislead the viewer by misrepresenting data. The most vital aspect of data visualization design relies on correctness and also the ease at which it can be perceived. Many classic “Bad Design” rules that apply to typography or layouts also apply to data. It makes sense that a graph that has too many frills, can distract from the meaning. Data visualization is difficult because unlike some types of graphic design, when your personal opinions get involved, you can very easily begin to sway the data into a place where it is hiding part of the story. There are endless ways to create a graph and it’s interesting that some are more correct than others. As the designer, you must make a choice about how the data is best represented in relation to the idea you want to get across. Perception is so important to data design, something as simple as shape choice can completely change how a person interprets a visual.