Today excess amounts of data are overwhelming; raw data becomes useful only when we apply methods of deriving insight from it. Interpreting bar graphs and charts have become old and particularly 3D bar graphs have several flaws (according to Dr. Alvaro Munoz PhD, a professor of epidemiology at the School of Public Health at Johns Hopkins). First, the variables, which equally contribute to an outcome, are not equally represented in the diagram. This gives the impression that one variable is more important than another. Second, it is sometimes difficult, if not impossible, to distinguish the true value of the bars, because of the problems of representing a three-dimensional image on a two-dimensional page. Because of perspective, some bars appear to be of greater or lesser value when they are actually of equal value. The third drawback of the 3-D graph is that it cannot be used to present overlapping data. In some cases, parallel bars with higher values may obscure those with lower values making the graph useless. He proposed a better way to represent graphs called Diamond Graph, for more read here.
Data visualization is a powerful exercise. Visualizing data is the fastest way to communicate it to others. Of course, visualizations, like words, can be used to lie, mislead, or distort the truth. But when practiced honestly and with care, the process of visualization can help us see the world in a new way, revealing unexpected patterns and trends in the otherwise hidden information around us.
Different look at Oscar Nominees
Visual.ly has a huge collection of visual content. How one can visually represent data depends on many parameters. There may not necessarily be only one way one can visualize the content anyways.
Here is an example of how visually one can view the Oscan Nominees along with their related data such as Movies, Budget, and Box Office.
Our analysts predicted in October 2013 that Seattle Seahawks and Denver Broncos are going to be in the finals and that Seattle Seahawks are going to win the SuperBowl. Although we desired Peyton Manning to win, we predicted that Seahawks will win,and therefore we collected data on these two teams (which is only partially displayed here).