The 3 Vs of Big Data revisited: Venn diagrams and visualization by Vincent Granville.
From the post:
This discussion is about visualization. The three Vs of big data (volume, velocity, variety) or the three skills that make a data scientist (hacking, statistics, domain expertise) are typically visualized using a Venn diagram, representing all the potential 8 combinations through set intersections. In the case of big data, I believe (visualization, veracity, value) are more important than (volume, velocity, variety), but that’s another issue. Except that one of my Vs is visualization and all these Venn diagrams are visually wrong: the color at the intersection of two sets should be the blending of both colors of the parent sets, for easy interpretation and easy generalization to 4 or more sets. For instance, if we have three sets A, B, C painted respectively in red, green, blue, the intersection of A and B should be yellow, the intersection of the three should be white.
Sorry to disappoint fans of the “3 Vs of Big Data,” as Vincent points out there are at least six (6). (Probably more. Post your suggestions.)
It is a helpful review on Venn diagrams until Vincent says:
For most people, the brain has a hard time quickly processing more than 4 dimensions at once, and this should be kept in mind when producing visualizations. Beyond 5 dimensions, any additional dimension probably makes your visual less and less useful for value extraction, unless you are a real artist!
I don’t think four dimensions is going to be easy:
3D projection of a tesseract undergoing a simple rotation in four dimensional space.
