Advanced visualization support data exploration and pattern discovery - A plausible thought
Just when the organizations are modifying their road maps for digitization and accommodate more data , this is the time when "advance visualization" makes the noise! If we are not on the same platform, advanced visualization is just about high-quality graphics that are well coupled by the person who tries to derive insights. Of-course, this need not be a abstruse chart. Visualization lets us leverage the very dynamic tool in the world of recognition, data or the pattern - "the human eye".
Visualization is one impressive tool to summarize any kind of data, utilizing the in-numerous rows and plot the chart. So for visualization of data, the graphics should be of high quality. If they are not easy to understand & interpret, then they are meaningless. One of the examples that defines this aptly is the case study of the Boost Labs.
What went wrong: Boost Labs partnered with US Government to create a data visualization on Asian Americans and the Pacific Islanders for one of the White House initiatives. The data had already been collected before the project went live, the only task was to design a visualization that would infer the desired results. At the start of the project, it showed that there was scope for more information. More information means more data that would have a better focus in deriving the expected results. A second round of data collection was on-the-go to gather that extra information. If a visualization tool had been used to manage the data at the initial stage, identification of areas of opportunity would have been greater, saving time.
Thus, the human eye is dynamic in recognizing patterns. At times, the human eye recognizes patterns which are non-existent and our grey matter captures that as illusion. Data visualization is a great tool and should be in the tool repository of any data centered professional. Done in the right way possible and used correctly estimates its significance in the long-run.