Data visualization techniques can be used to further a user’s understanding of massive data sets, and can be used for nearly any information type. Many popular data visualization techniques are adapted from already well-known aesthetics such as pie charts, heat mapping technologies, and subway maps. Additionally, data visualization standards have been influenced by the concepts of proximity, similarity, and size; many designers group associated topics near to each other and use large or small graphical representations for frequently or rarely occurring data points respectively. Smashing Magazine’s article “Data Visualization: Modern Approaches” gives a brief overview of particularly compelling data visualizations, including ChalkLabs CTO Bruce Herr’s visualization of Wikipedia articles.
While data visualization techniques are undeniably effective for static data sets (such as a city’s population demographics at a specific time), they’re also extremely useful when representing live or variable sets of information. For example, OnISP’s live call map is a live visual representation of all of the calls being made or received by phones using OnISP’s VoIP service.
This type of visualization is particularly effective due to its activity; simply listing how many users a system has or how many connections are made per minute can be informative, but it’s not particularly attention grabbing. In contrast, a real-time map tracking each connection made through OnISP gives the user a more concrete example of the significance of the represented data points. The user is able to personally experience the data, subsequently assisting in his understanding and processing of the represented information.
The increased use of data visualization is particularly important for businesses to keep in mind when considering how best to communicate pertinent information from their Big Data sets. Data visualization makes it easier for users to understand large, complicated data sets, ultimately increasing user ease of use and efficiency.