Like Object Oriented programming, while it’s possible to do without explicit language support, it’s much nicer if the programming language provides explicit support such as classes and inheritance. The same is true with data visualization.
It is certainly true that most graphs could be created with a minimum set of graphing features, such as those available in Excel, it is very helpful if the software tool has many of the advanced graphing functions built-in. The chart to the right is a visualization of medical case data.
Two measures are shown in the first graph:
It would be extremely difficult to draw this visualization if the software doesn’t provide direct support for visualizing multi-variant data as color and size. But with proper software, this can be done through simple drag-and-drop by business users.
Advanced data visualization features are not only a convenience for developers. More importantly, the existence of these features enables business users to create their own visualizations, and consequently opens up visualizations to a whole new area of usage that’s not possible when graphs must be hand crafted.
In addition, visualization software also should build in rules and defaults so a casual user can create visualization that automatically follows the data visualization principles. In a way, the software also acts as a guide besides being a tool.
Until recently, data visualization has been considered a separate field from Business Intelligence (BI). Visualization software generally focused on applications in scientific and research fields, and is normally designed to be used by statisticians and researchers.
This has changed in the last few years. Data visualization vendors have started to address business users and target their software at business analytics. However, the chasm between data visualization and BI persisted. A simple examination of data visualization tools will find almost all are applications serving sophisticated analysts. Even the tools that made a good effort in bridging the gap between visualization and reporting offer very superficial support.
Given the power of visualization, it is only natural to apply the rich communication techniques in the field of reporting. However, the naïve approach of just combining the two feature sets will not work, since they are designed to serve different user communities. An effective blend of visualization and reporting must maintain the strength of each solution, and avoid the conflicting needs of the two diverse approaches.
The combination of robust visualization features with complete traditional reporting will define the next generation business intelligence software.
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