Data visualization is not a new concept. Per Wikipedia’s definition: “Data visualization is the study of the visual representation of data, meaning “information which has been abstracted in some schematic form, including attributes or variables for the units of information.” For businesses, the primary application of data visualization is the conversion of large volumes of technical data into easy to read dashboard reports, heat maps, and other visualizations. For example, a corporation with 100 different retail locations on the Eastern seaboard might use data visualization software to generate a heat map showing their most profitable and least profitable stores. Alternatively, an executive might want to quickly reference which locations have the highest utility costs and compare that map with the profitability heat map.
This concept of creating easy to understand visualizations of large volumes of data is also referred to as data transformation. Tremendous amounts of data are created and collected by organizations in the course of operations. This data is often stored in many silos of information ranging from databases, to spreadsheets, to data marts, to enterprise data warehouses. A central repository is often not the solution. Studies have shown that more than 50 percent of data warehouse projects have had limited acceptance or were outright failures because of data quality issues. Data transformation allows decision makers to quickly access the nuggets of business intelligence locked within these large volumes of data.
Expect to see data visualization and data transformation become increasingly popular buzz words with people involved in business intelligence solutions in 2011.