According to Friedman (2008) the “main goal of data visualization is to communicate information clearly and effectively through graphical means.”
The main idea behind data visualization is to reduce the complexity of huge data sets by creating meaningful graphical representations. Using data visualization techniques makes it easier to understand patterns between abstract data set. Several types of graphs, such as bar graphs, line chart, column charts and several types of indicators, such as gauges, traffic lights, flags are elements used to visualize data. However, it is meaningless if the appropriate pattern of visualization is not used in the right context.
Data mining, data transformation, data analysis and data management are terms that form the foundation of data visualization. To create efficient graphical and statistical representations of the data, it is essential to analyze and recognize the KPI or metrics of primary concern.
When building KPI and metrics, you need to use appropriate graphical representations to display your findings. For instance, representing the sales evolution over months through a pie chart is not as effective as representing it using a bar chart.