Data visualization: existing tools and techniques

Over time, data have become the essential competitive factor for businesses/enterprises to grow and develop. Selected businesses/enterprises such as information industrial businesses will put more focus on product innovation or technology for solving the challenges of gigantic data, i.e., capture, storage, analysis, and presentation/application. Enterprises/businesses like banking, manufacturing, and other enterprises will also benefit from analysis and management of huge data and provide more prospects for management/strategy/marketing innovations. For centuries, persons/societies have depended on visual illustrations such as maps and charts to grasp information quickly. Due to the way the human brain processes information, it is faster for people to grasp the meaning of many data points when they are displayed in charts and graphs rather than in piles of spreadsheets or long reports. Data visualization is the presentation of data in a graphical or pictorial format. Over time, as data are collected, stored, and analyzed, decision makers at all stages rely on data visualization/presentation software that enables them to see and visually present fruitful analytical results, find significance among the heaps/millions of variables, communicate established concepts and hypotheses to others, and even forecast/predict the future. By exploring each aspect of existing tools and techniques related to data visualization, the major objective of this chapter is to present essential theoretical aspects in an analytical way with a profound focus on challenges to represent data in visual form and limits in terms of pros and cons of existing tools and techniques.