Application of data visualization

 Most visualization designs are to aid decision making and serve as tools that augment cognition. In designing and building a data visualization prototype, one must be guided by how the visualization will be applied. Data visualization is more than just representing numbers; it involves selecting and rethinking the numbers on which the visualization is based.

Visualization of data is an important branch of computer science and has a wide range of application areas. Several application-specific tools have been developed to analyze individual datasets in many fields of medicine and science.

1. Public Health - the ability to analyze and present data in an understandable manner is critical to the success of public health surveillance. Health researchers need useful and intelligent tools to aid their work. Security is important in cloud-based medical data visualizations. Open any medical of the health magazine today, and we will see all kinds of graphical representations.
2. Renewal Energy - Calculation of energy consumption compared to production is important for an optimum solution.
3. Environmental Science - As environmental managers are required to make decisions based on highly complex data, they require visualization. Visualization applications within applied environmental research are beginning to emerge. It is desirable to nave at one's disposal different programs for displaying results.
4. Fraud Detection - Data visualization is important in the early stages of fraud investigation. Fraud investigators may use data visualization as a proactive detection approach, using it to see patterns that suggest fraudulent activity.
5. Library-decision Making - Data visualization software allows librarians the flexibility to better manage and present information collected from different sources. It gives them the skill to present information in a creative, future library needs and goals. Librarians , as de factor experts of data visualization, can assist students, faculty and researchers visualize their data. 

Several information visualization algorithms and associated software have been developed. This software enables users to interpret data more rapidly than ever before.