Data visualization is the process of communicating and translating data and information in a visual context, usually employing a graph, chart, bar, or other visual aid. Visualization also uses images to communicate the relationships between various sets of data.

Data visualization is also called information visualization, information graphics, and statistical graphics. It is a step in the process of data analysis and data science, which tells us that after all data has been collected, processed, and modeled, the information must be visualized so that users can use it to draw conclusions.

The Importance of Data Visualization

Visually representing insights derived from data provides a means for people to see and understand data patterns, trends, and outliers. Consider the rejoinder “Do I have to draw a picture for you?” aimed at someone who’s not grasping the speaker’s point. Well, data visualization draws us that picture, presenting facts and figures in a clear, visually appealing manner.

The benefits of data visualization include:

• Gives the reader the means to quickly absorb information, improve insights and make faster decisions
• Provides an easy means of distributing information that offers users more opportunities to share their insights with everyone involved in the project
• Imparts an increased understanding of what steps an organization must take to improve itself
• Offers the ability to attract and maintain the audience's interest by giving them the information they can understand
• Gives the decision-makers the means to quickly act on findings, deliver successful outcomes faster, and have fewer errors
• Eliminates the need to excessively rely on data scientists because it is more accessible and easily understood.

How is Data Visualization Used?

Nothing speaks more effectively about data visualization’s versatility than real-world examples, and there are plenty to be found. Such as:

• Determining correlations. The best way to determine the relationship and correlations between two variables is to compare them visually.
• Network examination. In this context, “network” refers to the whole market audience. By examining the network, analysts can spot audience clusters, including any influencing factors and the bridges between them, and statistical outliers.
• Tracking changes over time. This use is a simple yet essential data visualization function. Visualization helps people see and analyze how data trends change over a given period.
• Frequency determination. Frequency is related to tracking changes but differs because it examines how often a given event happens.
• Timeline scheduling. Using a resource like a Gantt chart, project leaders can illustrate each assignment within the project and how long the tasks will take.