Data visualization is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of visual elements like charts, graphs, maps, and other visual tools. The goal of data visualization is to communicate information clearly and efficiently to users, making complex data more accessible, understandable, and usable.

Data visualization is concerned with visually presenting sets of primarily quantitative raw data in a schematic form. The visual formats used in data visualization include tables, charts, and graphs such as pie charts, bar charts, line charts, area charts, cone charts, pyramid charts, donut charts, histograms, spectrograms, cohort charts, waterfall charts, funnel charts, bullet graphs, diagrams, plots, and more.

Data visualization is one of the steps in data analysis or data science. It is used to spur idea generation across teams, convey an idea, such as a tactic or process, and illustrate workflows. Data visualization can be utilized for a variety of purposes, and it’s important to note that it is not only reserved for use by data teams. Management also leverages it to convey organizational structure and hierarchy while data analysts and data scientists use it to discover and explain patterns and trends.

The importance of data visualization is simple: it helps people see, interact with, and better understand data. Whether simple or complex, the right visualization can bring everyone on the same page, regardless of their level of expertise. As the “age of Big Data” kicks into high gear, visualization is an increasingly key tool to make sense of the trillions of rows of data generated every day. Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers. A good visualization tells a story, removing the noise from data and highlighting useful information.

Some advantages of data visualization include easily sharing information, interactively exploring opportunities, and visualizing patterns and relationships. Disadvantages include the possibility of oversimplification and the potential for misleading interpretations.

Top data visualization solutions include features like business intelligence, data analytics, and data visualization tools.