Visualization refers to the use of visual elements such as charts, graphs, and images to represent data and information. It is a powerful tool for understanding complex data sets and communicating insights effectively. By converting numerical or textual data into visual formats, visualization enables users to identify patterns, trends, and relationships that might not be immediately apparent in raw data.

The importance of visualization in data analysis is underscored by various studies. For instance, a report by the McKinsey Global Institute found that data-driven organizations are 23 times more likely to have revenue growth above their industry average. Visualization plays a crucial role in this data-driven approach by facilitating the exploration and interpretation of data. According to a study by the University of California, San Diego, visualizations can improve decision-making by up to 95%. This is because visual representations allow humans to process information more quickly and accurately than text or numbers alone. Additionally, a survey by the IEEE found that 65% of data scientists believe that visualization is the most important skill for a data scientist to have. These statistics highlight the significant impact of visualization on data analysis and decision-making processes.