Why is it important to remove redundant information in data visualization?

Removing redundant information in data visualization is crucial for clarifying insights. When visualizations contain excessive or repetitive data, they can become cluttered, making it difficult for the audience to identify key messages or trends. By eliminating redundancy, the visualization focuses on the most pertinent information, allowing viewers to process and understand the data more effectively.

This clarity facilitates quicker and more accurate interpretations, enabling stakeholders to make informed decisions based on the insights presented. A streamlined visualization highlights important patterns and relationships without distraction, thus enhancing the communication of the analysis. Moreover, this focus prevents cognitive overload, which can occur when viewers are confronted with too much information, leading to confusion rather than understanding. In summary, the primary goal of visualization is to convey insights clearly; therefore, removing duplicates directly contributes to that objective.