Description: Data quality visualization refers to the graphical representation of quality-related data to facilitate understanding. This approach allows analysts and decision-makers to quickly interpret complex information, identifying patterns, trends, and anomalies that may not be evident in tabular data formats. By using charts, diagrams, and other visual representations, the goal is to transform raw data into meaningful information that supports continuous improvement and quality management across various industries. Key characteristics of data quality visualization include clarity, accuracy, and relevance, ensuring that the presented data is easily understandable and useful for the audience. Additionally, effective visualization can help communicate audit results, performance evaluations, and process analyses, fostering a culture of quality within organizations. In a world where the amount of generated data is overwhelming, data quality visualization becomes an essential tool for informed and strategic decision-making.
