Data visualization in KDD is coupled with statistical analysis and helps in what way?

• A. It helps illustrate patterns and trends in the data
• B. It slows down data processing
• C. It replaces data mining
• D. It has no role in KDD

Answer: (A)

Data visualization in KDD, when combined with statistical analysis, helps illustrate patterns and trends by turning numeric results into graphs that reveal relationships, clusters, and outliers. Seeing how variables relate on scatter plots, how values cluster in heatmaps, or how a metric changes over time makes patterns obvious that may be missed in raw numbers, guiding which statistical tests to apply and where to probe more deeply. This visual insight accelerates understanding, aids hypothesis generation, and helps communicate findings to stakeholders. It doesn’t slow down processing, nor does it replace data mining—the visualization is a complementary step that highlights what to mine and how to interpret the results.