Data mining focuses on discovering patterns, correlations, statistical relationships, clusters, trends, and profiles within large data sets. It is commonly used to identify unusual behavior, customer profiles, fraud indicators, exception patterns, and risk relationships that may not be obvious through manual review. Process mining is different; it analyzes event logs to understand how business processes actually flow. Process analysis evaluates process design, controls, bottlenecks, and efficiency. Data analysis is broader and may include summarization, filtering, testing, or reporting, but it does not specifically describe creating profiles from statistical relationships. Internal auditors use data mining when searching for hidden risk patterns, vendor anomalies, duplicate transactions, behavioral indicators, or unusual population characteristics. Therefore, Option C is correct.