The primary reason for an IS auditor to use data analytics techniques is to reduce detection risk. Detection risk is the risk that an IS auditor will fail to detect material errors or irregularities in the information systems environment. By using data analytics techniques, such as data extraction, analysis, visualization, and reporting, an IS auditor can enhance the audit scope, coverage, efficiency, and effectiveness. Data analytics techniques can help an IS auditor to identify anomalies, patterns, trends, correlations, and outliers in large volumes of data that may indicate potential issues or risks. Technology risk, control risk, and inherent risk are types of audit risk that are not directly affected by the use of data analytics techniques by an IS auditor. References: [ISACA Journal Article: Data Analytics for Auditors]