Which of the following are data models used by Enterprise Security (ES)?

The data models used by Enterprise Security (ES) in Splunk are specifically designed to enhance security analytics by organizing and categorizing data in a meaningful way. Among the correct options, the data model "Anomalies" is crucial for identifying unusual patterns or behaviors that may indicate security incidents or breaches. This data model leverages machine learning and statistical analysis to help security teams detect anomalies that deviate from normal behavior, thus allowing for proactive threat detection and response.

In contrast, the other choices do encompass various aspects of data analysis but do not specifically align with the standard data models recognized within the Enterprise Security framework in Splunk. While "Transactions," "Users," and "Device Scores" may represent important elements in security contexts or broader data analytics, they do not constitute the defined data models that are utilized for analysis within the Enterprise Security application, which focuses specifically on identifying security threats and managing incidents through data modeling.