What is one purpose of auditing in the Data Modeler?

The purpose of auditing in the Data Modeler primarily revolves around tracking query processing time and data usage. This function is critical as it provides insights into how data models are performing in a practical environment. By understanding the processing times of various queries, users can identify bottlenecks, assess the efficiency of the model, and make informed decisions to optimize performance. Additionally, monitoring data usage helps in managing database resources effectively, ensuring that data modeling aligns with actual user demand and usage patterns. This process contributes to a more efficient and effective data management strategy, as it allows for adjustments based on real-world engagement with the data models.

In contrast, creating new data models focuses on design rather than auditing existing ones. The automatic generation of reports serves a different operational need and does not directly relate to the continuous evaluation of a data model's performance. Enhancing data model security relates more to protecting sensitive information rather than auditing model functionality or performance, which further clarifies the distinctive role that auditing plays in tracking query processing and data usage.