What is an essential step in auditing data models according to best practices?

Creating a database table for logging audit events is vital in auditing data models according to best practices. This approach provides a structured and systematic method to record all relevant activities concerning the data models. By maintaining a dedicated table for audit logs, organizations can track changes, access patterns, and interactions with the data, which is crucial for both compliance purposes and data integrity monitoring.

This logging mechanism allows for efficient querying and analysis of audit trails, enabling teams to identify unauthorized access or changes, investigate anomalies, and ensure accountability within data governance practices. It helps ensure that any actions performed on the data models are documented, creating a clear historical record that can be referred back to when needed.

In contrast, creating a new database from scratch doesn't directly contribute to auditing efforts and could complicate data management. Exporting audit events to a public repository raises serious security and privacy concerns, as sensitive information is often involved in audit trails. Restricting access to all data models, while important for security, does not facilitate the tracking of changes or interactions essential for auditing purposes. Thus, the creation of a database table for logging audit events is the best practice for effective data model auditing.