What is an audit trail and how can it be implemented in a relational Clarity model?

What is an audit trail and how can it be implemented in a relational Clarity model?

• A. A summary of data definitions.
• B. A log of user login attempts only.
• C. A separate data warehouse only.
• D. A record of edits to data; can be implemented with audit/history tables or temporal tables that capture changes with timestamps and user IDs.

Answer: (C)

An audit trail is a record of data changes over time that shows who made what change and when. In a relational Clarity model, you implement it by designing for history: keep a log of edits to data rather than just storing the current value. This can be done with audit/history tables that capture each change, or with temporal tables that version rows automatically. Key ideas to understand: you want to know not only the current state of a row but the sequence of changes that led there. That means storing the operation (insert, update, delete), the timestamp of the change, and who made the change. In history or audit tables, you typically store the primary key of the row, the changed_at timestamp, the user_id, and the before/after values (or the full previous and new row). With temporal tables, the system maintains period start and end times (and often the user) so you can query the state of data as of any point in time. This concept is broader than just logging login attempts, and it’s more than just a separate data warehouse. It provides accountability, traceability, and the ability to audit, rollback, or review data evolution within the transactional database.

An audit trail is a record of data changes over time that shows who made what change and when. In a relational Clarity model, you implement it by designing for history: keep a log of edits to data rather than just storing the current value. This can be done with audit/history tables that capture each change, or with temporal tables that version rows automatically.

Key ideas to understand: you want to know not only the current state of a row but the sequence of changes that led there. That means storing the operation (insert, update, delete), the timestamp of the change, and who made the change. In history or audit tables, you typically store the primary key of the row, the changed_at timestamp, the user_id, and the before/after values (or the full previous and new row). With temporal tables, the system maintains period start and end times (and often the user) so you can query the state of data as of any point in time.

This concept is broader than just logging login attempts, and it’s more than just a separate data warehouse. It provides accountability, traceability, and the ability to audit, rollback, or review data evolution within the transactional database.