Data Integrity Test

A.

A data integrity test is a process that ensures the accuracy, completeness, and consistency of data throughout its lifecycle. It is important to review certain aspects of the data to ensure its integrity.

A. Completeness: Completeness is a measure of whether all required data elements are present in a dataset. As part of a data integrity test, completeness should be reviewed to ensure that all data elements are present and accounted for.

B. Confidentiality: Confidentiality is the protection of sensitive information from unauthorized access. While confidentiality is an important aspect of data security, it is not typically reviewed as part of a data integrity test.

C. Data backup: Data backup is the process of creating a copy of important data to protect against data loss. While data backup is important for data recovery, it is not typically reviewed as part of a data integrity test.

D. Redundancy: Redundancy is the duplication of data to ensure availability in case of data loss. While redundancy is important for data availability, it is not typically reviewed as part of a data integrity test.

In summary, the correct answer to the question is A. Completeness, as it is a critical aspect of data integrity that ensures all required data elements are present and accounted for.