Which of the following is MOST important for a data steward to verify when a...

The most important thing for a data steward to verify when a system’s data is edited by an automated tool to fix an incident is that the change maintains consistency among databases and has no other impacts. Data consistency is a dimension of data quality that describes the data’s uniformity as it moves across applications and networks and when it comes from multiple sources1. Data is considered consistent if two or more values in different locations are identical and do not conflict1. Data consistency is related to data integrity and data currency1. To ensure data consistency, some steps include data governance, automated data integration, and regular data audits and quality control checks1. If the automated tool changes the data in one database, but not in others, it can create inconsistencies and errors that affect the reliability and usability of the data. Similarly, if the automated tool changes the data in a way that affects other processes or systems that depend on the data, it can cause disruptions and failures that impact the business operations and performance. Therefore, the data steward should verify that the change is consistent and has no other impacts before approving it.

The other options are not as important as verifying the data consistency and impact of the change. Requesting and approving the change by the business department and the data owner is a good practice, but not a verification step. Documenting the change in preparation for future audits is a necessary step, but not a verification step. Addressing the permanent solution for the incident by problem management is a relevant step, but not a verification step. References := What is Data Quality - Definition, Dimensions … - Simplilearn