A data analyst receives a new data source that contains employee IDs, job titles, dates...

This question falls under theData Governancedomain, focusing on identifying data quality issues. The dataset includes dates of birth and birth months, which suggests a potential inconsistency.

Redundancy (Option A): The dataset includes both dates of birth (e.g., 1990-05-15) and birth months (e.g., May), which is redundant because the birth month can be derived from the date of birth, indicating a data quality issue.

Equivalence (Option B): Equivalence isn’t a standard data quality term in this context; it might refer to data matching, which isn’t the issue here.

Parallel (Option C): Parallel isn’t a recognized data quality term; it might relate to processing, not data inconsistencies.

Duplication (Option D): Duplication refers to identical records, but the issue here is redundant fields, not duplicate rows.

The DA0-002 Data Governance domain includes "data quality control concepts," and redundancy is a key inconsistency when the same information is stored in multiple forms unnecessarily.