Given the following table: Which of the following describes the data quality issues with the age data?

Completeness refers to whether all required data is present, meaning there are no missing values, but it does not address format or contradictory entries.

Data consistency refers to the uniformity and reliability of data across various systems or over time, ensuring that data points do not contradict each other and adhere to a standard format or definition. Inconsistent age data could manifest as different formats (e.g., '25', 'twenty-five'), or contradictory values for the same individual, which impacts reliable analysis.

Accuracy refers to whether the data correctly represents the real-world value, but inconsistency (e.g., '25' vs 'twenty-five' for the same age) is a specific type of accuracy issue related to format or internal coherence, best described as consistency.

Manipulation refers to the process of altering data, not a data quality issue itself.