Which of the following is the correct definition of the quality criteria that describes completeness?

Completeness is a core dimension of data quality. It refers to the extent to which all necessary data is present and available. A dataset is considered complete if it contains all the required data points and attributes for its intended use. For example, if a customer record requires a name, address, and phone number, a record missing the phone number would be considered incomplete. This criterion ensures that there are no gaps or missing values in the data that could hinder analysis or operations.

B: This describes consistency or comparability, ensuring data is the same across different sources or systems. C: This describes uniformity, which is a facet of consistency, ensuring data uses the same units of measure. D: This describes validity, which ensures that data values fall within acceptable ranges or conform to predefined business rules.

- Wang, R. Y., & Strong, D. M. (1996). Beyond Accuracy: What Data Quality Means to Data Consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099 (Table 2, "A Framework for Data Quality").

- Pipino, L. L., Lee, Y. W., & Wang, R. Y. (2002). Data quality assessment. Communications of the ACM, 45(4), 211–218. https://doi.org/10.1145/505248.506010 (Section "Data Quality Dimensions," Completeness).