Which data quality attribute indicates data contains all the necessary fields and records?

• A. Timeliness
• B. Completeness
• C. Uniqueness
• D. Consistency

Answer: (B)

Completeness is the data quality attribute that indicates data contains all the necessary fields and records. When data is complete, every required attribute exists for each record and no essential rows are missing, so you can rely on having the full picture for analysis or processing. For example, a customer dataset should include key fields like name, contact details, and purchase history; if any of these fields are missing or records are incomplete, the data cannot fully support downstream processes.

Timeliness focuses on being up-to-date or available within the needed time frame, not whether all fields exist. Uniqueness concerns the absence of duplicate records, ensuring each entry is singular. Consistency ensures data values conform to the same formats and rules across the dataset, avoiding conflicting or mixed representations. Because the question asks about having all necessary fields and records, completeness is the best fit.