Data validation is a tool for checking the _____ of data before adding or importing it.

• A. accuracy and quality
• B. consistency
• C. completeness
• D. timeliness

Answer: (A)

Data validation is about ensuring data is accurate and of high quality before it is added or imported. It applies rules and checks—such as data type, value ranges, formats, and required fields—to catch mistakes like numbers typed in text fields, impossible ages, invalid dates, or misspelled categories. By catching these issues upfront, validation protects the reliability and usefulness of the data you bring into your system.

While consistency, completeness, and timeliness are important aspects of data quality, the primary goal of validation in the import process is to prevent incorrect or unreliable data from entering your data stores, thereby preserving accuracy and overall data quality. Consistency checks ensure harmony across related fields, completeness checks verify that all required information is present, and timeliness checks confirm data is current; validation supports these concerns by ensuring the data entering the system is fundamentally correct.