Which data quality attribute ensures data adheres to defined business and technical logic and is considered valid?

Which data quality attribute ensures data adheres to defined business and technical logic and is considered valid?

• A. Validity
• B. Data Lake
• C. Uniqueness
• D. Timeliness

Answer: (A)

This question is about data quality attributes that certify data conforms to defined business rules and technical logic. Validity means data matches the expected formats, types, ranges, and constraints defined by the business and the system—it's about whether values are "in the right form" and acceptable for use given the rules in place. When data passes validity checks, it adheres to domain rules (like allowed values or referential integrity) and technical constraints (such as data type and format), making it reliable for downstream processes. Uniqueness focuses on avoiding duplicate records, which is important but different from ensuring data follows the established rules. Timeliness concerns how current or up-to-date the data is, not whether it conforms to the defined logic. A Data Lake is a storage concept, not a quality attribute.

This question is about data quality attributes that certify data conforms to defined business rules and technical logic. Validity means data matches the expected formats, types, ranges, and constraints defined by the business and the system—it's about whether values are "in the right form" and acceptable for use given the rules in place. When data passes validity checks, it adheres to domain rules (like allowed values or referential integrity) and technical constraints (such as data type and format), making it reliable for downstream processes.

Uniqueness focuses on avoiding duplicate records, which is important but different from ensuring data follows the established rules. Timeliness concerns how current or up-to-date the data is, not whether it conforms to the defined logic. A Data Lake is a storage concept, not a quality attribute.