Which data quality dimension refers to whether a variable measures what it is intended to measure?

Which data quality dimension refers to whether a variable measures what it is intended to measure?

• A. Accuracy
• B. Completeness
• C. Validity
• D. Accessibility

Answer: (C)

Validity is about whether the variable truly represents the intended concept or construct. If you’re trying to measure something like customer satisfaction, the data should reflect that satisfaction directly through appropriate questions or indicators. When validity is high, the measurements align with what you mean to assess, so conclusions about that concept are meaningful. You could have perfectly accurate numbers or complete data, but if they aren’t measuring the right thing, they won’t tell you what you want to know. In contrast, accuracy is about closeness to the true value, completeness is about missing data, and accessibility is about being able to obtain the data.

Validity is about whether the variable truly represents the intended concept or construct. If you’re trying to measure something like customer satisfaction, the data should reflect that satisfaction directly through appropriate questions or indicators. When validity is high, the measurements align with what you mean to assess, so conclusions about that concept are meaningful. You could have perfectly accurate numbers or complete data, but if they aren’t measuring the right thing, they won’t tell you what you want to know. In contrast, accuracy is about closeness to the true value, completeness is about missing data, and accessibility is about being able to obtain the data.