Which attributes define data quality for decision-making in audits?

• A. Data volume is a primary data quality attribute.
• B. Accuracy, completeness, timeliness.
• C. Data age is not important.
• D. Data accessibility is the main quality attribute.

Answer: (B)

Trustworthy data for decisions in audits rests on three pillars: accuracy, completeness, and timeliness. Accuracy means the numbers and facts reflect reality—no errors or misstatements. Completeness ensures all relevant data is captured so you’re not missing information that could change conclusions. Timeliness keeps data current enough to reflect the period being assessed, avoiding decisions based on stale information.

Data volume isn’t a measure of quality—having lots of data doesn’t guarantee accuracy or usefulness. Data age matters, because older data may no longer represent the current state. Data accessibility helps use the data efficiently, but it isn’t the main quality attribute on its own.