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Data & Analytics · Foundational

Data Quality Dimensions

Measurable aspects of data quality: accuracy, completeness, consistency, timeliness, validity and uniqueness.

Definition

Accuracy means data matches reality, completeness that required values are present, consistency that data agrees across systems, timeliness that it is current enough, validity that it conforms to format and rules, and uniqueness that there are no unwanted duplicates.

Exam tip

Map each issue to its dimension: duplicate customers = uniqueness; wrong date format = validity; stale data = timeliness.

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