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Data Quality

Data Management

Data Classification Information Governance Data Integrity Data Accuracy

Set of dimensions (accuracy, completeness, consistency, timeliness) used to assess dataset reliability.

Definition

Data quality includes accuracy, completeness, consistency, timeliness, and validity. Poor quality can cause privacy incidents (misdelivery, over-sharing) and faulty analytics or automated decisions.

In plain English Set of dimensions (accuracy, completeness, consistency, timeliness) used to assess dataset reliability.

Why this matters

Why it matters: Higher quality supports safer processing and reduces unintended disclosure.

Example

Example: Implement deduplication, validation, and monitoring; restrict access to raw datasets and fix upstream collection errors.