What are data quality metrics?
Data quality metrics are essential standards used to evaluate the condition and suitability of data for specific purposes. Key metrics include accuracy, which measures the correctness of data against the real-world objects it represents; completeness, assessing the presence of all required data; and consistency, ensuring uniformity across different systems.
What are some types of data quality metrics?
Types of data quality metrics include:
- Timeliness: Checks if data is up-to-date.
- Validity: Confirms adherence to business rules and formats.
- Uniqueness: Ensures each entity is represented only once.
- Integrity: Maintains data relationships.
- Consistency over time: Ensures data remains stable across periods.
- Relevance: Measures data applicability for its purpose.
- Precision: Assesses data granularity.
- Accessibility: Gauges how easily authorized users can retrieve data.
