What is the significance of consistency in data quality metrics?
- It ensures that data is uniform and coherent across different sources and applications
- It focuses on the timeliness of data updates
- It measures the completeness of data within a dataset
- It validates the accuracy of data through manual verification
Consistency in data quality metrics refers to the uniformity and coherence of data across various sources, systems, and applications. It ensures that data elements have the same meaning and format wherever they are used, reducing the risk of discrepancies and errors in data analysis and reporting. Consistent data facilitates interoperability, data integration, and reliable decision-making processes within organizations.
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