The quality of data is properly assessed, catalogued/ recorded, and communicated to users and applications in order to ensure that it is fit for their intended purpose and use.
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| source | AC/322-D(2024)0166 |
| Remark/Example | The principle of managed data quality ensures that data is assessed, catalogued, and communicated effectively to users and applications, ensuring it is suitable for its intended purpose and use. High-quality data is indispensable for enabling accurate and timely decision-making within the Alliance. Proper management of data quality ensures that data can be aggregated, fused, compared, and exploited effectively, facilitating informed responses and preventing potentially detrimental outcomes. By integrating business and technology and adopting a data-centric approach, NATO can leverage vast amounts of data to derive actionable insights, leading to more effective and efficient leadership. Quality data is characterized by measurable characteristics, with ISO 8000 serving as a reference guide for identifying relevant data quality indicators. Intrinsic data quality, independent of specific use, is defined by metrics related to data quality dimensions, while extrinsic data quality depends on the data's conformance to expectations within the context of decision-making needs. This distinction underscores the importance of aligning intrinsic data quality with extrinsic requirements for specific use cases, highlighting the need for regular and automated assessments of data quality dimensions and metadata to support effective communication of data quality. Progress in managing data quality is evidenced by standardized presentation of data, utilization of common data syntax and semantic metadata, comprehensive data dictionaries, and robust processes for creating and managing business vocabularies and enterprise standards. |