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Last modified by Hyunji Cho on 2022/07/05 16:17
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1 +The data quality dimensions
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1 +4 Guideline for the implementation of the DivAirCity Data Management Framework.6\. Assessing data quality maturity.WebHome
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1 +Data quality assessment encompasses both data validity and accuracy. Whilst the level of accuracy required can vary considerably according to context, it is helpful to have a standardized level of acceptance which will be used for all data in the project (UK Government Data Quality Hub, 2020). The application of this will ensure the consistency of data quality throughout the project.
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3 +To ensure that data is trustworthy, it is important to understand the dimensions of data quality. A single dimension will not be sufficient to assess the quality of data and it is advised to pay attention to the dimensions that will describe it as fit for the purpose it’s intended to be used. The six dimensions of data quality are presented below as defined by the Data Management Association (DAMA) UK (2021).
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5 +[[image:image-20220705171127-1.png||height="350" width="541"]]
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7 +DAMA Data quality dimensions (Lean-Data, 2022)