DMN4DQ: When data quality meets DMN
作者:
Highlights:
• Companies need high level of quality data for many contexts of use.
• DMN4DQ is a context-aware systematic method for assessing data quality.
• DMN4DQ relies on DMN to automatically decide about the usability of data.
• Organizations formalise data quality rules according to their risk appetite.
• DMN facilitates the declarative formalisation of data quality business rules.
摘要
To succeed in their business processes, organizations need data that not only attains suitable levels of quality for the task at hand, but that can also be considered as usable for the business. However, many researchers ground the potential usability of the data on its quality. Organizations would benefit from receiving recommendations on the usability of the data before its use. We propose that the recommendation on the usability of the data be supported by a decision process, which includes a context-dependent data-quality assessment based on business rules. Ideally, this recommendation would be generated automatically. Decision Model and Notation (DMN) enables the assessment of data quality based on the evaluation of business rules, and also, provides stakeholders (e.g., data stewards) with sound support for the automation of the whole process of generation of a recommendation regarding usability based on data quality.
论文关键词:Data usability,Data quality,Decision model and notation,Data quality rule,Data quality assessment,Data quality measurement
论文评审过程:Received 10 June 2020, Revised 15 November 2020, Accepted 15 November 2020, Available online 18 November 2020, Version of Record 8 January 2021.
论文官网地址:https://doi.org/10.1016/j.dss.2020.113450