基于云模型的企业数据资产质量评价模型

Enterprise Data Asset Quality Evaluation Model Based on Cloud Model

摘要:

结合云模型与最优最劣法（best worst method，BWM）、逼近理想解距离法（TOPSIS）提出一个综合考虑定性与定量指标的数据资产质量评价模型。首先，构建数据资产的质量评价指标体系，并基于云模型的黄金分割法将单个自然语言评价等级值转化为云模型；其次，分别对定性和定量指标计算评价群决策值，并结合基于BWM获取的指标权重计算得到云‐TOPSIS决策矩阵；再次，基于TOPSIS对评价方案进行质量排序；最后，将所构建模型应用于阿里云公开数据集的质量评价，验证模型的可行性与有效性。

Abstract:

A data asset quality evaluation model considering qualitative and quantitative indexes comprehensively was proposed by combining the cloud model with the best worst method （BWM） and technique for order preference by similarity to an ideal solution （TOPSIS）. Firstly， the quality evaluation index system of data assets was constructed， and the individual natural language evaluation value was transformed into the cloud model based on the golden section method of cloud model. Secondly， the evaluation group decision value was calculated for qualitative and quantitative indexes respectively， and the cloud-TOPSIS decision matrix was obtained by combining the index weights from BWM. Thirdly， the evaluation schemes were ranked qualitatively based on TOPSIS. Finally， the constructed model was applied to the quality evaluation of Alibaba Cloud’s public datasets for the verification of the feasibility and effectiveness of the model.