A Data Asset Quality Evaluation Model Based on a Multi-criteria Decision-making Method

Abstract:

This paper proposes a multi criteria decision making （MCDM） framework for evaluating the quality of data assets by combining the best worst method （BWM）， technique for order preference by similarity to an ideal solution （TOPSIS） and triangular fuzzy number. In this framework， firstly， the evaluation indexes are constructed through expert interviews. Then， the BWM method is used to determine the weight of the evaluation indexes. After that， experts are invited to linguistically evaluate the quality of the data set based on the constructed indexes， and triangular fuzzy numbers are introduced to overcome the problem of incomplete expression of individual real numbers. Finally， the TOPSIS method is utilized to rank the quality of the data assets. The feasibility of the methodology is verified by applying the proposed approach to data asset quality assessment of commercial banks.