Contents I. Introduction
With the development of science and technology, the “information explosion” has become a feature of this era. In order to utilize these massive amounts of information data, various information systems have been established. At present, various types of applications are developing rapidly. There are common problems in the standardization of enterprise master data such as confusion, difficulty in sharing, and difficulty in migration. There are many data entries, repeated entries, and multiple codes, and the management leaders do not pay attention to them, there is no corresponding management method, resulting in low quality of the master data. The master data identification method includes the integrated weighting method [1] and the analytic hierarchy process [2]. The master data recognition technology based on the integrated weighting method integrates the principal component analysis method with the Delphi method, and designs the master data recognition score template to overcome the defects of the single weighting method. The analytic hierarchy process comprehensively considers the importance of each factor in the evaluation indicator system, so that the weight of each indicator tends to be reasonable, but there may be a risk that the two factors are different, The effectiveness of these two methods depends fundamentally on how the experts define the relationship of weights. In this paper, the weights of various factors are determined through expert comprehensive analysis. The master data recognition and scoring system is more flexible and versatile, and can be easily modified by the identification feedback to improve the optimization and scoring system, which is more suitable for the construction of enterprise master data models, especially small enterprises.
