Using an Ontological Approach to Extract Expectations About the Data Quality of Enterprise Data Warehouses

Abstract

An important role in the processes of data mining, building corporate data warehouses and developing information and analytical systems is played by data quality. The article is devoted to the formulation and substantiation of the relevance of the problem of extracting expectations for the quality of corporate storage data. Despite the numerous publications devoted to the problem of extracting expert knowledge, in the field of data quality (Data quality) and data governance in general (Data governance), this problem is underdeveloped. The aim of the study is to determine the possibility of expanding the existing problem of extracting expert knowledge by the problem of extracting expectations for the quality of data of corporate storages, proposed for further research, as well as developing an ontological model for extracting expectations for the quality of data of corporate storages. The study was carried out on the basis of the ontological approach. As a result of the study, the need for a centralized collection of requirements for the quality of data of an organization was substantiated, the problem of extracting expectations for the quality of data of corporate storages was posed by expanding the existing problem of extracting expert knowledge, and an ontological model for extracting expectations for the quality of data of corporate storages was developed.