Provide data quality management model for data governance using meta synthesis

Abstract

All organizations use data to execute their processes. Organizational data is either generated by the organization itself or created and provided by other organizations. Data and information play an essential role in the decisions and functions of organizational processes. For this reason, data is part of the organization's resources and perhaps the most important source of organizations. The purpose of this study was to provide a data quality model for data governance. The research method was used in a meta-combination. Therefore, out of 268 sources found, during the meta-combination process, 62 articles were used using keywords such as; data, data management, data governance and data quality management were selected in IRANDOC, Science Direct, Google Scholar, Springer, IEEE and ACM databases between 1995-2022. In this study, first a code was considered for all factors extracted from previous studies and then, considering the concept of each code, they were classified in a similar concept. In this way, the concepts of research were identified. Two coders were used to control the extracted codes and categories, and the desired index in this field is the Kappa index. Based on the analysis performed using the content analysis method, a total of 12 main categories (data attribute, data, data fable, data value, initial data value, data pattern, data set, data access, data composition, data formatting, metadata and data objectivity) and 47 sub-categories for data quality management for data governance were identified.

Keywords

• data quality
• data governance
• quality management
• meta synthesis