A Data Governance Model Based on Multi-Agents System

Data assets have become a core driver of societal development; however, data originates from diverse channels and varies significantly in quality, making it unsuitable for direct analysis and decision-making without enhancement through data governance. To address the limitations of traditional data integration techniques in meeting the multi-modal data governance requirements of massive data environments, this paper proposes a data governance model based on multi-agents system. Leveraging the powerful computational and reasoning capabilities of large language Model, this model constructs specialized intelligent agents for tasks including metadata management, data standards management, data integration, data classification and grading, and data quality management, facilitating the evolution of data management from the integration phase towards intelligent governance. The paper further illustrates the model’s application within the context of university data governance and concludes with a summary of related work.