Research on Multi-Source Data Fusion Methods in Information Systems for Intelligent Decision-Making

In the contemporary era of rapid advancements in artificial intelligence, the Internet of Things, and big data technologies, various types of information systems have been continuously deployed, generating a large amount of multi-source heterogeneous data during their operation. This data contains rich training value; however, due to issues such as complex sources, diverse formats, and ambiguous semantics, it is difficult to directly apply it for work evaluation and decision-making services. Based on the analysis of the challenges in multi-source data fusion within information systems, this paper investigates its key concepts and essential technologies. A multi-source data fusion framework and fusion model tailored for information systems are proposed, aiming to achieve collaborative analysis and intelligent decision-making with multi-source data. This research has practical significance for work quality assessment, personalized solution formulation, and intelligent decision support.