Systematic review of data integration methods in the context of data preparation for enterprise information systems

Data integration methods were extracted from the publications, categorized and extraction process documented in different worksheets. In enterprise information systems, data-driven decision-making is a critical success factor across all organizational levels.

With the rise of paradigms such as Industry 4.0, big data, and intelligent production systems, the role of data integration within the knowledge discovery in databases process has gained increasing attention. This paper presents a systematic literature review of data integration methods, with a focus on their role in the data preparation phase of the knowledge discovery process. The study categorizes data integration methods across four key task categories: schema mapping, schema matching, data matching, and data fusion.