Data Integraion and Data Pipeline Model by Using KNIME for Research Data

Nowaday, we are in an era of data-driven decision-making that is challenging for universities to gather and analyze a large amount of data from various sources. Moreover, the data centralization in a single repository or data warehouse is required for a good quality data collection and integration along with a fast and easy data accession. This research work focuses on finding a solution to lessen the burden on personnel staff responsibility for summarizing the data of researchers linked to their research works at Mae Fah Luang University. The goal of this research is to improve a lack of research data collection and integration that meets the university's strategic plan criteria of the research publications in national and international databases while reducing data retrieval errors. The research will utilize data pipeline processes to generate the efficient research data collection and accurate mapping data including the researcher personal profiles from the personnel division relevant to the university faculties and departments, integrating with the research publications from public research databases. Finally, this work develops the business intelligence to visualize the summary of university research data. The proposed data pipeline and integration model including the business intelligence dashboard is useful for data-driven decision making for any faculties and departments in university that would be also applied to other academic institutions.