Unlocking the Multidisciplinary Potential of Data Science: Insights from Apriori Analysis

Barun M. N., Önder E.

JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, vol.1, no.1, pp.1-16, 2024 (ESCI)

  • Publication Type: Article / Article
  • Volume: 1 Issue: 1
  • Publication Date: 2024
  • Journal Name: JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI
  • Journal Indexes: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Page Numbers: pp.1-16
  • Istanbul University Affiliated: Yes

Abstract

Aim This study aims to identify, analyse other fields where researchers work in data science, and provide guidance for future research endeavours. Design & Methodology Apriori analysis is applied to two different data groups using the R Studio program. Originality Data science holds paramount significance for the progress of technology and science. It is important to discern the existing studies in data science and identify areas where research is deficient. Findings Data science is used in decision and policymaking, developing learning methods for educators, breast cancer treatment, and genetic science in the health domain. Conclusion The support of data scientists to people working in other fields will contribute significantly to the development of science because of the interdisciplinary nature of data science.