Khaleghi, A. Akbari, M. Haedar, H.H. Mahmoudi, K. JACoW Publishing Geneva, Switzerland This research review explores the impact of data science and synchrotron technology as emerging technologies in scientific research. The research model begins with an overview of the significance of data science and synchrotron technology in advancing scientific discoveries. The research methodology involves a comprehensive analysis of interdisciplinary applications in materials science, structural biology, and environmental science. By employing data science techniques, including machine learning and statistical modeling, researchers can effectively analyze the complex datasets generated by synchrotron facilities. The results obtained from this integration showcase accelerated scientific discoveries and the emergence of new phenomena. The research concludes with a discussion on the challenges related to data quality and accessibility to synchrotron facilities, while also highlighting future advancements and emerging trends in data science and synchrotron technology. This research review underscores the transformative impact of these emerging technologies and their potential to reshape the landscape of scientific research.