Big Data Analytics (BDA) in the Research Landscape: Using Python and VOSviewer for Advanced Bibliometric Analysis
- 1 Department of Data Science, Faculty of Engineering and Design, Institut Teknologi Sains Bandung, Bekasi, West Java, Indonesia
- 2 Miningtech BC Research Team, PT Berau Coal, Tanjung Redeb, Berau, Kalimantan Timur, Indonesia
Abstract
Big data analytics has become a key element in research and development in various fields. With the ability to analyze large and complex amounts of data, this technology allows researchers to identify patterns, trends, and insights that were not seen before. This article explores how big data analytics is applied in various disciplines, including computer science, engineering, and mathematics. We use Python for data processing and analysis, as well as VOSviewer for in-depth bibliometric visualization. The study highlights recent developments in big data analysis methodologies, the challenges they face, and the potential for the future. Our findings suggest that the integration of advanced analytical techniques can accelerate scientific discovery and improve understanding across different research domains.
DOI: https://doi.org/10.3844/jcssp.2025.347.362
Copyright: © 2025 Samsul Arifin, Muhammad Faisal, Monica Mayeni Manurung, Bakti Siregar, Andi Pujo Rahadi, Abdullah Eli, Gilang Ramadhan and Ilham Fikriansyah. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Big Data Analytics
- Python
- VOSviewer
- Bibliometric Analysis
- Data Science
- Machine Learning
- Research Trends
- Data Visualization