Data-Driven Clustering and Insights for Rural Development in India.

This study aims to reveal the complex socioeconomic structure of Indian villages by utilizing a dataset obtained from several government sources, which includes a wide range of 150 distinct variables. This study intends to uncover the underlying structure of these groups by using powerful data analytics and clustering approaches and further group Indian villages into meaningful clusters by finding socioeconomic differences and geographical details in India's rural landscape. The final research findings suggest a four-cluster strategy as the most insightful solution for providing a more detailed understanding of India's rural regions' diversity and its specific requirements. By describing the diversity of these clusters, this research study improves the framework for data-driven policy formation and development interventions that address the specific requirements of each group. Finally, this study highlights not only the potential of data-driven techniques in rural development, but also the importance of targeted customized solutions in solving India's rural development challenges. [ABSTRACT FROM AUTHOR]