Data Science and Analytics in Agricultural Development

This article examines the applications of data science and analytics in agriculture, focusing on how emerging technologies help improve crop yield, soil health, and farming efficiency. It explores tools such as satellite data, sensors, machine learning algorithms, and real-time decision systems to support precision farming. The paper also underscores the importance of farmer-centric data models and institutional collaborations to scale innovations sustainably. The authors suggest data-driven agriculture can significantly transform rural livelihoods, productivity, and resilience against climate change.