An Overview of Data Science and Big Data Applications in Agriculture for Smart and Sustainable Farming
S. Sheik Shalik *
Department of Agronomy, Faculty of Agriculture, Annamalai University, Chidambaram-608 002, Tamil Nadu, India.
Meyyappan M
Department of Agronomy, Faculty of Agriculture, Annamalai University, Chidambaram-608 002, Tamil Nadu, India.
*Author to whom correspondence should be addressed.
Abstract
Agriculture is experiencing a paradigm shift, driven by the integration of data science and big data technologies, which promise to revolutionize farming practices, enhance productivity, and ensure sustainability. This presentation explores the transformative role of big data in agriculture, with a particular focus on how it enables precision farming, resource optimization, and supply chain management. The concept of smart farming, driven by IoT, machine learning, and big data analytics, allows farmers to make informed decisions that significantly impact crop yield, pest management, and climate adaptation. Through the application of big data tools, farmers can optimize water usage, predict pest outbreaks, and adjust operations in real-time for improved productivity. Moreover, corporate solutions and technological innovations are providing the infrastructure for data-driven farming practices, empowering farmers to make smarter, data-backed decisions. This presentation also covers the growing career opportunities in agricultural data science and showcases case studies demonstrating the successful application of big data in enhancing agricultural efficiency. As the agricultural sector embraces the potential of big data, it holds the key to addressing the challenges of food security, resource management, and climate change, ensuring a resilient and sustainable agricultural future.
Keywords: Big data analysis, data analytics, data science, machine learning, smart farming