Paper Contents
Abstract
The Indian food economy is a complex and dynamic system that requires accurate and timely data to inform policy decisions, manage supply chains, and ensure food security. The increasing availability of big data in the food sector has opened up new opportunities for data-driven decision-making in India. This study explores the role of big data in food economics of India, with a focus on its potential to improve food security, reduce food waste, and enhance agricultural productivity.The analysis highlights the vast amounts of data generated by various stakeholders in the food supply chain, including farmers, processors, distributors, and consumers. Big data analytics can be applied to these datasets to identify trends, patterns, and correlations that can inform decision-making at various levels. For instance, big data can be used to predict crop yields, detect early warning signs of crop diseases, and optimize logistics in the supply chain.Furthermore, big data can help identify areas of food insecurity and waste in India, enabling targeted interventions to improve food availability and access. Additionally, big data analytics can be used to develop more effective marketing strategies for agricultural products, increase consumer awareness about nutritional values, and promote sustainable consumption patterns.The study concludes that big data has the potential to revolutionize the food economy of India by providing valuable insights that can inform policy decisions, improve supply chain management, and enhance agricultural productivity. However, the successful adoption of big data in food economics will require investments in data infrastructure, analytics capabilities, and human resources.
Copyright
Copyright © 2024 Shreshth Gupta. This is an open access article distributed under the Creative Commons Attribution License.
