A Study on the Challenges and Future Trajectory of Agricultural Data Transformation in the Big Data Era

Abstract

This paper delves into the opportunities and challenges that the growth of big data has presented for the transformation of agriculture in recent years. Despite technological advances, agriculture often remains entrenched in outdated practices, and the shift toward data-driven agriculture has been slow. The urgency of this transition is underscored by the risk that if global production fails to keep pace with emerging market demands, more efficient producers will gain a competitive edge elsewhere. Key challenges identified include fragmented data sources, interoperability issues, and resistance from labor to adopting new technologies. To address these challenges, the paper suggests several measures: the adoption of interoperable data standards to ensure seamless data integration, fostering a culture of technology adoption through comprehensive training programs, and safeguarding employment by implementing retraining initiatives. These strategies are crucial for enabling agricultural entities to enhance productivity and sustainability. Additionally, they serve as a foundational guide for mapping out the transformation of the sector, ensuring that agriculture can meet future demands while supporting rural livelihoods. By embracing these changes, the industry can achieve a more resilient and sustainable future that is aligned with global food security goals.