The integration of big data analytics has revolutionized pest management in agriculture, offering advanced tools for prediction, monitoring, and control. Machine learning techniques have enhanced predictive modeling, allowing for more accurate forecasts of pest outbreaks and associated risks. Remote sensing technologies, such as satellite imagery and drones, enable real-time monitoring of crop health and pest activity, facilitating early detection and intervention. Integrated pest management strategies prioritize sustainability by incorporating diverse datasets and analytics to manage pest populations while minimizing environmental impact. Precision agriculture practices optimize resource utilization and maximize crop yields through data-driven decision-making. Despite challenges related to data interoperability and privacy, the adoption of big data analytics in pest management promises improved decision-making, sustainability, and resilience in agricultural systems.