Alerts and automated retraining are essential components in modern machine learning and data management systems. Alerts serve as notifications that inform data scientists and engineers about significant changes or anomalies in model performance or data quality. These alerts can trigger automated retraining processes, ensuring that models remain accurate and relevant over time. Automated retraining allows systems to adapt dynamically to new data, reducing the need for manual intervention and optimizing performance. By integrating alerts with automated retraining, organizations can enhance their predictive capabilities, maintain model integrity, and ultimately improve decision-making processes.