AUTONOMOUS DATA HEALING: AI-DRIVEN SOLUTIONS FOR ENTERPRISE DATA INTEGRITY

This comprehensive article explores the emerging field of autonomous data healing systems, which leverage advanced AI techniques to address the growing challenges of data quality and integrity in the era of big data. The article examines the system architecture, self-optimization capabilities, and real-world applications of these AI-driven solutions across various industries. Through detailed case studies and aggregate results from multiple implementations, the research demonstrates significant improvements in data quality, operational efficiency, and cost savings achieved by autonomous data healing systems. The study also outlines future research directions, focusing on integrating federated learning and exploring quantum machine learning to further enhance the capabilities of these systems in distributed and complex data environments.