As data volumes and complexity continue to grow, robust data governance has become mission-critical for modern enterprises. This article explores how AI and ML can automate compliance checks, detect anomalies, track data lineage, and streamline validation processes, thereby reinforcing data quality and regulatory adherence. Drawing on real-world use cases from finance to healthcare, it illustrates the transformative potential of AI-driven governance at scale. Finally, the paper discusses emerging trends—such as explainable AI and self-healing data pipelines—that promise to redefine the future of data engineering.
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