In modern data-driven enterprises, trustworthy and managed data serves as the essential foundation for everything from AI and automation to strategy and compliance. However, traditional governance systems often struggle to keep pace with the sheer complexity of decentralized data across cloud and on-premises environments, where manual monitoring eventually fails to scale against millions of transactions and evolving cross-border mandates. To address these challenges, Snowflake integrates automated data quality, lineage, and policy enforcement directly into the architecture of its Data Cloud. This shift transforms data governance from a reactive afterthought into a continuous, AI-ready process, ensuring that an organization's most valuable asset remains secure, traceable, and usable without the friction of traditional silos.