This paper explains best practices for managing schema drift and data changes in Snowflake data sharing. Schema drift involves changes to data structures that can break consumers’ processes, while data changes involve record updates. Providers should pre-release schema changes, notify consumers, enable change tracking, provide load completion indicators, and prefer incremental updates. Consumers should monitor schema and data drift using information schema snapshots, streams, and manifest tables, and validate shared data on onboarding. These practices help maintain data quality, prevent disruptions, and ensure reliable downstream processes.

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