Automated data governance involves the use of technology-driven processes and platforms to manage, protect, and optimize the quality, availability, and usability of data within an organization. It is often considered a subset of automated governance, which enforces and manages regulatory compliance, organizational policies, and decision-making across a wider business environment

Automated data governance encompasses tasks such as data classification, access control, metadata management, and data lineage tracking. Through the use of algorithms and workflows, organizations can automate the application of data policies, monitor data usage, and proactively address data quality issues. This helps maintain consistency, accuracy, and security across diverse data sets.

Key components of automated data governance include

• Automated policy enforcement
• Data discovery
• Integration of governance controls into data workflows. 

By automating these processes, organizations can streamline data management, reduce the risk of data breaches, and ensure that data is used in a manner consistent with regulatory requirements and internal policies.

Learn more about Snowflake and data governance.