Become a master at access history and column lineage in Snowflake.

In this ProTalk, you will learn:

Access History – How to: 

• Utilize Data Discovery: 
• Uncover unused data to decide whether to keep or delete it.
• Track Sensitive Data Movement: 
• Follow the data journey from external cloud storage (e.g. Amazon S3) to Snowflake tables.
• Trace the movement of data within Snowflake tables.
• After tracing, implement policies (masking and row access) to protect data. 
• Regulate access control settings for stages and tables. 
• Tag stages, tables, and columns to maintain compliance. 
• Data Validation: 
• Validate the accuracy and integrity of reports and visualizations. 
• Receive notifications before dropping or altering tables or views. 
• Compliance Auditing: 
• Identify Snowflake users who performed write operations and when. 
• Meet compliance regulations such as GDPR and CCPA. 
• Enhance Data Governance: 
• Get a comprehensive view of data access, timing, and movement from source to target. 

Column Lineage – How to: 

• Protect Derived Objects: 
• Easily tag sensitive columns without extra work. 
• Protect tables containing sensitive columns with row access policies. 
• Protect sensitive columns with masking policies or tag-based masking policies.
• Sensitive Column Copy Frequency: 
• Determine the number of objects containing a sensitive column. 
• Prove regulatory compliance standards (e.g. GDPR). 
• Root Cause Analysis: 
• Trace data to its source to solve problems. 
• Pinpoint points of failure from poor data quality. 
• Reduce columns to analyze during troubleshooting.