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.