Ensuring data quality and governance requires comprehensive strategies across the entire data pipeline.

Data validation and quality:

• Implement data validation and enrichment processes like those provided by Snowplow's schema-first approach
• Use automated data quality testing and monitoring throughout the pipeline
• Implement proper error handling and data quality reporting for proactive issue resolution

Governance frameworks:

• Use data governance frameworks to track and manage data quality, security, and compliance
• Implement comprehensive data lineage tracking and metadata management
• Establish clear data ownership and stewardship responsibilities across the organization

Compliance and auditing:

• Regularly audit data pipelines for accuracy, completeness, and compliance with regulations like GDPR
• Implement proper access controls and data protection measures throughout the pipeline
• Maintain comprehensive documentation and audit trails for compliance reporting