To validate event quality before loading into Snowflake:

• Schema Validation: Leverage Snowplow's built-in Iglu schema registry to validate all events against predefined JSON schemas before ingestion
• Real-time Monitoring: Implement monitoring dashboards to track event validation rates, schema failures, and data quality metrics as events flow through the pipeline
• Dead Letter Queues: Configure Snowplow to route invalid events to separate error streams for investigation and reprocessing
• dbt Tests: Use dbt's testing framework to validate data quality in Snowflake, including completeness, uniqueness, and referential integrity checks
• Automated Alerting: Set up alerts for data quality degradation patterns, enabling proactive response to schema drift or tracking implementation issues

This comprehensive approach ensures high data quality while providing visibility into the health of your behavioral data pipeline.