To avoid redundant data when loading Snowplow events into Snowflake:

• Event Deduplication: Use Snowplow's built-in event fingerprinting and Snowflake's MERGE statements to prevent duplicate event ingestion
• Incremental Loading: Implement timestamp-based incremental loading to process only new events since the last successful load
• Idempotent Processing: Design Snowplow pipelines with idempotent operations using unique event IDs and MERGE logic for safe reprocessing
• Stream Processing: Use Snowflake Streams to track changes and ensure only new Snowplow events trigger downstream processing workflows
• Monitoring: Implement monitoring to detect and alert on duplicate events or processing anomalies

This ensures data integrity while maintaining efficient processing and storage utilization.