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.
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