Preventing data duplication in Azure Synapse requires implementing robust deduplication strategies at multiple levels.

Upsert and merge operations:

• Perform upsert operations (merge) to ensure new events update existing records or insert only unique events
• Use SQL Server's MERGE statement or Synapse's MERGE INTO operations for efficient deduplication
• Implement conflict resolution logic for handling potential data conflicts

Pipeline-level deduplication:

• Implement deduplication logic in your Snowplow event pipeline before data reaches Synapse
• Check event timestamps, unique identifiers, and message fingerprints to eliminate duplicates
• Use Snowplow's built-in event fingerprinting capabilities for reliable duplicate detection

Staging and partitioning strategies:

• Load events into a staging table first and apply deduplication rules before moving to final tables
• Use partitioned tables in Synapse to prevent duplicate entries in high-volume datasets
• Partition data by date, user, or event type to improve deduplication performance and query efficiency