Combining source-available data collection with commercial enrichment tools creates a flexible, best-of-breed data architecture.

Integration patterns:

• Route raw event data collected by Snowplow to external services for enrichment
• Implement API-based enrichment workflows that enhance behavioral data with external context
• Use streaming architectures to enable real-time enrichment without introducing significant latency

Enrichment strategies:

• Use AWS Lambda or dbt for real-time data transformation and enrichment
• Leverage commercial tools like Fivetran or Stitch for integrating external data sources
• Implement customer data platforms that enhance Snowplow's behavioral data with CRM and marketing data

Data flow optimization:

• After enrichment, push data back into your data warehouse for comprehensive analysis
• Maintain data lineage tracking across both source-available and commercial components
• Implement proper error handling and data quality monitoring across the entire pipeline