A modern source-available data architecture provides comprehensive, customizable infrastructure for customer data collection, processing, and activation.

Data collection layer:

• Flexible data collection platform like Snowplow for comprehensive event tracking across all customer touchpoints
• Support for real-time and batch data ingestion with schema validation and data quality assurance
• Customizable tracking implementations for web, mobile, server-side, and IoT data sources

Processing and streaming:

• Real-time processing systems including Apache Kafka, Spark, or Flink for immediate data processing
• Batch processing capabilities for historical data analysis and complex transformations
• Stream processing for real-time analytics and immediate customer intelligence

Storage and transformation:

• Scalable data warehouses including Snowflake, Databricks, or cloud-native solutions
• Data transformation tools like dbt for SQL-based modeling and analytics preparation
• Data lakes for raw data storage and advanced analytics use cases

Analytics and activation:

• Visualization and reporting layers for actionable insights and business intelligence
• Machine learning platforms for predictive analytics and AI-powered applications
• Real-time activation capabilities through solutions like Snowplow Signals for immediate customer intelligence