Before any dashboard, LLM, or ML model can generate real-time intelligence, there’s one critical question: can you trust the data feeding it?

In this session, we’ll explore how shift-left data validation turns pipelines into quality enforcers—ensuring every event collected is complete, compliant, and fit for downstream use before it enters your lakehouse.

Costas Kotsokalis, Director of Engineering will share how designing robust event tracking and governance frameworks within the Snowplow Customer Data Infrastructure (CDI) eliminates schema drift, enforces data lineage, and creates a single source of behavioral truth for analytical and AI workloads.

You’ll also see how FanDuel, America’s leading sportsbook and iGaming platform, applied these principles to achieve real-time personalization at massive scale. Operating across 24+ states under strict regulatory oversight, FanDuel built a compliant, AWS-native behavioral data platform that:

• Rapidly designed a complete tracking plan via Snowplow’s MCP Serve
• Validated millions of events in real time using Snowplow’s real-time pipeline
• Delivered user insights within minutes, not hours, during major sporting events like the Super Bowl
• Reduced engineering overhead and ETL maintenance with native AWS and Databricks integrations
• Enabled comprehensive journey visibility across all customer touchpoints
• Laid the groundwork for real-time model optimization using Amazon SageMaker

By embedding validation and governance at the collection layer, FanDuel ensured that every downstream decision—whether a personalization trigger or predictive model—was powered by trusted data.

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Video Credit: Group Futurista Nexgen Data Engineering and Data Science Virtual Summit