Adam Segal

While data scientists focus on model fine-tuning and weights, data engineers are left to handle the messy reality of the underlying data plumbing. If you don't know exactly what tables feed your vector stores or what transformations they went through, your AI strategy and sovereignty is operating blind. This presentation guides you to mastering the only part of the AI stack you fully control by implementing robust data lineage. We will map out exactly how to build a verifiable chain of custody using automated metadata capture. Learn how to trace data hops through complex pipelines, intercept compliance risks (like GDPR-regulated fields) before they reach model context windows, and use a centralized Knowledge Hub to assign data ownership. Stop trying to piece together lineage retroactively from spreadsheets. Discover how to establish the rigorous, automated data foundation required to back up your enterprise's AI claims.

Institutions are drowning in complex, fragmented data ecosystems, slowing down AI adoption, increasing compliance risks, and making data governance a burden. Without clear data lineage automation, organizations struggle with data trust, explainability, and operational inefficiencies. In this session, Adam Segal, Senior Solutions Engineer of Cloudera Octopai Data Lineage, will reveal how automated lineage and metadata intelligence can: Unravel the data mess by mapping end-to-end lineage across hybrid environments Ensure AI readiness with traceable, high-quality metadata flows Simplify compliance with real-time visibility into data movement and ownership Empower teams by making data accessible without IT bottlenecks Discover how leading organizations turn automated data lineage into a competitive advantage, ensuring data clarity, compliance, and increased adoption of AI-driven innovation.