Jeff Chou

Managing data systems at scale often leads to hidden inefficiencies and risks that can impact business performance. Capital One will share research on how to leverage context-aware AI to drive significant cost savings compared to manual optimization and strengthen data security posture of large-scale systems. Attendees will gain actionable insights into the role and impact of context on data cloud optimization and security.

Managing data systems at scale often leads to hidden inefficiencies and risks that can impact business performance. Capital One will share research on how to leverage context-aware AI to drive significant cost savings compared to manual optimization and strengthen data security posture of large-scale systems. Attendees will gain actionable insights into the role and impact of context on data cloud optimization and security.

Despite high AI adoption, few enterprises see meaningful impact because traditional governance and security methods slow innovation. For most, governance lives outside the platform, in workflows that operate at human speed. To bridge the gap between investment and impact, enterprises must embed governance and protection into the data platform. In this session we will discuss: Governing and protecting what AI models learn from, so sensitive data can fuel training without surfacing in outputs Lineage, accountability and protection when AI agents act on enterprise data Keeping governance and protection consistent as data moves across clouds Unstructured data as the new risk surface This session is being conducted under Chatham House Rules. To foster an open and candid discussion, participants are expected to treat all information shared during the session as confidential. Information, comments, viewpoints, and materials discussed may not be referenced, disclosed, attributed, distributed, or shared outside of this session without the express permission of the organizers and participants.

Managing data systems at scale often leads to hidden inefficiencies and risks that can impact business performance. Capital One will share research on how to leverage context-aware AI to drive significant cost savings compared to manual optimization and strengthen data security posture of large-scale systems. Attendees will gain actionable insights into the role and impact of context on data cloud optimization and security.

Companies need a lot of data to build and deploy AI models—and they want it quickly. To meet this demand, platform teams are quickly scaling their Databricks usage, resulting in excess cost driven by inefficiencies and performance anomalies. Capital One has over 4,000 users leveraging Databricks to power advanced analytics and machine learning capabilities at scale. In this talk, we’ll share lessons learned from optimizing our own Databricks usage while balancing lower cost with peak performance. Attendees will learn how to identify top sources of waste, best practices for cluster management, tips for user governance and methods to keep costs in check.