Day 2 | Hall 1 - Thought Leadership and Strategic Insights

In the era of AI-driven decision-making, data quality has become more critical than ever. This session explores how poor-quality data can amplify errors at scale, leading to flawed insights and risky outcomes. It will highlight the importance of robust data governance, validation frameworks, and continuous monitoring to ensure AI systems are built on reliable, high-quality data.

Internal data platforms are becoming a core competency. The panel can explore how data engineering is borrowing from DevOps and platform engineering self-serve infrastructure, developer portals, golden paths and whether it’s working in practice.