As organizations increasingly adopt AI and data-driven strategies, ensuring quality and reliability across the entire data + AI estate has never been more critical. This session will explore 2026 as the year of Data + AI Observability, highlighting key trends driving this transformation. Attendees will gain insights into how observability bridges the gap between data and AI systems across your data, system, code, and models, enabling more trustworthy, scalable, and efficient operations. Join us to learn practical approaches and tools that can future-proof your data and AI initiatives to drive real business impact.
talk-data.com
Speaker
Michael Segner
3
talks
Project Manager
Monte Carlo
Michael has spoken with hundreds of data teams about their data + AI strategy as the director of product strategy for Monte Carlo. He is the co-author of the upcoming O'Reilly report, "Ensuring Data + AI Reliability Through Observability."
Bio from: Big Data LDN 2025
Filter by Event / Source
Talks & appearances
3 activities · Newest first
As organizations increasingly adopt AI and data-driven strategies, ensuring quality and reliability across the entire data + AI estate has never been more critical. This session will explore 2026 as the year of Data + AI Observability, highlighting key trends driving this transformation. Attendees will gain insights into how observability bridges the gap between data and AI systems across your data, system, code, and models, enabling more trustworthy, scalable, and efficient operations. Join us to learn practical approaches and tools that can future-proof your data and AI initiatives to drive real business impact.
We know that poor data quality leads to poor performance when it comes to training and serving AI models. But how much garbage is too much?