George Fraser, co-founder and CEO of Fivetran, blends his neuroscience background with data integration insights. He discusses the competition between data giants Databricks and Snowflake. Fraser emphasizes the significance of quality data in AI workloads and evidence-based decision-making. He shares reflections on investment strategies during the pandemic and the complexities of integrating acquisitions. Light-hearted moments reveal the quirks of video call backdrops and the balance between risk and innovation, making for an engaging and enlightening conversation.

CEO Barr Moses, Cofounder Prukalpa Sankar, and CEO George Fraser discuss scaling data quality for generative AI. Topics include challenges in data quality and trust, cultural issues, importance of data quality in AI use cases, permissions complexity in AI applications, and impact on organizational success.

Three industry experts, including Barr Moses, CEO of Monte Carlo Data, discuss scaling data quality for generative AI. They explore challenges, best practices, and governance in the age of AI. Topics include AI roles, organizational transformation, evolving AI skills, storytelling in AI, prompt engineering, and navigating the AI job market.

Over a decade after the idea of “big data'' was first born, data has become the central nervous system for decision-making in organizations of all sizes. But the modern data stack is evolving and which infrastructure trends and technologies will ultimately win out remains to be decided.In this podcast, originally recorded as part of Fivetran's Modern Data Stack conference, five leaders in data infrastructure debate that question: a16z general partner and pioneer of software defined networking Martin Casado, former CEO of Snowflake Bob Muglia; Michelle Ufford, founder and CEO of Noteable; Tristan Handy, founder of Fishtown Analytics and leader of the open source project dbt; and Fivetran founder George Fraser.The conversation covers the future of data lakes, the new use cases for the modern data stack, data mesh and whether decentralization of teams and tools is the future, and how low we actually need to go with latency. And while the topic of debate is the modern data stack, the themes and differing perspectives strike at the heart of an even bigger: how does technology evolve in complex enterprise environments? We're re-running this episode as part of a special report on Future.com, the Data50: the World's Top Data Startups, which covers the bellwether private companies across the most exciting categories in data, from AI/ML to observability and more. 

Lakes v. warehouses, analytics v. AI/ML, SQL v. everything else... As the technical capabilities of data lakes and data warehouses converge, are the separate tools and teams that run AI/ML and analytics converging as well?In this podcast, originally recorded as part of Fivetran's Modern Data Stack conference, five leaders in data infrastructure debate that question: a16z general partner and pioneer of software defined networking Martin Casado, former CEO of Snowflake Bob Muglia; Michelle Ufford, founder and CEO of Noteable; Tristan Handy, founder of Fishtown Analytics and leader of the open source project dbt; and Fivetran founder George Fraser.The conversation covers the future of data lakes, the new use cases for the modern data stack, data mesh and whether decentralization of teams and tools is the future, and how low we actually need to go with latency. And while the topic of debate is the modern data stack, the themes and differing perspectives strike at the heart of an even bigger: how does technology evolve in complex enterprise environments?