Tim & Juan are on the Road (Again!): Rants About Their Latest Observations in the Data World

As Season 9 of Catalog & Cocktails comes to a close, Tim and Juan reflect on the conversations, breakthroughs, and trends that shaped the past episodes. From rethinking data governance to building trust in your data, this recap dives into the standout moments, key lessons, and recurring themes from our incredible guests. Tune in for an honest, no-BS discussion on what we’ve learned this season—and a sneak peek at what’s coming next!

Join Juan and Tim as they welcome special guest Rebecca O’Kill (CDAO of AXIS Capital) fresh from their panel at the Gartner Data & Analytics Summit 2025 in London. They'll have an Honest, No-BS discussion on making data catalog and governance work in the real world while sharing key themes and actionable insights from one of the year's most influential data conferences.

Join Juan and Tim as they welcome special guest Rebecca O’Kill (CDAO of AXIS Capital) fresh from their panel at the Gartner Data & Analytics Summit 2025 in London. They'll have an Honest, No-BS discussion on making data catalog and governance work in the real world while sharing key themes and actionable insights from one of the year's most influential data conferences.

This week Tim and Juan are on the road. Instead of taking a break, they will be commenting and ranting about their latest observations in the data world: data products, semantics, AI, knowledge graphs, governance, and so much more.

Barr Moses, CEO & Co-Founder of Monte Carlo, challenges the notion that models alone create competitive advantage, arguing instead that the real moat lies in how organizations manage their proprietary data and ensure end-to-end reliability. Tim and Juan chat with Barr to get the Honest, No-BS scoop of what AI observability is (hint, it’s really data + AI) and how organizations can build resilient AI applications.

Barr Moses, CEO & Co-Founder of Monte Carlo, challenges the notion that models alone create competitive advantage, arguing instead that the real moat lies in how organizations manage their proprietary data and ensure end-to-end reliability. Tim and Juan chat with Barr to get the Honest, No-BS scoop of what AI observability is (hint, it’s really data + AI) and how organizations can build resilient AI applications.

Fresh from the TED conference, Tim Gasper and Juan Sequeda share the most thought-provoking ideas that caught their attention: What are you most excited about in the world of AI? What are you concerned about? How do you find a balance?

Data teams often emerge from executive FOMO – chasing AI trends or vague "data-driven" aspirations, but Blake Burch, AI & Data Leader, reveals most remain stuck in setup mode, creating dashboards nobody uses. Team members rarely understand how their work impacts business outcomes, leading to data graveyards instead of value, with success measured by vibes rather than revenue. Join us as Blake proposes embedding data experts within business units, developing "full-stack" practitioners, and designing initiatives that begin with clear business actions. Is it time to rethink your data team? Pour yourself a strong one – this conversation might sting.

Data teams often emerge from executive FOMO – chasing AI trends or vague "data-driven" aspirations, but Blake Burch, AI & Data Leader, reveals most remain stuck in setup mode, creating dashboards nobody uses. Team members rarely understand how their work impacts business outcomes, leading to data graveyards instead of value, with success measured by vibes rather than revenue. Join us as Blake proposes embedding data experts within business units, developing "full-stack" practitioners, and designing initiatives that begin with clear business actions. Is it time to rethink your data team? Pour yourself a strong one – this conversation might sting.Data teams often emerge from executive FOMO – chasing AI trends or vague "data-driven" aspirations, but Blake Burch reveals most remain stuck in setup mode, creating dashboards nobody uses. Team members rarely understand how their work impacts business outcomes, leading to data graveyards instead of value, with success measured by vibes rather than revenue. Join us as Blake proposes embedding data experts within business units, developing "full-stack" practitioners, and designing initiatives that begin with clear business actions. Is it time to rethink your data team? Pour yourself a strong one – this conversation might sting.

Hugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyond the initial excitement.