Catalog & Cocktails: The Honest, No-BS Data Podcast

Rebecca O'Kill, CDAO of AXIS Capital and an expert in data governance, joins Juan and Tim to share insights from the Gartner Data & Analytics Summit 2025. She discusses the evolving landscape of data governance, emphasizing its critical role in enabling AI and aligning with business objectives. They explore the transformation of innovation teams and the necessity of balancing fast-paced business demands with tech strategy. Additionally, the conversation highlights the significance of collaboration and effective communication in fostering stakeholder engagement for better data outcomes.

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.

Tim and Juan take listeners on a journey through their latest observations in the dynamic data world. They dive into the recent acquisition of Data.World by ServiceNow and its implications for data as a strategic asset. Insights from the Data Governance and Information Quality Conference highlight best practices for data management. The hosts discuss the challenges of AI in data governance and the importance of treating AI as a product. Their excitement for upcoming conferences and community engagement adds a personal touch, inviting listeners into the conversation.

Barr Moses, CEO and Co-Founder of Monte Carlo, dives into the world of data and AI observability as a competitive advantage. She asserts that managing proprietary data is the true moat, not just models. The discussion highlights the importance of reliability in AI products and the necessity of human oversight. They explore the integration of data governance and machine learning practices, the evolving relationship between data and AI, and the vital role semantics play in observability. Networking insights and learning resources for data professionals are also shared.

Barr Moses shares insights on why managing data is more important than just having advanced models for competitive advantage. He explains the concept of AI observability, highlighting its dependence on solid data practices. The discussion navigates through common data challenges organizations face with AI, advocating for collaboration between data and software teams. Ultimately, building reliable data systems is essential for creating resilient AI applications.

Fresh insights from the TED conference spark a lively discussion on the exhilarating yet daunting world of AI. Tim and Juan explore the delicate balance between innovation and human experience. They emphasize the need for responsible AI development, especially as it reshapes storytelling and creative industries. Innovative concepts like an 'AI scorecard' promote ethical alignment with societal values. Tune in for a cocktail-inspired chat that celebrates the potential of technology while addressing pressing concerns!

Blake Burch, an AI & Data Leader and the first AI hire for RoboFlow, dives into the inefficiencies of modern data teams. He discusses how many teams fall victim to trendy AI pursuits but end up creating unused dashboards. Blake advocates for embedding data experts within business units and developing full-stack practitioners who can directly impact outcomes. He also stresses the need for clear business goals and effective communication in data initiatives to avoid creating "data graveyards." It’s time to rethink how we approach data!

Blake Burch tackles the pitfalls of modern data teams, often born from executive trends but failing to deliver real value. Many team members churn out unused dashboards, leading to wasted resources and data graveyards. He suggests rethinking data integration by embedding experts within business units and crafting 'full-stack' practitioners. Emphasizing clarity in business goals and measurable outcomes, Blake advocates for an experimental mindset and smaller, agile teams to truly connect data efforts with tangible business impact.

Hugo Bowne-Anderson, an independent data and AI scientist, dives into the reasons behind the frequent failure of AI applications to progress beyond the demo stage. He introduces Evaluation-Driven Development (EDD) as a solution, emphasizing continuous evaluation. The conversation covers the importance of synthetic data generation, the collapse of boundaries between data and product development, and the evolving roles in AI. Hugo also highlights the need for clear specifications and robust testing frameworks to ensure that AI applications provide real business value.

Hugo Bowne-Anderson shares insights on why many AI applications stall at the demo stage. He introduces Evaluation-Driven Development (EDD) as a solution, emphasizing continuous evaluation. The conversation highlights the blurring lines between data, machine learning, and product development. Practical approaches to testing and monitoring strategies are discussed, aiming to create AI applications that provide lasting business value. Discover how collaborative and iterative methods can revolutionize software building in the age of AI.