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

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.

Hala Nelson, a Professor of Mathematics and author of "Essential Math for AI," discusses the transformative potential of digital twins and AI in modern organizations. She emphasizes the importance of human-centered innovation and the critical role of oversight in AI applications. Misconceptions about AI autonomy are tackled, along with strategies for workforce evolution and the need for updated safety standards. With practical insights and an eye on future skills, she advocates for a balanced approach between technology and human values.

Hala Nelson, Professor of Mathematics and Author of "Essential Math for AI", explores how digital twin technology and AI deployments are reshaping organizational systems while challenging conventional wisdom. We will also discuss establishing a new "standard of care" in human-centered engineering and examine how these technological shifts are transforming the workforce. Join us as we untangle real-world AI implementation strategies that prioritize both technological innovation and human experience.

Patrick Cuba, Snowflake Architect, explores the fundamental connections between Data Modeling, Data Vault, and Knowledge Graphs—revealing how these approaches all center on the same core elements: business entities, their relationships, and their historical states. Patrick unpacks why, despite the AI revolution, human expertise remains irreplaceable for accountability and real business value. If you're wrestling with cognitive overload in the face of data explosion or wondering how different modeling disciplines can complement each other, this episode delivers the practical insights you need.

Patrick Cuba, Snowflake Architect, explores the fundamental connections between Data Modeling, Data Vault, and Knowledge Graphs—revealing how these approaches all center on the same core elements: business entities, their relationships, and their historical states. Patrick unpacks why, despite the AI revolution, human expertise remains irreplaceable for accountability and real business value. If you're wrestling with cognitive overload in the face of data explosion or wondering how different modeling disciplines can complement each other, this episode delivers the practical insights you need.

Jean-Georges Perrin, an expert in data governance and data mesh from the Linux Foundation, joins Tim and Juan for an enlightening discussion. They dive deep into the essence of data contracts and their crucial role in shaping successful data products. The trio explores the evolution of data governance, emphasizing the need for skilled professionals in this field. With humor, they tackle challenges in modern data engineering and the balance of centralization and decentralization, offering insights on navigating information overload through collaboration.

Tim and Juan meet in person with Jean-Georges Perrin for a longer-than-usual episode. Together, they unpack the real meaning behind data contracts, explaining how these agreements serve as the backbone for successful data products and the practical framework for data mesh implementation. If you want to cut through all the jargon and buzzwords and get to an Honest, No-BS discussion, this is the episode for you!

Frances O'Rafferty, Senior Manager at Baringa, explore sthe critical gap between data-driven aspirations and decision-making reality. While many organizations claim to be "data-driven," leaders often revert to gut instinct when making crucial decisions. We'll examine how fragmented data experiences erode confidence and how a user-centric approach that brings together data, metadata, quality metrics, and lineage in one place can build the foundation of trust necessary for truly data-driven decision making. Frances shares practical insights on creating holistic data experiences that empower everyone across the organization to trust in their data and make confident, fact-based decisions.

Frances O'Rafferty, Senior Manager at Baringa, explore sthe critical gap between data-driven aspirations and decision-making reality. While many organizations claim to be "data-driven," leaders often revert to gut instinct when making crucial decisions. We'll examine how fragmented data experiences erode confidence and how a user-centric approach that brings together data, metadata, quality metrics, and lineage in one place can build the foundation of trust necessary for truly data-driven decision making. Frances shares practical insights on creating holistic data experiences that empower everyone across the organization to trust in their data and make confident, fact-based decisions.

Krystin Kim, VP of Data & Analytics at Post Holdings and a seasoned expert in data analytics, joins for an enlightening discussion. She shares key takeaways from the Gartner Data & Analytics Summit 2025, emphasizing the transformative shift towards user-centric data governance. The conversation highlights the importance of clean data for collaboration and the critical need for clear KPIs to drive business success. Additionally, they tackle the democratization of data access, the role of AI in workflows, and the value of learning through incremental governance.