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

Jesús Barrasa, Field CTO for AI at Neo4j and knowledge-graph veteran, joins for a lively rant. They explore why ontologies are resurging, how ontologies serve WHAT (shared formal meaning) and WHY (interoperability, automation), how context graphs capture decision traces, and how agents and graphs accelerate AI and ontology engineering.

Kyle Winterbottom, CEO of Orbition Group and board advisor on data and AI, challenges how boards define CDO mandates. He discusses why mandates focus on platforms not outcomes. He outlines how to align data work with business KPIs. He explains when domain expertise and reporting lines matter, and whether AI will help or worsen mandate problems.

A sharp critique of how boards craft CDO mandates that prioritize technology over business outcomes. Discussion on why ROI from data projects is scarce and how accountability gaps let data leaders be enablers, not owners. Exploration of shifting role designs, decentralization into domain data heads, and strategies for influencing boards from inside.

Kierra Dotson, Director of AI strategy and former DevOps engineer, focuses on practical AI governance. She discusses breaking governance silos and engaging engineers, translating policy into code and building governance-as-code, and creating cross-functional charters and incentives to make ethical, sustainable AI a shared responsibility.

A brisk take on why AI governance cannot be left to legal teams alone. Practical analogies compare guardrails to seatbelts and brakes. Concrete tactics include educating engineers in plain language, using RBAC and model cards, and codifying rules as versioned checks. Emphasis on participation, incentives, psychological safety, and starting small with a clear RACI and iterative roadmap.

Thais Cooke, a former dentist turned senior healthcare data analyst, blends clinical experience with analytics insight. She talks about using domain expertise to spot patterns, learning SQL and visualization tools, building trust through honesty, and treating data work as problem solving rather than technical showmanship.

A wrap-up focusing on how subject matter expertise multiplies data impact. A surprising link between dentistry and analytics sparks conversation. Stories about self-taught SQL and getting started through hands-on lab work. Practical tips on balancing technical skills with people smarts and building trust through alignment.

Sanjeev Mohan, a practitioner on data strategy, and Ryan Dolley, a hands-on analytics leader, share quick takeaways from Gartner Orlando. They talk AI and agent hype. They debate semantics versus context. They call out skill gaps, agent-washing, and the push to sell outcomes over tech. Trendy vendors may consolidate soon.

Two data veterans rant about why 'context' will dominate Gartner conversations and how it outgrows metadata. They debate the execution gap where insights never reach action and why AI agents must do more than answer questions. Decision intelligence is explored as a possible bridge while warnings surface about context lock-in and the need for open standards.

Säde Haveri, entrepreneur and metadata specialist who champions semantics and data governance, explains why data must mirror an organization’s language. Short, clear takes on aligning conceptual models with physical data. Tips on prioritizing KPIs and master data. A lively case for shifting meaning work left and making metadata machine readable.