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

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.

A concise take on why metadata must bridge systems and people. They highlight the recurring gap where data fails to speak business language. Conversation covers why AI flounders without organizational context and how managing metadata creates shared understanding. Practical focus on modeling, prioritizing core data, and making semantics machine-readable for better governance.

Nachiket Mehta, VP of AI and Data Engineering who built ontologies and event-driven teams at Wayfair. He unpacks mapping happy vs unhappy paths, the $35M trailer story, shifting data teams left into domains, tiger teams and ops visits, and turning process maps into reusable ontologies for actionable enterprise AI.

Nachiket Mehta, an experienced data leader who built Wayfair’s enterprise insights work, explains why ontology, events, and culture matter for unlocking AI. He describes tying semantic layers to real-world fulfillment, embedding data teams into domains, and turning tribal knowledge into formal context. Short, practical, and focused on shifting data left for impact.