The Data Culture Podcast

Culture eats strategy for lunch, and on this episode it eats your AI roadmap too. Sid Atkinson sits down with Mathias Vercauteren to make the case that data is the fourth production factor, AI is the fifth, and most companies are managing both with a fraction of the rigor they apply to money and people. They get into why Amazon runs circles around competitors who sit on far more data, how shadow A...

The term "forward deployment engineer" is everywhere right now, Palantir popularized it, Anthropic is leaning into it, and every data and AI platform seems to be packaging it as their answer to the last mile problem. But what is it, really? Michael Wharton, VP of Engineering at Kung Fu AI, joins Sid and Lee to cut through the noise. They dig into where the FDE model works, where it falls short, wh...

As a founder of the Berryville Institute of Machine Learning, Gary McGraw has been researching AI security since before most people knew what machine learning was. He's identified 78 risks across ML systems and was sounding the alarm on recursive pollution and model collapse long before those terms went mainstream. He joins Sid and Lee to break down what practitioners need to understand about the...

Julia Bardmesser, CEO of Data4Real and former Chief Data Officer at Voya Financial, brings 25+ years of financial services experience to a conversation about what's actually standing between companies and real AI value. She and Sid dig into why AI layered on top of broken data and workflows delivers little ROI, why the unsexy work of semantic clarity and data management at scale is now more critic...

You've heard of UX. You've heard of developer experience. Now meet AX — Agent Experience — and it's about to reshape how enterprises think about their entire tech stack. Lee Harper talks with Vihan Patel of Australia's Mantel Group about what happens when AI agents start bumping up against APIs that were never designed for them, why e-commerce is ground zero for the agentic shift, and the uncomfor...

Most data programs don't fail because of bad technology, they fail because nobody wants to talk about the hard stuff. John Ladley has spent decades proving that behavior change is what separates the programs that stick from the ones that quietly die. In this episode, he's not holding back. From walking away from clients who weren't serious to telling a CIO to admit he didn't know what he was doing...

Data governance is often seen as restrictive—but what if it’s actually the key to making data work? Bob Seiner joins Sid Atkinson to challenge how organizations think about governance, accountability, and behavior change. Drawing from decades of experience, Bob explains why governance efforts stall, what shifts when organizations focus on outcomes instead of activity, and how ownership, not toolin...

Hosts Sid Atkinson and Lee Harper engage with guests Gary Griffin and David Holcomb, authors of "Building a Data Culture: The Usage and Flow Data Culture Model", to explore the concept of data culture. They challenge the notion that culture is unmanageable, presenting frameworks and models that make culture visible and actionable. The discussion covers the three R's of data culture, the usage and...

Data management purity and pragmatism built opposed camps starting in the 1990s, and echoes of those tenants present themselves today in Generative AI. Ontology purists and vector-based engineers appear at opposite ends, but how might we reframe so everyone's in the same picture? Tracy Talbot is a consummate data practitioner and has seen it all—from mainframes to machine learning. In this episode...

Building a data program isn't all about the tech—it's about getting people to actually work together. Carlos Rivero shares what it was really like starting as Virginia's first Chief Data Officer with no team, no budget, and a lot of skeptical agencies. He talks about how he learned to be more of a "people wrangler" than a data expert, turning critics into allies and figuring out that most of the j...

Ever wonder why so many promising tech pilots never make it past the starting line? In this episode, Sid chats with Jonathan Alexander about breaking free from “pilot purgatory” and actually scaling innovation. From cavemen pushing carts with square wheels to global rollouts of cutting-edge solutions, Jonathan brings stories, strategy, and wisdom about how to get things done in a giant enterprise....

Leading complex IT systems in a major city demands more than technical know-how—it requires a shift from individual success to team achievement. Summer Xiao, Deputy CIO of Houston, shares her journey from "I" to "we," discussing the crucial transition from "doer" to "facilitator," the importance of shared ownership in large projects, and how team performance reflects directly on leadership.

State University Systems are frequently impacted by state legislation- from funding to rules, policies, and everything in between. Universities typically operate with streamlined (slim) budgets, busy staff, and with lots of focus on serving students and research. Legislators are similarly busy and concerned with many things across the state, not just the university system. Proposals and draft legi...

North Dakota is well known for energy and food production, but less known is the states roots in technology. Rep. Josh Christy discusses North Dakota's ambitions in AI, what they mean, and how North Dakota is taking a holistic approach to safety and innovation.

Successful AI projects/ideas have many necessary ingredients, one of the most important being the people you identify and choose to be part of the project. How to you decide and how to you build culture? Ron Green is a successful entrepreneur, listen in as he discusses his most current company (almost seven successful years now!) as he walks us through finding the right folks to add to the team, h...

The first Federal Chief AI Officer, Oki Mek, runs through three key components in building responsible and secure AI programs, something desperately needed in today's organizations.

How do you get all the cowfolk to giddy-up in the same direction? Smart people are notorious for having opinions; combine intelligence with the independent streak in North Dakota folks and it makes for a lot of work in driving change. Kim Weis has some insightful tips in lessons learned in trying change, failing, learning, and trying again.

Do you want some AI with that? It's everywhere, though thankfully not IN our coffee (yet). So if AI conversations are ubiquitous, how do we sort value from folly? Keatra Nesbitt is a practiced strategy leader and data scientist, listen in as she shares her thoughts on how she navigates these complex conversations with her clients.

Utilizing Gen AI towards your organization's specific needs presents both an opportunity and a challenge. Opportunity to take advantage of massive investments by large tech firms; challenges in that it can be difficult to know what is correct and usable at scale out of these projects. Sabre's Laura Palomino discusses novel approaches they've used towards that have helped her team, and others at Sa...

What does it mean to have AI ready data? And once I know that, what do I do about it? Ian Stahl is Director of Product Management @ Informatica and has seen many data centric applications come and go. He provides insights into what's happening in the market today and how we all may work better together to make data highly useable and fit for purpose.

We have come a long way since the publication of "Hidden Technical Debt in Machine Learning Systems" was published almost a decade ago. ML Ops has transformed how data science work is delivered, managed, and monitored. Great? Maybe. In this discussion we cover what is still one of the most glaring gaps in the AI/ML field. Disagreement is accepted and encouraged.

Audio from our LinkedIn Live Event! Organizational structure, team, and culture are critical components to repeatedly and consistently delivering innovation, business results, and absorbing innovative techniques from outside the org walls. AI is rightfully getting the lion’s share of attention, but to make purposed and impactful use, and to have it generate value, many teams across many people and...

Engineers are famous for building the amazing, and for wasting time on pet projects, dead ends, and losing track of the customer and real problems. How do you balance creativity and solving real problems? Jodi Blomberg, VP of Data Science at Cox Automotive, has sound, entertaining, and insightful advice!

Digital transformation has been around for a while, but have we succeeded at it? AI, for better and worse, is pushing change in organizations. One of the positives is that AI is creating urgency for organizations to do the things they have deprioritized for a long time: data management, governance, or in this case, digital transformation. Now that this is come back into focus, what are the foundat...

At the end of a spectacular achievement, the journey there can sometimes seem obvious, but we all know clarity at the start is frequently missing. Nancy Tickle was at the center of Chesterfield County's pioneering transformation in using data to forecast micro-level growth, achieving something no other city or county had done before. In this episode, Nancy offers a detailed account on how Chesterf...