Explorez tous les épisodes du podcast The Data Culture Podcast

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 Sabre, pursue innovation and change, and be more efficient in testing, and more proactive in resolving potential issues before users find them.

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 many business units need to align on a baseline operating model. Without this, work efforts, collaboration, and implementations will continue to have marginal gains, if any.And the future will be left to the companies that have or will figure out operating models for innovation and AI.

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 foundations of effective change?

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 Chesterfield achieved remarkable results.

Software is eating the world (or used to, that was soooo 2011). AI is eating the world now at a blistering pace, and while a lot of it feels like hyperbole, and in some cases faked gains (Devin), many initiatives in AI & data are very real, and organizations are adopting and adapting their cultures to include these gains and take advantage of what they enable.

Within this astounding pace of change, we have lots of anxiety on learning and adapting. How do I stay current? Is RAG even going to be a thing a year from now?

Want some AI with your coffee? It seems anywhere you turn, AI is infused into every interaction, decision, and experience, so it makes sense that your organization should upgrade (or create) your AO strategy. But how? CDO Peggy Tsai offers incredibly practical advice on AI Strategy for today's Chief Data Officers.

"What's in a name?" Shakespeare's romantic notion that naming something is irrelevant may work in purposes of his plays, but for the data world, naming, and conformance on the meaning of names, is critical. Amit Pahwa has spent a good portion of his career dedicated to making our data lives easier, all by focusing on that most basic of tasks: naming things.

What is most useful for making decisions? Leaders and business owners face decisions almost every moment of the day. We aspire to be an entirely data driven world, so where does this leave 'gut' or intuition? Seyi Fabode helps us explore these questions; be prepared for some philosophical and practical insights.

Mergers and acquisitions have a high failure rate in terms of hitting the envisioned objectives. There are many root causes, but lack of alignment on operating models is definitely on the list. Jeremy Kingry discusses how Argano quickly analyses a target acquiree using data and enforces aligned operating models, using data!

A data strategy is an AI strategy. Subroto has 20+ years in data, innovation, and creating companies; he walks us through several topics that everyone should pay attention to in assembling their AI and data strategy.

We have worked across the globe for a while, but not everyone succeeds at it. Laura of IFC, a division of the World Bank, provides expert advice and guidance on how you might better understand your colleagues across the globe, gain understanding, and succeed together.

Emerging Leaders Series: Where do millennials get their leadership advice? There is a bias in the market to perceive that what big tech and other large progressive companies are publishing and discussing around open, collaborative, and supportive models for growing, supporting, and mentoring the next generation of talent and leaders IS the pervasive model in the market. But there are many orgs across the US and the world, with many different cultures, and many different models in how they grow and support the next generation. Stephanie Rennie shares her experiences in coming to data via the Army to her current position at Sysco.

Collaborating smoothly using data with our colleagues can be a challenge, but what about with external partners? Properly sharing insights and analytics is a challenge even today. Solomon has worked in some of the largest data environments wherein sharing and collaborating with external partners was critical to success, and has some useful insights on collaboration challenge history and what we do about it.

How can you influence change? In the minds of developers, data infrastructure, and those that manage it, can be seen as slow, stodgy, and resistant to moving quickly. Steve Jones, Advocate at Red Gate software, has lived both sides of the fence and offers his thoughts on how we may influence change that lasts.

Product management has always been an interesting intersection in looking at human desires, intents, and behaviors, the value of the system, and how to make everything smoothly interact. Throw in AI and now you have variability in both the inputs and outputs that vastly complicate the product manager's job. Reza Shirazi of Procore discusses successful ways to adapt and adopt the canon of product management methods to AI/ML focused products and their increasingly variable end user interactions.1

Buy versus build and everywhere in between - thinking through what and how you should manage your data estate can be tricky. Storable's Jerry Gregoire walks us through how he and the team break down planning and investments in their data stack so that they are lean, close to business value, and operate smoothly.

The rise in practical uses of Gen AI and AI/ML is underlining an oft forgot and but necessary step in using data: data quality and governing of data quality. DW and analytics practitioners have trumpeted quality for ages, but practical and cost effective methods haven't always been widely known or taught. Rob Hawker thankfully has published a wonderful and practical book, covering real world examples and easily applied methods. Well worth a read! Listen in as he discusses the reasons for writing, and some of the stories behind the story.

Talking about data governance is (typically) not the topic that gets people jumping for joy. Rather, governances invoke "here comes the process monster" type responses. Yet this topic is critical, and considering Gen AI and advanced analytics, becoming more rewarding and, dare say it, fun?!? to undertake. Mathias Vercauteren has been bringing forward an enlightening and engaging way to kick start data governance efforts. In this episode, we explore Mathias’ journey towards creative and empowering workshops and collaboration methods, as well as the bumps along the road.

What is data product management and the associated concepts? How should we frame and think of this so we care successful? Dr. Elena Alikhachkina has been working in this area for a while, before we had recognized naming for data product thinking. She provides some amazing perspectives that will help you and your org adopt successful mindsets and patterns.

Coaching/mentoring has seemed more art than science. Data is everywhere to guide leaders and their teams, but not always accessible. And in today's remote and hybrid world, we have lost much of in the way human observations, one of the largest tools used by leaders to guide the next generation. In this episode, Colum discusses these challenges and how AI/ML can positively impact our ability to be better and more human leaders.

Emerging Leaders Series: We have a new sub-thread to our show wherein we talk with emerging thought, tech, or business leaders in data. Discover how they got to where they are, what's next, and who to watch out for! This first episode features Matt McGuinness of Buckland.

We talk with Eckerson Group's VP of Research Kevin Petrie on the research he is conducting on LLMs and Gen AI, and what he sees coming up that organizations should pay attention to in the coming months.

How do we better frame our data management challenges so IT and business can better align and pursue value? Data4Real CEO Julia Bardmesser walks us through practical advice based on real world data challenges and transformations.

There is so much talk on data quality, yet are we actually progressing? Do we have a good definition on data quality and how big or small the problem is? Chad Sanderson walks through his thinking on the topic and how he arrived at his focus on data product thinking as a path forward for the industry.

Hypergiant's Michael Roberts has spent considerable time in the AI and data field, having collected many enviable experiences and ideas. In this episode, we pick his brain on the current state of the art and what an ex-NASA engineer thinks of current approaches.

Responsibility and Ethics discussions are thankfully coming more to the forefront when it comes to AI discussions and implementations. Even with the recent awakening, there is still much to do. Dr. Julia Stoyanovich joins us in this episode to discuss the importance in bringing AI and ethics topics to the center , inseparable from the systems being designed, implemented, or dreamed.

Join us for Episode 15 as US Data and AI Practice Director Daren Child of Kyndryl and ex-Microsoft Principal Solution Architect discusses the ecology of data systems, how they've formed, and his insights in how companies transform at scale. Daren has had the opportunity to work on both large scale and highly impactful solutions, and his insights have inspired him to write a book. Listen in!

The eternal paradox of the consultant: implement masterfully for your client, and remain jealous of all the beautiful things they have that you do not. Slalom's Karl Méhu walks us through how Slalom started their own insights and analytics transformation.Some of my favorite quotes:> Stepping over a dollar to pick up a nickel,> We've recognized that .. basically, it's was an inhibitor to our own growth> making sure also that we're not also orchestrating in a way just to accommodate legacy.That last point is critical! Karl and team made sure to look to what was needed today, and also challenge tradition so that they improved towards a bigger future.

How do you create successful and lasting change? How can organizations learn and integrate into their cultural ethos better, informed, and responsible use of data? NYU's Julia Lane walks us through key learnings she has had over the course of her career in working on and solving very large and impactful programs across the globe and provide her perspective on how to create change that sticks.

Vivid Machines' Jenny Lemieux talks through the importance of empathy and curiosity in building a compelling product, delighting customers, and building strong and high performing teams, Jenny's path towards high-tech AI enabled agriculture is unique, and affords her perspectives worth hearing more about!

Ed Kelly, Data Strategist and Texas’ first Chief Data Officer, discusses the journey Texas took in building out data programs, cultures, and capabilities. He runs through some of the key attributes of a successful CDO as well as how to win people over in building a shared vision. The path wasn’t easy, but the story is very interesting and promises some key insights into how one of the largest states moved towards a more robust data-centered culture. Favorite quotes:> CDOs today have to have a balance of understanding> [Data] It is a hardcore thing. You just gotta be able to articulate it.> [This was a] critical component to the success of the Texas program. Was learning from others and then applying it to how Texas would be able to handle it.

CEO of OpenBlock and ex Microsofter Amy Nichol walks us through building and branding a data culture program to help customers, experience gained in her role as Director of the Cloud Architect team focused on States and larger cities and counties in the United States.> "You just have to start walking. You have to get to a point where you have some kind of momentum."> "The work will be the byproduct of your capability to do the work."> "We just have to have modern data culture at every turn in our operations."

We talk with Microsoft’s Eve Machol in this session on the importance of always being a student and the art of listening. And then consulting. She discusses the importance of stakeholder identification and alignment, and never forgetting that outcomes matter most – to use her catch phrase, “put the business back into old school business intelligence.”

Our executive perspective’s episode this week features Dorman Bazzell, former CDO of North Dakota and North American Data Strategy Practice Lead at Capgemini. Listen in to our conversation as Dorman shares insightful visionary and leadership level perspectives on trust, culture, and building strategy that sticks. Trust is a key component, and Dorman layers observations and thoughts on trust throughout the conversation.

Data Culture's span the globe and have both similar and divergent ways in which they tackle data and the pursuit of insights. Microsoft's Aarshiya Gupta has worked in different continents. In her role as a Customer Success Account Manager at Microsoft in India, she walks us through global perspectives on data cultures.

Data holds two sharp edges in the domestic violence and abuse support space; reporting and analytics are critical to defining programs that help survivors and craft new ways to support them. These stories can at times be at odds with what's needed by government and funders. Listen in to Katie Hughes walk through her story to this field and how we all may better understand data and it's impact.

Data Science is still nascent and paths to being a data scientist are as varied as the people in those positions. And yet, it is a prevailing assumption that successful senior data scientists have PhDs, Masters or similar advanced degrees. Market perceptions are thankfully changing, in part due to early entrants like Andrew Kraemer. Andrew walked (sprinted) to a successful and experienced data scientist, having delivered award winning client projects, from a liberal arts degree from a small Midwestern university. His story provides salient details on a journey and a potential path for anyone wondering how one might navigate from a non-technical start to a deeply technical field.

We talk with Adam Leonard, Chief Analytic Officer at the Texas Workforce Commission, about the importance of data in decision making. Adam has a long journey in serving Texas citizens and in bringing data to the table to make better and more informed decisions. His story is interesting for many people, whether you are brand new or an experienced leader.