2987: Why Every Business Needs a Chief Data Citizen: Lessons from Collibra

[00:00:01] Welcome back to the Tech Talks Daily Podcast. Now, at the end of every episode, I always ask each and every one of you to message me, email me, anything at all. Tell me what you thought of the show. And I do that for good reason.

[00:00:15] I had a lovely surprise today. A big thank you to Bjorn von Siemens. He's the founder at CareSyntax and an investor in precision surgery, AI, robotics, and much more. But he tagged me in a LinkedIn post that I was the soundtrack to his run.

[00:00:32] He was listening to one of the interviews, absolutely loved it, and took the time to share that on LinkedIn. This got me thinking, where do you listen to this podcast?

[00:00:40] I believe Bjorn's based in London, and I know loads of you listen in the US, and you're just scattered all around the world. So let me know, where do you listen to this podcast? And Bjorn, it's truly an honour to be the soundtrack of your run.

[00:00:54] So as you're lacing up for your next challenge, listening to maybe this episode, I'm going to try and inspire you now. Remember Bjorn, every step you take is not just a stride in your run, but a leap towards transforming the future through innovation.

[00:01:10] Keep pushing them boundaries and keep setting the pace, both in your runs and in your visionary work. And if that doesn't inspire you, I don't know what will. So Bjorn, big thank you for listening to the podcast, but on with today's episode.

[00:01:27] And the big question I ask for you all today is, how can data shape the future of our workplaces and influence the trajectory of AI development? Well, today I'm going to be joined by Felix, the CEO of Calibra.

[00:01:42] And he's been pioneering the concept of something called the Chief Data Citizen that exists within the realm of data governance. And at a time where most organisations are just beginning to grasp the critical nature of C-suite roles in AI, Calibra seems somewhat ahead of the curve.

[00:02:02] So Felix is going to be joining me today to discuss the revolutionary role of the Chief Data Citizen, its impact on both AI and data operations and why it's a role that could be instrumental for other companies aiming to harness data for strategic advantage.

[00:02:20] I want to take a time out to express my gratitude to everyone who supports my mission of delivering daily content to you in 165 countries. I couldn't do it without you, and I couldn't do it without my sponsors.

[00:02:32] And today I want to give a quick shout out to Kiteworks, who recently told me that defence contractors are facing immense pressure to comply with things like CMMC 2.0 security standards. And finding a secure, easy-to-use file sharing platform that meets those guidelines can be a big challenge.

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[00:03:14] And while others struggle with DIY approval processes and clunky apps, you'll breeze through with their zero-trust framework. So don't let compliance slow you down is what I'm trying to say. Simply visit kiteworks.com to get started.

[00:03:28] And visit kiteworks.com to learn more about Kiteworks' secure content platform for CMMC compliance. But with my thank yous out of the way, it's now time to jump right into today's interview with our fantastic guest.

[00:03:42] Buckle up and hold on tight as I beam your ears all the way to New York where Felix is waiting to share his story. So a massive warm welcome to the show, Felix. Can you tell everyone listening a little about who you are and what you do?

[00:03:58] Absolutely. Great to be here. Thanks for having me. So I'm Felix van der Baelen. I'm the co-founder and CEO of Culibra. Culibra, we're an enterprise software company focusing on data governance. And what that means is that we help typically larger organisations do more with trusted data.

[00:04:16] We help them understand what data they have, how it's being used, making sure that they understand the quality of the data, understand how that data is flowing through all the different systems to be used in a report or, of course, nowadays in an AI model.

[00:04:30] And so that's how we're really helping large organisations, like I said, do more with trusted data. And it's so refreshing to hear you talk there because you mentioned data about nine, ten times. AI just once, you know, the other way around.

[00:04:46] And of course, AI is useless. It's nothing without that data. But I've got to ask, before you came on the podcast, I was reading about how you created the Chief Data Citizen role.

[00:04:57] So straight away, I know you're passionate about data, but can you tell me more about what inspired that decision and how this role has evolved since its inception?

[00:05:07] Yeah, absolutely. Maybe let me take a step back first and talk a little bit about kind of when we started Culibra, why we started Culibra, because I think that makes sense and how we felt about the Chief Data Citizen's role and why it's so important.

[00:05:19] So we started Culibra in 2008. So we've been at it for a while before data was, you could argue, as sexy as it is now in the context of AI.

[00:05:29] But we always believed that to really get value from data, you need to be able to bring people together and to agree what that data means. Because if you don't agree what data means in the right context, it's basically meaningless. And when it's meaningless, there's no value, right?

[00:05:43] So we did a lot of research at the University of Brussels. We actually spin up the University of Brussels, where we did a lot of research on semantic technologies, like how do you capture the meaning of data?

[00:05:54] And so we took that research, started the company in 2008, and you remember 2008 financial crisis? So that's really where we found that it's a product market fit because suddenly all of the banks had to prove to the regulators that they were in control of their data.

[00:06:08] They had to prove to the regulators that if they showed them a number, how did they calculate that number? How did they combine all the data from all these different sources that ultimately led to that number?

[00:06:18] Because if you don't understand that, there's really no way you can trust the reports. And at the time, that was an acute problem. And I'll fast forward to AI, which again today, very similar problems.

[00:06:29] But over the last 15 years, we've worked with so many organizations around their data, around their data maturity. And if you take a step back and look at what has happened over the last 15 years, there's been a tremendous amount of innovation in what I call data infrastructure.

[00:06:45] We've done so much work on building better, faster databases to deal with store, compute, consume more and more data volumes of data.

[00:06:55] And now, especially with the move to the cloud, we see Microsoft and Amazon and Google and Databricks and Snowflake have these incredible technologies for us to store more data, process more data, do it at scale, do it more efficiently and so forth.

[00:07:10] Now, what we've seen with a lot of organizations and what we fundamentally believe is that to really get value out of data, whether it's for AI or reporting or business automation, digital transformation, just a way to store process data is just one part of the solution.

[00:07:24] The bigger challenge is really much more of a people and process challenge. We fundamentally believe that just having a bigger, faster database isn't going to help you truly get more value from your data.

[00:07:38] And this is really why we've come up with this term, this leadership role, which we call the chief data citizen, because it's really how do you build a culture of data? How do you build a data maturity in the organization?

[00:07:51] It's a lot of the change management that you need to drive through an organization to educate organizations what the opportunities are with data and what the potential risks are with data. And this is why we like this idea of a chief data citizen.

[00:08:06] As a citizen, we believe you have rights and you have responsibilities. We believe that everybody today has the right to easily access trusted data because almost everybody needs data to do their job.

[00:08:20] Whether you're an analyst, whatever role you have, you're probably using data directly or indirectly to do your job.

[00:08:26] And frankly, nowadays, everybody who's using chat GPT or cloud or whatever kind of AI model is using data because all these models ultimately, to your earlier point, are just really a user interface on top of vast amounts of data. We are all using data.

[00:08:43] So we have the right as a data citizen for easy access to trustworthy data. We also have responsibilities as we all do as citizens. There's a level of control. You can't just do whatever you want and that holds true for data as well.

[00:08:55] But with the fact that data has only become more and more important, we've also seen the scrutiny around privacy, security, compliance only increase. We had data privacy with GDPR in Europe, CCPA in the US.

[00:09:09] Now in this age of AI, I think there's a lot of attention of, okay, we all want to do AI, but how do we do it in a trustworthy way? How do you need to do AI governance? And so that's a big focus.

[00:09:20] And so we really like this balance as a data citizen to have easy access to trustworthy data, but also understand how you use that data responsibly. And so how do you then drive that kind of change management maturity in an organization?

[00:09:36] We believe that chief data citizen is a great way to kind of lead from the front and show the organization, this is how we're going to get more out of our data. And so this is really kind of the vision of Kulibya.

[00:09:48] And this is kind of how we made that real true, what we call the chief data citizen. And he's such a forward thinking vision. I absolutely love it. Not to mention incredibly cool job title for someone as well.

[00:10:01] But can you elaborate on the responsibilities of that chief data citizen that you created and how that role maybe supports the overall data strategy at what you're doing at Kulibya? Absolutely.

[00:10:12] And so we call it the chief data citizen because we want to kind of enforce the importance of the people side of things, the change management. Typically what that role is typically called in organizations as a chief data, chief analytics officer.

[00:10:26] And this is kind of a trend that again, you've seen over the last 10 years, I think 10 years ago, Capital One was the first organization with a chief data officer. And then a lot of the banks followed.

[00:10:37] And again, the first responsibility of a chief data officer was compliance in financial services and then in healthcare and pharma. Data is valuable, data is important, and we need to make sure we control the data.

[00:10:48] So the initial focus of the chief data officer, it was really on trust, compliance, control. So that's still today one of the responsibilities of a chief data citizen or chief data analytics officer. How do we make sure we trust the data?

[00:11:02] How do we make sure we know what data there is? So they typically responsible for the data governance programs, data maturity programs, compliance, reporting, and so forth.

[00:11:14] Over the last few years, you've seen the shift from what we call playing defense to play offense, where it's not just about compliance. Compliance doesn't go away. Everybody needs to comply with privacy regulations.

[00:11:26] And that's typically a clear responsibility of the chief data officer together with the privacy team and legal team. Everybody is responsible for data security. And again, that's a partnership typically between the chief data officer and the CISO or the CIO.

[00:11:39] But now a lot of organizations are also thinking, okay, how do we use data to do more, to drive our business, to drive our automation, to build digital services?

[00:11:48] How do we make it easier for people to find data so they can do their analysis and optimize their work?

[00:11:54] And so this is where the shifts have come from only complies to much more about, okay, how do we make it easy for people again to find the right data?

[00:12:02] And this is where a lot of those chief data analytics officers, this is where the analytics part of the chief data analytics officer role came in. To really enable the organization to almost wrap kind of self-service analytics.

[00:12:15] So you don't rely on a small team that makes all the analytics, but everybody in the organization is empowered to find data, use data again to do their job. And how do you make it easy? How do you enable that?

[00:12:27] And what most of those leaders do is they create a data marketplace. And again, I like it to like Amazonification of data where on Amazon, you shop for a product, you see the reviews, you see comments, you see ratings, you add it to your shopping basket.

[00:12:41] And the next day, it's literally in front of your door delivered. How do you deliver a same experience with respect to data? Imagine I'm in marketing and I want to do customer trend analysis for a sales region in New York, for example.

[00:12:55] Okay, the first problem is where do I find the data that I need to do that work? And typically it's calling, asking a lot of people because they have so many databases, the data spread around, it's kind of everywhere.

[00:13:08] Well, with a data marketplace, you're able to really easily find that data and understand if it's appropriate, what the quality is, how do I get access? And so something that used to take probably weeks or even months from time to time can now take hours.

[00:13:21] And so that's another responsibility of a chief data citizen to enable the whole organization to find and use and access data in a much more efficient way. And so that's typically their responsibility. They often partner with the CIO and CTO. Again, from an organization to organization, it depends.

[00:13:37] Sometimes they also own the infrastructure, the platform, sometimes underlying platform, the data warehouse and so forth might be owned by the IT and the technical team. So there's some dependencies from organization to organization, but that's typically the responsibility of a chief data analytics officer.

[00:13:54] And there's so much change happening in workplaces around the world at the moment. So I'm curious, how does this chief data citizen role contribute to enabling this new future of work?

[00:14:05] While also, of course, addressing the growing importance of data in the global business community, especially when we're talking about AI as well, which is no avoiding. So what do you see here?

[00:14:16] I think the biggest disruption, maybe the disruption of the right word, but the change that's going to come out of the workforce is going to be AI. How are we going to incorporate AI in the way we all work? Is it going to display some workers?

[00:14:30] Is it going to make us all more efficient? How is it going to shift where we focus, focus more on creativity versus got repeatable tasks. So I think there's a lot to still discover and see how things are going to play out.

[00:14:41] But I think that there's a certainty that it will change the way we work. And again, this is why I believe that the chief data analytics officer, the chief data citizen has such an important role to play.

[00:14:49] And the way we talk about it to our chief data citizens is that they have an opportunity to be the hero of AI. And why do we say that? It's because the biggest challenge that we are seeing with organizations trying to put AI in production,

[00:15:06] it's not actually the development of the models or the use cases. It's really making sure that we're able to trust those use cases, to trust the data that we're using to train those models, to fine tune those models, to track whatever architecture you want to use.

[00:15:21] How are you using that data? And are we confident enough? Are we certain enough that this is appropriate use of the data? So we actually put those use cases in production. And I think that's going to be the biggest challenge that we're going to see with AI.

[00:15:34] Today, it's still very much experimentation. And I think what we see now is moving from experimentation to in-production. It's a big step and it's probably the biggest step. And it requires a lot of collaboration between different stakeholders.

[00:15:47] Privacy team, legal team, engineering team, data team, the risk team, of course, the business stakeholders. All of them need to work together to make sure, okay, we feel good about putting that model in production or using a certain AI capability internally. Are we going to use employee data?

[00:16:04] I mean, that's very sensitive. We don't want that to be. How do we make sure that any kind of sensitive data is not going to be disclosed or accessible by the wrong people? So all of these concerns are real.

[00:16:14] And again, the chief data citizen, the chief data officer has a really important role to play because they play a pivotal role in coordinating between all those different stakeholders

[00:16:24] to make sure there's confidence and trust and the right documentation and traceability and quality to move AI from experimentation to production. And that's where I think that the chief data officer can be the hero of AI.

[00:16:38] I think the most frustrating thing for data scientists once they build an amazing model or use case is for it to go nowhere. And it's illegal to say, no, we can't do it. Right? That's the worst for everyone.

[00:16:49] We spend time, resources, efforts ultimately for it to go nowhere. And so how do you move from a no to a yes? Again, the chief data officer has a really big role to play there.

[00:16:58] And I suspect there'll be a lot of people listening, especially business leaders, thinking exactly, oh, I get this. And a lot of what you're saying will resonate with them, especially the need for this chief data citizen or chief data officer roles.

[00:17:11] Can you just expand on that for anyone sat on the fence? Why do you think it's essential for other companies to appoint these roles and the kind of benefits that they can expect to see from this role as a result?

[00:17:22] I think it's good to look and we're really seeing the role continue to increase. There's more and more chief data analytics officers. It's still a relatively new role. There's a lot of evolution as you typically see in these new roles.

[00:17:37] There's a lot of change with those roles as well. So it's still a role that has to kind of find its footing.

[00:17:43] And I think the reason why this role continues to be important is going back to what I said in the very beginning, this understanding that look, a bigger, faster database alone is not going to get us there. It's valuable, it's important, but it's not enough.

[00:17:58] And so you have to build that data culture in the organization. You have to make it easy. You have to make sure we do it appropriately with right controls and visibility and documentation and automation. And that's absolutely critical.

[00:18:11] And that's typically what a purely technical team is not that focused on. They're focused on how do we make it faster, cheaper, better, more scalable, and so forth, which is again very important. But that's really that partnership is really important.

[00:18:22] And so the companies that do that the best are the companies that have a strong chief data analytics officer role and team and function in the close partnership with the IT and engineering function that do that together.

[00:18:34] McDonald's is a great example, a customer, they rolled out to Columbia in 60 days in 25 different countries and languages. And again, it's such a big part of the digital transformation. And we have many examples like this. And so I think it's a role that's only becoming more important.

[00:18:50] And I think AI has got to be another accelerator for this role to really hold an organization. And there's a lot going on there. You mentioned AI and there's so many different things all converging.

[00:19:04] And I know this is a huge question, but in your opinion, what would you think the relationship is between data governance, the rise of AI, et cetera?

[00:19:13] The role that chief data citizens play here as well, because there seems to be a lot happening, but it makes sense to bring it all together with this chief data citizen. But what do you see this relationship being?

[00:19:26] I think the importance of AI governance is becoming very apparent to every organization. Like I said, the big challenge of how do you move AI use cases, whether you acquire them or you build them yourself from testing experimentation into production.

[00:19:43] And so governance, I think is a key there. And AI governance, you think about what is required to do AI governance. It's really an extension of data analytics governance. Whether you're looking at a Tableau report or Power BI reports, again, it's consuming data for analytical purposes.

[00:20:01] An AI model is also consuming data for automated, kind of automation gen AI purposes. It's very similar. The needs to govern it is again very similar. So it's very much an extension of what a lot of organizations are already doing.

[00:20:15] So it's not that much of a leap to go from data analytics governance to AI governance. A lot of the best practices are the same. And so the way we think about that, if you think about AI, you really have to think about the AI use case.

[00:20:27] Again, if you have a purely technical perspective, you think about the model. I read about all those models in the news every day, these frontier models and open AI and CLAUDE and NOLALA recently in the news and again in open source. That's fantastic, right?

[00:20:43] All these models that we're going to continue to see more innovation and better and better models. The reality is most organizations are going to probably use a model, small model, big model, open source, public, closed source.

[00:20:52] But then they're going to use their own proprietary data and apply it on top of that model to deliver a use case that's very specific to them. It's very rare that organizations are going to use a public frontier model without their own data.

[00:21:07] And so this is really important because a use case is a combination of the model, like what model am I going to use? And it's a lot of again, copyright constraints or concerns around that. What data am I going to use?

[00:21:19] And for what purpose am I going to use it? Is it an internal chatbot to make it easy for employees to understand our support documents?

[00:21:27] The risk of that is a lot lower than if it's an externally customer facing model that's going to automatically recommend loans to our customers. Right? I mean, the chance of the risks is a lot higher.

[00:21:41] So you have to understand the use of the model, the data in the context of what is being used for. And so that combination creates a risk profile. It requires documentation traceability, and it goes through a change management process.

[00:21:55] It goes through a workflow lifecycle from experimentation, control, validation, monitoring to production. And that change management process needs to be supported. And again, that's what people are doing for data governance.

[00:22:08] That's what every bank is doing to comply to the financial regulations that there are in the scrutiny on. They call it the critical data elements. They need to understand the critical data elements that they're using to report to the regulators.

[00:22:19] And it goes through exactly the same lifecycle where you need to document it, you need the lifecycle, you need the traceability, you need the documentation, responsibility, quality, and so forth. Again, that's exactly the same for an AI use case.

[00:22:32] And again, that's why that role of a chief data analytics officer is so important. And it's such an opportunity to accelerate the adoption of AI and GeneXus AI. And many business leaders are incredibly cautious and have a little concern around things like AI and data governance, etc.

[00:22:50] So actually, how are you ensuring that these data governance practices are robust enough to support effective AI workforce implementation, etc.? Anything you can share around them? Absolutely. We want to lead from the front and set the right example.

[00:23:05] So we have our own chief data citizen, one of our co-founders, our chief data citizen. He leads our data office. He's also responsible for AI governance, which we've implemented in our product like many other customers have.

[00:23:19] And so we use, of course, AI in our own product internally to drive automation and AI capabilities for our customers. And so our customers rightfully ask us, okay, what data are you using? Are you using our data? And what way are you using that?

[00:23:32] What models are you using? Where are we hosting? So all the questions that anybody would ask.

[00:23:37] And so this is why we are adopting our own AI governance solution through our data office with our chief data citizens leading that to make sure we've documented all of that and using that appropriately.

[00:23:49] And then the result of that kind of AI governance lifecycle is a model card or a use case card. And this is where we have documented all the usages of AI algorithms and models in our product. And I could easily show that to our customers.

[00:24:04] We actually have it publicly on our website. And so there's a lot of transparency and that creates a lot of trust and confidence with our customers that they understand how we're using AI, what data we're using, how we're using that data. And I think that's a best practice.

[00:24:19] It's the outcome of a good kind of AI governance practice supported by a great platform. And I think that's a way a lot of our customers are planning to adopt that as well.

[00:24:30] And assuming we have people listening today that are fully on board with everything that you're saying here, maybe they're even considering having listened to you about creating their own chief data citizen.

[00:24:40] They've got to then go pitch that to the board almost to determine ROI, business value of this kind of role.

[00:24:48] So do you have any examples or maybe a success story where the chief data citizen role has made a significant impact on Kaliber's operations or strategy just to help people listening understand the kind of value that it can offer? Absolutely. And I'll take a step back.

[00:25:07] If you think about if you as an organization believe that data is important for your organization, I would argue which organization is going to say that data is not important, especially in the world of AI. It's a hard thing to argue that data is not important.

[00:25:21] But if the data is important, you need a system, a business application to manage that data, to manage all the business processes around how the data is produced and consumed. And this is nothing new. We have an application that helps us build products like Atlassian.

[00:25:38] Many companies are using Atlassian to build software products. Many companies are using Salesforce to run their sales organization, to run their sales function. Many companies are using Workday to run their HR organization. Many companies are using ServiceNow to run their IT organization.

[00:25:53] But you need a system to run your data organization, right? It's not just a database. You need to really run your data organization so it's efficient, effective, and you stay in control from a compliance and security perspective. And that's really what Kaliber kind of is.

[00:26:06] And this is really what the chief data officer is responsible to run. And so we have many customers where we have very strong examples of how they do that. Maybe two top of the minds. One is Heineken. I think we all know Heineken, great beer.

[00:26:22] And so they are on this very important digital transformation journey as a core strategy. And for them, what's absolutely critical is that they have a deep understanding of their end consumers. And they don't typically sell directly to the end users or end consumers.

[00:26:37] They sell to retails and things like that. So how do they really understand their end users? And so data is incredibly important to them. And step one, which they realize, is that we can't really do anything with our data until we all speak the same language.

[00:26:54] Because that seems like an obvious problem, but it's a real problem in large organizations. When I say we have 1,000 customers and you say, no, we have 2,000 and we're both right. That's not possible. We just have different definitions. We've got them in different ways.

[00:27:09] There's a lot of nuance and specificity on how you use data. And so step one is often, how do we create a shared language that at least we're able to use data in a consistent way where we actually trust the results?

[00:27:22] Otherwise, we just argue about whose number is right. And that's something that we see all the time in large organizations.

[00:27:26] And so that's a great example of how they've built that data culture by initially just building a shared language around what are the key concepts, how are they using the data, and it's been very effective for them.

[00:27:36] Another great example is Estellus, a big Canadian telecommunication company where, again, data is a big part of their strategy. And their chief data officer, they actually have the title of data enablement, which I think is a great title.

[00:27:51] Because in the words it says, we're enabling the organization to do more with data. And a big part of their focus was how do we make it easier for people to find the right data?

[00:28:01] And things that took maybe weeks or months to be able to find the right data set so I can do my analysis or use that data for my job, now takes days to hours. So there's a tremendous acceleration of helping people find the right trusted data.

[00:28:15] And so these are just two examples of large organizations that have been very successful with that data organization with a very strong data leader driving that. So many great points there. And of course, we're only five months away from life in 2025.

[00:28:29] So if we look ahead, how do you foresee the role of the chief data citizen evolving, especially as data continues to play a central role in business operations and AI development? We're going to be hearing a lot about data and the importance of data.

[00:28:44] How do you see this role evolving? Absolutely. I think it's the elephant in the room, no surprise to anybody. But I think AI is going to be the number one driver. It's really a step function in the importance of data. Again, AI is all about the data.

[00:29:00] It's using the data and the chief data citizen has an enormously important role to play. So that's going to be, I think, primary number one focus for all data leaders. So what does that mean? I think a couple of things.

[00:29:14] One, the types of data that you need to manage, I think is expanding. Typically, we focus on more structured data and databases, I think in an age of generative AI. And structured data, documents, PDFs, I think become really important. And so extending the types of data to manage.

[00:29:32] Two, we have seen a lot of fragmentation and complexity from a technology perspective. And there's so many different tools out there that do kind of different things. And I think we're starting to see a consolidation in broader platforms, just to make it easier, simpler.

[00:29:47] And let's be honest, everybody today is required to do more with less. And I think that's the way, including data leaders. So consolidation capabilities into kind of big platforms. That's one. And three, I think there's an incredible opportunity to also use AI internally

[00:30:04] to automate a lot of the manual stewardship and governance tasks. For example, in our product, we have the ability to automatically generate definitions for terms. And that's such a big difference versus starting from an empty page,

[00:30:18] a blank sheet of paper versus starting something that's relatively high quality is a big difference. And there's many, many other examples like that where we can really automate a lot of the manual work. And it's going to be really impactful to just get there faster, do more faster.

[00:30:32] And that's, again, important for everyone today. 100%. And I cannot thank you enough for giving everyone listening the gift of the importance of the Chief Data Citizen role and sharing your insights around that pure goal.

[00:30:46] But before I let you go, I'm going to ask you to leave one final gift. And that is we have an Amazon wishlist where I ask my guests to leave a book that means something to them or they recommend or a song for Spotify playlist.

[00:30:58] Guilty pleasures are allowed. Guilty pleasures are allowed. I don't mind which you choose, but what is that one final thing you'd like to leave everyone listening? I'll go with the book. It's an older book, but it's the book that really inspired me

[00:31:11] and I use the word inspire to start Colibria 16 years ago. And the book is called Founders at Work from Jessica Livingstone. And Jessica is one of the co-founders of Y Combinator, which I think a lot of people might know.

[00:31:24] It's an incredible book around the stories of now often large companies and how they got started. Some exist still, some don't. There's PayPal, Adobe. I was just really inspired to read those stories, how they got started. Now big companies are very, very little, very small people, teams.

[00:31:42] And I think that was for me a really inspiring catalyst to say, hey, when I was 23 in Belgium and didn't know what to do, why don't start a company myself? If they can't do it, I can't do it. And all my ignorance, I would say.

[00:31:54] And I think it's a book that had a tremendous impact on my life. So it's definitely one that I would recommend. Wow, great choice. I'll get that added straight to our Amazon wishlist. Anybody wanting to dig a little bit deeper on the stuff we talked about today?

[00:32:08] Where's the best place for listeners to find you, your team, and find out more about anything we talked about? Where would you like to point everyone? Absolutely. I'd say our website, colibria.com. C-O-L-I-B-R-A.com is your best gateway in the world of data, data governance and AI.

[00:32:26] Well, again, a big thank you for joining me today, talking about the importance of the chief data citizen role, how it could enable the future of work and the growing importance of data across the global business community, especially with the obsession with AI right now.

[00:32:42] And the big takeaway is you can't have AI without data and you can't have effective AI workforce without data citizens. I think that's a beautiful moment to end on. And I'd be interested in what people think about our conversation today.

[00:32:55] But thank you for bringing this conversation to life. Fantastic. Thank you, Neil. So a big thank you to Felix for sharing his valuable insights on the role of the chief data citizen and its profound impact on shaping data governance and AI utilization within businesses. But for everyone listening,

[00:33:13] what will be your next steps in adapting your data strategies to support your business's growth and compliance in this AI era that we find ourselves? I'd love to hear your thoughts on any actions you plan to take after today's discussion.

[00:33:28] And Bjorn, if you're listening from the very beginning of the podcast and you've made it to the end, it's time for your warm down now. So please email me, techblogrideratoutlook.com, Twitter, LinkedIn, Instagram, just at Neil C.

[00:33:41] Let me know your thoughts on everything that we've talked about today, where you listen to the show, the role of the chief data citizen. And other than that, I'll be back again bright and early tomorrow. So thank you for listening as always.

[00:33:53] And until next time, don't be a stranger.