[Radar Recap] Building an Enterprise Data Strategy that Puts People First

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Hello everyone. Welcome to Data Framed. I'm Adele, Data evangelist and educator at DataCamp and data framed is a weekly podcast in which we explore how individuals and organizations can succeed with data. In this episode, I wanted to share with you our third Radar 2023 session that we're releasing on Data Framed, and this one is with Cindy Howson, Chief Data Strategy Officer at Thoughtspot, and Valerie Logan, CEO of the Data Launch. This was probably my favorite session of the entire conference as it really hits all the themes that we care about at Data Frame, and Cindy and Valerie just bring an incredible energy. Throughout the session we talked about the reason why People is such an important aspect of a data strategy, how to align data strategies with organizational goals and with the skill set of individuals, and how to scale data literacy within the organization. Now for newcomers who didn't listen to yesterday's episode, Just a warning, the format will be slightly different for these episodes as oftentimes we take audience questions as well and moreover the audio quality is that of a zoom call. But we hope this brings an additional perspective from radar to a wider audience. Now let's get started.

Hello, hello everyone and welcome to our panel on building an Enterprise Data Strategy that puts people first. Every year, multiple surveys coming from Wavestone, Harvard Business Review, Gartner, and more ask data leaders about the state of data within their organizations and year after year, a consistent theme still remains. The people and data culture component remain to be the biggest challenge data leaders face when it comes to building a data driven organization. This is why I'm so excited for today's panel. Joining us today is Cindy Howson and Valerie Logan. Starting off with Cindy, Cindy Howson is the Chief Data Strategy Officer at Thoughtspot and host of the Data Chief Podcast. Cindy is an analytics and bi thought leader and expert with a flair for bridging business needs with technology. As Chief Data strategy officer at ThoughtSpot, she advises top clients on data strategy and best practices to become data driven she speaks internationally on top trends such as AI ethics, influences, thought spots, product strategy. Cindy was previously a Gartner research Vice President and was recently named Motivator of the Year by Women's Leader in Data and AI. Cindy, welcome.

Thank you Adele. And I'm glad you stopped with the bio there. Otherwise like pick up the whole session.

Yeah, I do. When we got the original bio, it was actually like this long. That's the list of accolades that you had. It would have taken us 10 minutes. Appreciate you letting it.

I like the word flare. I think Cindy housing is data flare. I hadn't heard that before. So I love that.

That is true. That is true. And then second on here and definitely next is up is Valerie. Valerie is the CEO of the Data Lodge. Valerie is committed to data literacy. She believes that in today's digital society, data literacy is a life skill. With advisory services, boot camps, a resource library and community services. At the Data Lodge, Valerie is certifying the world's first data literacy program leads and pioneering the path forward in cracking the data culture code. Previously, Valerie had joined Gartner in 2015 in the data Analytics Group where she covered information management strategies, advanced analytics and related change management topics. She was a member of the Office of the CDO Research team and she led Gartner's annual CDO survey as well as the CDO Circle executive Training and networking event. She pioneered research in the area of data literacy and nurturing the speaking of data by creating information as a second language. And in 2018 she was awarded Gartner's Top Thought Leadership Award for her leadership in the area of data literacy. Valerie, great to have you on.

There is nowhere else I would rather be.

I really appreciate that. Now I want to make sure as well for the audience that you can ask as many questions as you can. We will have some brief time for Q and A at the end, so do send us as many questions as you want and and moreover, if you want to live post on social media, we want to make sure that we amplify your message. Use the hashtag DCRadar2023 and please join me in welcoming Valerie and Cindy. So I want to kick off today's conversation by really discussing the why first. Right? We mentioned in our introduction many surveys in the industry from Gartner to New Ventures Partners, Wavestone, Harvard Business Review continuously point to data culture and data literacy and the people component as the biggest struggle for data leaders when it comes to creating a data driven organization. So maybe to set the stage on why the people component of creating a data strategy is so important. Why is the people component the most challenging aspect of becoming data driven? Cindy, I'll start with you.

Yeah. And I think this goes back to Adele, that as an industry, it's easier to throw technology out there than to change people skills habits that have been built up over decades by human nature. We are creatures of habit. And so I think when we fail to pay attention to the people element, this is why a lot of teams really don't create a true data driven culture. So we have to pay attention to changing legacy habits, but also motivating them intrinsically, either the why from the business value or the why from the heart. Like, what's in it for me?

And Valerie can give this off to you.

Yeah, I mean, I guess I'd like to unpack the title a little bit of the session where it says Enterprise Data Strategy. And then people like Enterprise Data Strategy to me. First of all, I think there should be no strategy other than a business strategy fueled by data and analytics. Right. So let's get that out of the way. Secondly, the whole idea of the role of people, I mean, what strategy should. I mean, every strategy should pay attention to people. Right. But stating the obvious. But when I think about why now and why is this so fundamental now, I think a few things have changed. Like if you were to think back a few decades to like ERP strategy and implementations, there wasn't a personal corollary. So what I mean by that is with digital and data, this is pervasive to people's lives as well as their work lives. So I think there's an opportunity here and a need here to really look at this more from the complete person view of this is personal and it's work, whereas ERP certainly didn't matter in my personal life. So I think there's that. I think there's also an element of. We really are seeing a convergence of disciplines here where you have to look seamlessly at the business outcomes, the data involved in the analytical method, and what decisions are you driving, what actions are you driving? So I think there's a few things at play here that I know we're going to unpack, but I just wanted to lead off with that. Yeah.

And Adele, this is where you get Valerie and me together and we're like.

Yes, that.

I do think what's really important, something Valerie said, data strategy should be your business strategy. And if there's a recurring mistake that I see is when somebody shows me their data strategy, and it is really only a Technology, or let's say data plumbing strategy, and the best align to the business strategy, and they look at it holistically with, with people as a solid element as part of executing on their strategy.

So I couldn't agree more with the both of you, and I'd love to unpack the what here. We discussed the why we set the motivation. Both of you have mentioned the importance of people when it comes to creating a data strategy, the importance of aligning a data strategy with the business objectives. So maybe how can data leaders and organizational leaders fill the gap? Let's work back from a definition of a great definition of a data strategy here. What do you think are hallmarks of an effective data strategy that is one aligned with the business strategy and that puts people first? I'll start with you, Valerie, here.

Yeah, I mean, Cindy and I, as Gartner analysts, in the past, we, we've advised a lot of organizations on what comprises this kind of strategy. And, and I always, I always kind of frame it into a few key blocks. So the first is vision and value. Like, what are you solving for? What are the strategic imperatives? Where can you derive value, you know, of, you know, revenue, optimization, efficiency, risk. I mean, the classics, right? So you always start with that. Then there's always a piece around platform modernization. So how are you modernizing all of the infrastructure, et cetera, the data quality, the tools and techniques? So there's that piece. There's classically a governance block to the strategy of how are you not only fostering quality data, but how are you supporting responsible usage of that data? That's another aspect of governance. And then there's organization, design. And that includes roles, responsibilities, communities, centers of excellence, the citizen movement. So those are like the four big blocks. But to me, there's a fifth block at the bottom, which is culture, literacy, and change. And that is the foundation of the other four. I'll turn it over to Cindy from there.

Yeah, so you have, you have five, I have six blocks. And maybe I'll share a free ungated resource in the chat with some slides in it. So I actually put culture in the.

Top.

And it intersects across all of these elements. And I used to just have culture more associated with the people because the people do make up the culture, but it also is the habits and the leadership processes would be the other pillar that I would add, as we have so many data leaders and data analysts on this session. If you think about some of the legacy or what should be legacy processes, it was how data and analytics was often approached as an afterthought or even an order taker process. Tell me what you want, document the requirements, throw it over the fence. And that is really not a good process in today's digital economy. It has to be much more collaborative. Design thinking comes in here related to the people. So Valerie mentioned data literacy as an important skill. I would also say a recurring theme so important for the data teams that I would challenge every person to own their own career. They also need a little more business literacy. So I think learning the basic elements of the language of the business, that should be on every data professional's career objectives. The best CDOs and CDAOs, they speak the language of the business and they speak the language of technology. And I see just in the chat, Kyle Kirkland in talent development. And this is where I think we oftentimes don't allow enough time for people to invest in these critical skills that have changed a little bit recently.

Okay, now I gotta riff back, so. Absolutely. And in my improv technique there.

Right.

So culture and literacy. I think when we hear the term data literacy, it often lends itself to, oh, we're talking about the data and the data acumen or maybe the analytics acumen. But Cindy, thank you so much for putting such an emphasis on. There is no data literacy without business literacy. It is three. It is again, the convergence of business literacy, business acumen, data acumen, and analytical acumen. That is what we're talking about. So, yeah. Over to you, Adele.

So I couldn't agree more with these notions. And you mentioned here kind of this framework and different varying degrees, whether it's a six pillar framework or five pillar framework, culture and people is an incredibly important aspect of a framework of advancing organizational data maturity. Right. So maybe let's talk about the execution side here. What are ways data leaders can prioritize data culture advancement and maturity in a way that helps approach and bridge the gap between data literacy and business literacy as well. I'll start off with you, Cindy.

Yeah. And this is where I think having a purposeful strategy around communication, communicating the why and the what's in it for me, and then aligning the incentives, creating that reskilling or upskilling plan. And then the fourth element is really tribes. Who are you going to surround yourself with to execute on this change? And that can be internal, having communities of practice, but also external. So incorporating groups like Data Camp. And I really think about some of the organizations I've had the privilege to work with who do this. Well, so Schneider Electric, for example, they in their Data and analytics innovation program as they were driving self service analytics adoption. They said look, our company goal is to ensure that everyone has access to energy. It should be a life. Right. And also they tie it into sustainability goals. So then they talk about the personal impact, the what's in it for me, the WIFA is freeing up your energy, not doing the drudgery of work or low value work that should be stopped. That's shutting down legacy processes or the other thing I think of is I have to go to my friends in Australia like Endeavor Drinks or at Patty's Foods. They also do things like gamification. They have a change management champion. So I'd like to see more CDOs CDAs have a change management champion part of their team, if not part of their team. They are working with people ops to actually collaboratively have a change management team program.

Yeah. So picking up on there. First of all, I love the pun of Schneider Electric freeing up energy. That was really clever. I don't know if that was intentional or not, but that was good. So. So on the, on the. How do you approach this programmatically? So first of all, this is not going to emerge and evolve on its own. If it was going to, it would have already. So you have to approach this as a really a committed program. I do that through data literacy and culture programs. The very first part of that has to be the case for change. I don't mean let's get everybody on the same page with basic stuff, basic definition of data literacy. I'm talking about how do you, I call it excavating the case for change. What does behavior look like today and what is the target behavior we're looking for and where does that exist today that we can model? So when talking about data literacy we use the term skills a lot. I just want to reset that a little bit. That a person who is fostering and really representing a strong data literacy orientation, it is about mindset, it is about their language and it is about skills. So the mindset is. If you hear people saying I'm not a data person, that is a gift to you. That is a gift because they are giving you an insight that they don't even want to participate. So you're not going to get them to take courses, you're not going to have them participate in assessments, you're not going to have them join a lunch and learn because they don't even think it's relevant. So you have to start with mindset. Then language. If we talk about collaboration and Communication. We say that very, very flippantly, honestly, in this field, but communication is based on do we understand the terms? Cindy and I just came out of the Gartner Data and Analytics Summit, where people was the predominant theme in the keynote. But if you did a word cloud, over 4,000 people at that summit, there are naturally three sets of terms. Business acumen, data acumen, analytical acumen. So my point about that is there is a specific language that many of us speak as data analytics professionals. So it's important to codify that language and teach it, and then you come through with the skills like critical thinking and storytelling and understanding ethics. So I just wanted to unpack that. That that's really the formula of what we're really solving for and doing. These contrasts of what does it look like today? And then what is the target? What is it that we want people to do more of?

Yeah, so if I can just. Can I add something, Adele, or.

Yeah, yeah, please do.

You have to, like, stop us.

But.

So Valerie's point about mindset and when somebody says they're not a data person, I would say, after being in this space for 25, 30 years now, if we have made one huge, huge, huge mistake, is that we have made business people afraid of data because we have said, oh, in order to approach the data, you have to go to these long classes, learn these hard tools. And sometimes we've used data to punish and to tell our own version of the truth. So there's a fear out there of what does this really mean for their jobs? And so I often say, I don't want you to be a data expert, but data is now part of everyone's job, everyone's life. And, and that's why you need to have the mindset that data is part of your job. And learning it, but in the business context is super critical.

And so I just saw that Kate, our beloved Kate, put in the chat that everyone is, every person is a data person. I just really. If you take nothing away from this incredible session, every person is a data person. And the way you approach that is if someone says to you, I'm not a data person, I love to say, oh, you don't drive a car and you run out of fuel on a regular basis or you run out of electric on a regular basis. When you look at your dashboard and you see you're running low on either electric or fuel and you pull into a station that is making a data informed decision. So we are all data people. Let's just help the masses appreciate that Remove the intimidation, remove the abstraction. This is relevant personally and at work.

So I couldn't agree more, especially on the importance of removing the intimidation and on creating the what's in it for me for all of the organization. Want to zero in a bit on that? We talked about how to make data more accessible for the business user within the organization, but maybe let's shift gears and talk about how to make it more accessible for the leader within the organization. When both of you, whether you're working Valerie, with the Data Lodge, trying to create upskilling programs for data literacy within your own clients, or Cindy, when and advising different leaders on how to leverage ThoughtSpot, I'd love to understand how do you approach leadership resistance from people who don't want to necessarily adopt data within the organization? What are tactics that you can share here? I'll start with you, Valerie.

Yeah, this is incredibly relevant right now. So at the Data Lodge, we've got 60 people in our community who are either data literacy program leads or participating in data literacy programs around the world. And I ask them all the time, what are your biggest challenges with executing your program? And I can tell you one of the top three is how do we engage the senior leaders in this journey. So if you think about it, leaders can either be a reinforcing loop for the program or they can model the wrong behavior model, maybe not model strong data literacy and it can be a reverse effect. So I would suggest that really engaging the leaders very intentionally, they're very busy people, they have a lot going on, they have a wide scope. So carve out no more than an hour and do I hate to say it, but it's more like an intervention, right, where you're bringing them up to speed on how can they be the best champions for fostering data literacy. What we're doing with it, with a program and a treatment around that is a little two by two model that says there are four executive data Personas and they are about how to how to be an active, aligned champion. So that looks like are you identifying a data literacy ambassador in your organization? Are you providing resources? Are you recording a video testimonial on why this is important and how it matters? That's the advocacy part. The abilities part I think is more important, which is how do you show up as a leader? What are you modeling? And so one of the I'll just give one little tip. Modeling. There's a lot of fear and vulnerability around data. We've already kind of touched on that already. One of the best gifts a leader can do. Go into your. Go into a meeting and say, you know what? We use that term a lot. I'm not sure I really know what we mean by it. You may know, but ask the question or you know what? We. We use this visualization. And I think I know how to do it, but I'm not really sure. What that does is it creates the space for other people to admit what they don't know. Right now people are afraid. People are afraid. Like, oh my God, if I admit I don't know this, I might get cut. Right. So model vulnerability in addition to the other aspects of literacy. Cindy, thoughts?

Yeah. So I think to build on that a little bit. Adele, you asked the question. The leaders and I actually think the very senior leaders know data is super important, but maybe it's the middle or lower down. And then sometimes, as one CIO said to me, how do I stop this management by magazine? Because the very senior leaders might read something and say, oh, I want that too. And I'm thinking of one CEO who said, I'm going to have a data literacy program and I want everyone to learn Python. And I'm like, no, no, no, that's not what you want. But I do think it comes back to start with the why, that's what the senior leaders care about. The how is where we make people afraid. So for the senior leaders, it's the why. Why am I doing this? Show me how data will either help me make money or save money. That's what they care about. And the make money, it might be retaining those customers, improving NPS scores, saving money. It might be minimizing customer churn or minimizing stock outs. The how, as you move further down, might. Might include some of the technologies. And so I think that's where we don't want to overwhelm people with the how. We have to very quickly get to the why and show them something better than how they've been working before. Better and faster. Get to those aha moments. Faster is super important. So I think about some of our customers, Western Union, they run their management meetings with data, with live data. And there is that culture to be able to look at data in real time. I think about we had the privilege this past week at the Gartner conference of Paul Pregnale from cigna, talking about how they use data and it's again to improve these outcomes. Better claims management processing, which is ultimately better healthcare.

So one other addition while we're on the topic of leaders. So right now we've been talking a Lot about the chief data and analytics officer as, like, maybe the owner of this topic or the home base for this topic. But I do want to mention that there are a set of leaders that really need to be teaming to foster this kind of impact, and one of which is within learning and development. Right? So one of the first things I say when someone says, hey, I want to go after fostering data literacy, I'm like, to scale this and to have the broadest, most significant impact, you need to partner with. If there's someone in a digital organization who's driving a lot of the digital change, and you're learning and development in HR and people partner, it really is that trinity of leaders who come together to foster this in a scalable way. So Mayo Clinic, for example, phenomenal work around their center for Digital Health, their data and analytics team, and their learning and development and leadership development teams. They came together to say, how are we going to do this? And infuse and weave it into all of it. It's not like this is a separate thing that we're trying to inject. It's more, how do we weave it? And I love that Stephanie Lenzner at Mayo refers to it as weaving.

So that's really great. And I think this ties into my next question here, because both of you have mentioned on the importance of one, having that partnership between the learning team and the data team here, also creating that data literacy program that puts community and people at the center want to kind of push it onto you here and say, what does a great data literacy program look like? So I'll start off with you, Valerie.

Yeah. So a great data literacy program looks like one that people love, that people are engaged with. So first and foremost, it's clear and compelling and it's personal. It is something that people are naturally making time for. Nobody has time. Everybody's burnout. If you find that people are participating and then advocating for others to engage, that is the true test. Right? So I was asking my community other day, what's the primary measure for your program? Net Promoter score, right? When people are engaging with the folks in the program, are they telling their friends, you got to make time for this? Right. So that's kind of the top level, but a program. A lot of people think a data literacy program is primarily the academy, the skills. And I mean, we're at the radar event. Of course, that's central, Right. The skills development, however, it's not just training and learning paths. I like to refer to it as there's three blocks. There's Engagement, development and enablement. So development's the center. That's all of the professional development activities. The engagement is what we've been talking around. Leadership, engagement, communications, craft, giving this a brand that's fun and gamified. How do you leverage communities? So if you have communities of business, analysts, citizen data scientists, they are your natural local champions. Right. So if they're getting engaged, they're already doing this right on their own. So how about arming them with a consistent way? That's the engagement, the enablement piece. This is where a lot of innovation is going to happen. Enablement is not just office hours and lunch and learns and oh, I have. It's certainly things like data catalogs and dictionaries and glossaries. You have to have that to support scalable data literacy. But enablement strategy in a data literacy program is how are you maximizing your technology capabilities to foster guided data literacy in the moment? So Thoughtspot does a phenomenal job of this. It's things like hovering over the data element to display the definition. It's chatgpt, right? It is. How are we getting scale through automation and technology? So my message to you is a data literacy program. First of all, are people engaged and loving it? That's the real test and telling others. But it's engagement, development and enablement. I call it conducting the data literacy orchestra. It's a lot of moving parts.

Yeah. And what a great band. I want to be in Valerie's orchestra and there's always room. I know another thing that organizations the best that do this well. So Chick Fil A, for example, that it's also role based. So you're paying attention to what is the level of. I use the term data fluency a little bit so that it's thinking about data as well and that there are different levels of proficiency. What you expect from an executive maybe interpreting the data and aligning to those consistent business definitions will be one set of proficiencies. Whereas of course the data engineer and the analytics engineer, you might also expect them to be proficient in the actual sources of the data doing these different levels of fluency or proficiency that it's also role based. And I know that Valerie advocates that as part of the data lodge as well.

I do. And I just want to give a tip to everyone on that. So there's this big question of the term data literacy is like some people find it offensive, like, oh, are you saying I'm illiterate? And I get that. I lean into that. I appreciate it. I think a lot of times as Data and analytics people. We go there because, you know, duh, we know data and analytics, right? But we have to think of the masses, we have to think of everyone else. Does the front end store clerk, if you approach them and say, hey, we're going to make you data fluent, they'll probably be equally scared. Right? So the quick way to think of this is I view data literacy as the lowest common denominator across the Personas. Fluency is the next level up. Maybe people that minor in data and analytics, maybe a citizen data scientist. And then mastery are those that major, right? Your data scientists, your data engineers. But the one liner is data literacy is the lowest common denominator.

I don't know, Adele, how do you do these things? I'm reading all the chat things. Am I allowed to give a shout out? I like this. Angelica is talking about data accessibility and who feels empowered. And we did a survey a couple years ago with Harvard Business Review that found that the reason why the frontline people don't feel empowered is that they might see the data, but then they don't have permission to act on it. So this degree of empowerment gets back to the overall theme of how do we unite the people in this process too.

So on that point, Cindy, there's this myth that the people in the ivory towers and the smart data scientists and data engineers are the ones that come up with all the innovation. I think that's crap. I think as soon as you open up. Can I say crap?

Wow, you're getting Valerie down, down in the trenches here.

That's right. My point is, as soon as you open up the communication channels with the masses, the frontline employees, for example, and you open up this, this. How do we talk about the business acumen, the data acumen, the analytical acumen, Open that up, then all of a sudden, I'll tell you what, that front end cashier who's helping to process groceries and put them in a bag, that person knows what happens when it rains, right? So infusing weather data, that person's gonna know infusing weather data is gonna matter. So as soon as you open up those communication channels, you unlock what I call radical collaboration.

So I couldn't agree more. And this is an awesome set of insights that you're sharing here. So what I wanna do here is I'm gonna stop asking questions. I'm gonna take questions just from the audience, because we have a very engaged audience right now. First question I'm going to show here is from Kate Strachni. And this is especially on how to evaluate a data strategy. So I'm going to show it here on stage. How can an enterprise data strategy be continuously evaluated and improved to ensure that it remains aligned with the needs of end users? Cindy, I'll start off with you here.

Yeah. So, as we said and. Hi, Kate, how are you? Good to see you. Virtually, I do think this goes back to remember, it shouldn't just be the technology, it should be aligning to the business strategy. And the levels of maturity will progress at different paces by particular business units and by the different functions. So if you assess the people, the processes, the alignment to outcomes, and the technology and culture, that can all be at different levels. And so I think you, you want to at least take a baseline before you start any new program and then do a pulse. How are your stakeholders feeling? Those are the leading indicators. And then once a year, look at. Have you actually moved the needle across all those different six pillars?

Yeah. The only thing I would add there is I'm working with a large financial services organization where they're kind of coming out of their first. Well, let me step back in the new vantage survey. One of the things that's described is the average tenure of a CDO or CDAO is around two and a half years, 2.4 or something. And I think there's an interesting phenomenon as it relates to enterprise data strategy there, which is in the first couple of years, there's a lot of establishing the foundation kind of breaking glass and kind of establishing new functions and creating the new role. So I think what is evaluated and improved in that first couple of years has a different set of characteristics than when you pivot. And I think around two and two and a half years is typically where this pivot happens, where you should really be seeing a whole bunch of business value being coming out and people talking about it and realizing the value. I'm not saying there's no business value in that first two years that certainly there is. But I think there should be a really strong cadence of business value spinning off. That's even a little more than what you see in the first foundational years.

Oh, yeah, if I can also make that point. You have to be, especially if you are a new data leader, whatever your title is, some of the foundational elements that may take multiple years to get all your data in the cloud, clean master data, but you have to be having quick wins of visible business value. I say no less than once a quarter, otherwise you're at risk of losing your job or burning out. And I think that Two and a half years is now lower because of the impatience on both sides, the stakeholders as well as the data leaders who know what is possible and yet are getting blocked.

And if your business stakeholders cannot tell the story of the value, there's something wrong if the data office is the one that's having to do all the communications and push that out. You don't have a we, you need a we. You know, we are driving the data transformation and they need to be equally excited in driving the messaging of it.

I couldn't agree more. So we still have one. Time for one more question. This is a question from Suresh. I'm going to send put it here on stage. So completely understand the importance of putting data first, aligning the strategy of the organization based on data and business value. But in maturing organizations, this is very much possible because the data infrastructure is still there. How about a new organization that is just starting? How do you approach the data strategy that puts people first? Valerie, I'll start off with you here.

For me, it's an interesting dynamic when I run into someone who's maybe more on the early side of this or a new organization because I think you actually have the benefit of weaving the culture and the communication and the language and the mindset from the start and then using that and leveraging that to drive the transformation or drive the value, drive the outcome. So I think you actually have the benefit of setting the tone and setting the language and setting the culture from the beginning. So what that looks like is really engaging people in. We do something called a via model, which is a little mnemonic for how you, how you speak about use cases using business data and analytical acumen. So I think you have the benefit of infusing those capabilities and wiring the culture that way in the beginning and then you don't have to catch up with it later. So I hope I caught the question right.

So nice to see so many people from around the world and great to see you from Germany, Suresh. So this is where again, it's no matter where you are in your journey big, it is about start small and scale fast. Don't try to boil the ocean. I do think the technology piece has never been easier. With the modern data stack you can do rapid free trials, rapid proofs of concepts across that whole life cycle and so showing those quick wins. I think you can do that even if it's in one pocket, one department and then the rest of the organization will follow. If you have those good business stakeholder testimonials, do I get a final word too?

Adele, you can get a final word? Yes, definitely.

Okay, really quick. There are over 30,000 people enrolled in this event, registered in this event. This is not. These topics are not about some big top down change. This is not like corporate's coming here. And we're here to help and we're here to change you. This is as much of a grass movement as we've ever seen. So every single one of you who is either here live or watching a replay, you have an opportunity to be an ambassador for this work in this change. Start with the people around you, right? Look for mindset, language and skills. That is what you're on. There are people. Do people have limiting beliefs? Are they aware of the terms they're using? And then do they have the skills like storytelling and critical thinking? So just start putting on those data glasses. Look for it. You are the change agent.

That is a perfect way to end this session. Everyone make sure to send some love with the reactions and emojis to Cindy and Valerie. An excellent session as always. It's incredible to have you on here and it's an honor to share your insights with the rest of the radar and data community. Now, everyone, before we wrap up, we're going to head for a 20 minute break. We also have an AMA session with Datacamp founders in case you want to check that out. Ask them your most pressing questions. What do you want to see on Data Camp moving forward? And with that in mind, thank you so much, Cindy and Valerie, for sharing your insights and appreciate the audience joining us.

Thank you, Adele. Thank you everyone in Data Camp. Great seeing so many of you online. Thanks, Valerie. We saw each other live this week.

I know I'm going to be in withdrawals next week from Cindy Howsen, but yeah, anybody wants to connect on LinkedIn, happy to help with data literacy programs. Peace out.

Thanks so much.