Data Literacy Programs with Mariska Veenhof-Bulten at bol.com

Dave Mariani: Hi, everyone. Welcome to the AtScale Data-Driven Podcast. And we have a special guest today. It’s Mariska Veenhof-Bulten, who is the team lead of business intelligence at bol.com. I’ve known Mariska for a little while now. bol.com is an AtScale customer, a great customer of ours. And, I met Mariska in talking about data literacy, which is going to be the main topic of our chat today. Because there’s a lot going on in data literacy and it turns out that Mariska is a real pioneer there. So thanks Mariska. Thanks for joining us today.

Mariska Veenhof-Bulten: Thanks Dave. Thanks so much for having me here.

Dave Mariani: So Mariska, why don’t you for the audience to tell us a little bit about bol.com. you guys are very big and, on the, on the other side, on in Europe. and, so tell us about bol.com and what you guys do there, and how you guys leverage data and analytics.

Mariska Veenhof-Bulten: Yeah, so, bol.com is one of the largest online retailing platforms in the Benelux. So we’re, we started out in the Netherlands, but we now also serve Belgium. So in the Netherlands and Belgium, we’re one of the largest online retailing platforms. And within that a lovely company that now exists, over 20 years. I’m I, I lead the BI team or part of the BI team and mainly focused on really using the data. So my part of the team is really looking at, are you able to use data to make better decisions? So, yeah, I joined bol.com four years ago and I’ve a consultancy background, also in the BI area. So, it’s really the data analytics and BI areas really where, yeah, where I started my career and I still love working in.

Dave Mariani: Yeah, I know. It’s like at don’t bol.com. You are truly big data. I know you’re running on big query and on Google, big query as a platform. what are some, what’s, what’s some of the tools that most people use to, to explore the data and make it make those data-driven decisions, at bol.com?

Mariska Veenhof-Bulten: Yeah, so, our main tool stack that we use is at Tableau for, dashboarding and also, self-service and that analysis. So really, where people use, data sources to build their own reports and, AtScale is really being used for modeling that data. So making sure that the data is available in Tableau as a data source fast and also in a nice modeled way, that is, also very easy to use for users that maybe not so SQL savvy and a lot of our users also work directly in bakery area, as you mentioned. So I’m really writing their own queries and working with data from there.

Dave Mariani: Great, great. So, so let’s just get into the topic of data literacy. So a lot of people are talking about it and, you know, we tend to talk a lot about the tools and, and the, that the tools and the technology, but you know, and, and of course there’s tools and technology that can help with data literacy, but a lot of it is about people, and about the people skills. So, can you just tell us a little bit about, you know, how you define, data literacy, at gold.com and what’s it mean what’s it mean to you Mariska

Mariska Veenhof-Bulten: Yeah, so, within bol.com, we work with a few data coaches. I started at bol.com home also as a data coach, and we really look at the data maturity of teams. So there are many factors that determine how mature you are in working with data, for example, the culture in your team and how easy it is for you to work with data and actually use it for decision-making. One of the key factors is also the skills that you have in your team. And that’s where the concept of data literacy comes in. So literacy. And, to be honest, I really got inspired by Ben Jones and his definition of data literacy. So I did not come up with this myself.

Mariska Veenhof-Bulten: Yeah. And, data literacy is the ability to read, write, and speak data. And, and what I really like about that concept is that it, well, at least it speaks to me literally, because it is about how you are able to interpret data. So read data, but also, it’s really like learning a language, but then the language of things. So that is what, the definition that I use with my team for data literacy and, and so far, it’s still really works well. And we use it, also as a team, like, do you have the right mix of skills but also for individuals, are you how comfortable And we use three levels. So to say, how comfortable are you reading data, interpreting graphs, for example, how comfortable are you asking critical questions When you look at certain numbers and speaking data, ask really asking for proof for certain statements and writing data is where the tech skills really come in is

Dave Mariani: Yeah. What’s it mean to write data Like, what are some examples of writing data I get reading data. So interpreting the output. So what about reading What about writing and speaking What are some of the examples of that risk of,

Mariska Veenhof-Bulten: Yeah. So you could think of a, well, maybe an example. We have a lot of sellers on our platform and, you could be looking at like, Hey, there’s something happening, with costs, on our platform. So you look at a certain Groff and you see costs rising, and that is reading data. That’s all about reading data. Then of course, you’re gonna want to dive into that, like, what is happening here So you start maybe with a minute, and now this is based on data sources that you already have, for example, modeled by our BI team and at scale, or if you don’t find it there, you might want to write your own query and start looking for possible causes. and then asking follow-up questions. So that’s writing data actually find a cause for example, one of our sellers, is, creating a lot of customer cases, which cost obviously raise our costs.

Mariska Veenhof-Bulten: And then, you want to ask some critical questions like, okay, is this the, just this one center, or how does this work What is the average, what is a normal amount of cases That’s what he’s speaking to. So really asking critical questions and having a discussion on this. And of course I’m writing data and creating a dashboard on this and really sharing the insights. That’s where writing data, again, makes a step to speaking data so that you, for example, can discuss, Hey, let’s have a discussion with this particular center and try to reduce the number of cases and see what those are coming from. So really in working with data, all these three skills really come together.

Dave Mariani: So some risk guys like does, is, is the getting to speaking data, is that the sort of the most mature skill or is it a, is it a continuum or, how do you within bol.com, how do you like expect people to sort of move through the read, write and speak sort of continuum

Mariska Veenhof-Bulten: Yeah. well that was one of the first questions indeed, that came up for us as well. When we started with this, like, does everybody need to be that SQL guru and the, the most perfect, interpreter or speaker of, of, of data. and we found out that, well, at least on a team level, you need to have a good mix. So you need to have somebody what we call a level three. So let’s say an expert in reading data. So that person really understands about, for example, Everage is, and, and how you should interpret those or mix effects, maybe when the large number of products that we have on our platform. but not everybody needs to have that skill, but you do need an SQL guru in your team to be able to find the data that you’re looking for.

Mariska Veenhof-Bulten: but you, you don’t all meet to become this SQL Coro or a data scientist for that matter. So it’s really about in a team, it’s the right mix, for an individual. It depends what your role is. and that’s some conversations that we’re actually currently having, like, okay. So for a data analyst, you might want the highest levels on working with data before a manager. You may want to think about, that you speaking data should be something that you’re really good at and maybe reading data as well, writing data, maybe not so much. So we’re really having some interesting conversations, like, okay, so for which role, which levels, shoot, should apply on reading, writing and speaking data, but they all come together. Let’s say, there’s not a, you do a reading first and then a writing second or something. Yeah.

Dave Mariani: Yeah. I love that. So you’re really talking about a mix. So like anything, if you have a team, you know, you can’t all be point guards. If you’re playing basketball, you need to have, you know, a center and a forward. So it sounds like, that you need to make sure that people, you have the right mix of skill sets on the team. and that if you have a model for, for, you know, tracking that mix, you can be sure that you don’t have those gaps because a, you want to be an effective team. So I like that, that’s, that’s a really great way of thinking about things, especially from an organizational perspective and what the skills you want in your organization. So, look, it’s like, I love this. if I was in, if I was running data again for, for an enterprise, I would love to, love to build a program around this. So, you know, what is it, you know, for, for the audience out there, you know, how did they even get started So how do you start and helping people become more Versant and data, how, how would you actually think, and maybe you wanted to say, talk a little bit about how you got started Mariska at bol.com. Cause I know you really pioneered this concept there.

Mariska Veenhof-Bulten: Yeah. So, we found out a couple of years ago already that, one of my former managers used to say, solutions are not the problem. So, we worked with the central, business intelligence team and, we found that we created loads and loads of reports, but they weren’t necessarily all getting used. So it really felt like, yeah, we have tons of solutions and all these great insights, but are they really being used to take better decisions That’s why we started with the experiment of data coaching, where we, based on the data maturity model that I briefly briefly touched upon at the beginning of our conversation, started working with teams. And I guess that is also a bit, my recommendation get close to the teams and, and to the real business teams, because then you can talk about what data could mean for them and how it could help them in their job.

Mariska Veenhof-Bulten: So, really practical examples and being close to the team and showing them like, Hey, but if you were to use your, this data to do your job, you will get much more effective and you will get much better at your job. And then that’s where data comes to life. If, because it remains cause of like, yeah, we should work data-driven. Yes. Sounds awesome. But yeah. How do you even get started So, we went as data coaches really worked with teams for multiple weeks in a row and started learning about their business and, really started asking questions during their meeting. So joining their meetings, also asking questions like, okay, so what does this mean for you Oh, you’re talking about this KPI. Is it clear for everybody what that actually means well that, you could probably guess what the answer is.

Mariska Veenhof-Bulten: Not everybody was so clear on the KPI as they, filthy. Yeah. They had to be. so really working with those teams is, and getting close to combining business and data. That’s really where we got started. And we learned a lot from working with those teams. And based on that, we came up with, what are the factors that are, make, make the difference between a team that is working really well with data. So it was really mature data and not as much. And one of that was the mix of skills. So, and that’s when we started searching for like, is there a concept or something that can help us with this because we saw, for example, teams where you had this brilliant editor, just, but he was like, nobody understands what I’m saying. Probably for many of the listeners, this may sound, I’m trying to send a message here.

Mariska Veenhof-Bulten: And, but, and that’s where we are really, we liked when we found that we were Googling, for, for, you know, the, the skills. And we found the concept of data literacy, with, with Ben Jones and on his blog and videos that he made. And then it totally made sense for us. So I guess coming back to your question, how can you get started in helping people to hear something data it’s really about getting close to them and finding out where the biggest pain point is for them, and then, having a discussion with them on what data literacy could bring. So one of my team members, for example, does workshops with teams explaining data literacy, and you really see some people going like, yeah, finally, because I need people in my team to be able to read what I’m presenting.

Dave Mariani: So you’re doing some workshops. So you actually do, you actually have some, you actually have some programs, which gets us to really my next question, which is, okay, what is a, what is a data literacy program So it sounds like for a SCA that you have a team so that your team is going out, and you’re obviously marketing these skills that, you know, you know, investing in data literacy is going to, you know, is going to improve the business and improve your effectiveness as an employee of bol.com. but you know, what’s that program look like to you and, and talk to me a little bit about the investment that you have to make in running that program for the company.

Mariska Veenhof-Bulten: Yeah. So, the program that we, currently have set up is that we start working with a team and explain about data literacy. So that’s the first session, really And then we talk to their management team about the different roles that they have. Because one thing that I learned is, I’m a, I’m a data specialist, I know business specialists. So in the beginning we were very ambitious and we said, you know what We should, you know, write the curriculum for each and every business analyst. And we’re going to determine for them which level they should have. I got some angry calls there.

Mariska Veenhof-Bulten: we took a step back and realized we’re not the business specialist. So what we actually do is we bring this concept and we say, okay, so within your domain of the business, what do you feel, a business analyst or a data analyst for that matter, which skills, all the data literacy and levels. So reading level 1, 2, 3, writing level 1, 2, 3, or speaking level 1, 2, 3, they should have. And the management team has an elaborate discussion on that and it come to a set. and then we work with the teams that they manage and say, okay, so this is the idea from your management team on the levels that are required, where do you think you are currently And we actually have a really nice training program, which we summarized in a Tableau dashboard. there, you can really see, okay. So reading level one, what does that even mean

Mariska Veenhof-Bulten: so people can pull up themselves like, oh, maybe I’m reading, I’m not doing quite so bad. I’m doing, I’m actually a level two already. and what we saw is we have people plotting themselves and then saying, okay, where do you want to be some even exceeded one or to exceed the expectations from their management team So it says, what reading level one, nah, I’m going to go to a level three and put that in their development programs. So in that way and their development goals. So in that way, you let you, you know, really, with the business that they are in really weigh in and make their own decisions, like where do you want to be And where do you think you are now

Dave Mariani: Yeah, that’s, I mean, that’s really important because what you’ve done at bol.com is it you’ve made data literacy, you baked it into, each, each, team members, development goals. and, that’s, that’s, that’s huge because, you know, they can take that skill. and if they go someplace outside of boulder.com, they carry that skill with them. So it’s, it’s such a great asset as a person to be able to have your company invest in you that way. so, I love how you said too about it’s like, you know, I don’t know the business, it’s like, I it’s, but I know I know data, and, and the technology behind it. And I think that’s a really big thing I learned over the years, is that, you know, the old model was that, you know, it would have to know both sides, they’d have to know the technology and then they have to know the business.

Dave Mariani: And they’re responsible for creating the, you know, the dashboards and the analytics for the business, which made no sense to me. You know, I ran into all kinds of troubles trying to with that model. And that’s really kind of where I got down to where the idea for AtScale came from was like, look, let’s create a self-service infrastructure so that people can, you know, set subject matter experts can use, you know, can get access to data the way that they need to get access to data and they can understand it. And it’s, it’s, it makes sense to them. They don’t have to have the high technical skills that it has, and then they can use their business expertise to actually ask, ask questions, and, and make decisions on that data. And, and so it was really key to create a self-service infrastructure. And I like to call it, you know, a semantic layer so that people can really, make their own, do their own analysis. And so what you’re adding and what a data literacy program adds to that is that, it’s not just the technology available to do that, but it’s also the skill sets to be able to, really, leverage that data to make decisions. So I really love how you add the people part to the technology. I’ve always, I’m a technology guy. I may need to be a better people guy. And so I think that’s a, that’s a really good combination, really, really good.

Mariska Veenhof-Bulten: What would you, what you said, because I strongly also believe that, you know, bringing the business to the data team doesn’t make sense at all. And we realize we really got stuck, you know, with all the waiting list. And we had to balance between either making a report for logistics or our commercial operations, which is an impossible choice. we’re really taking steps, for a couple of years, to really bring indeed the data to the business teams and with that reducing their time to insights. And that’s really our vision towards the future for, for my team is that, you know, a few years ago, people in the business teams had to wait so long sometimes to, to get the insights that they needed. So they had this idea what to check it with the data, but it takes ages. And now if you have the right skills and you have the technology, to get access to that data, you can really take a step and saying, Hey, I have this hunch based on my experience, let’s check it with the data and then have to take a decision fast. And that’s really, you know, where, where I think our business is also moving towards. So yeah, I strongly believe in that.

Dave Mariani: I like what you said. He said, and this is what we used to do. Right. We used to bring the business to the, to the data or the business to it. And that’s just like, that’s just a model, like you said, it creates queues. It creates, and you know, I, cause I, I just know spending hours in meetings with the subject matter experts for them trying to translate to me, you know, exactly what the w w what is we know, what does gross margin mean It’s like, you know, it’s like, I don’t really don’t care what gross margin means, but obviously they care a lot about that. so it really lets the teams do what they do best, when you bring the data to the business versus the business to the data. So I really liked how you said that. so, Mariska did, so it sounds like maybe bold.com began that way. Is that kind of, was that where you began Was that your role in the, in the, you know, before all this happened was, was when you were a service center for the, for the,

Mariska Veenhof-Bulten: Yeah. True. So, I think as a lot of companies, we started with a few BI experts scattered across the company, and then we decided, to put them in one team that worked really well for a while. And I think it was two years ago, two and a half, maybe that we, yeah, we really no dislike, well, this isn’t working. And somehow we got too big. and indeed the requests were piling up and, we hired one guy totally, expert in, for example, logistics, reports. But if he was on a holiday, well, basically the whole logistics department, I need a report and we were all like, no, but that guy he’s expert in your stuff, you know, that we’re really wasn’t working. And, and that’s indeed what started it for us, like really How can we reduce that time to insight and how can we bring the data skills to the business without, you know, asking them to become BI specialist

Dave Mariani: Yes. Our data in, or data engineers, right Yeah. Yeah. That’s unreal. It’s an unrealistic, it’s like this, you can’t, you know, that’s, yeah. It’s like you think about it. Right. It’s and I hear other customers of ours talking about basically everyone is an analysts, so we have another retailer stateside, that’s a digital retailer. And their concept is like, you know, we want to abolish the title of analyst because we believe everybody should be an analyst. and if you create that role and he’d say these are our analysts, then you’re basically asking them to do the job of analyzing all data for all, for the whole business, versus having the business, people do their own analysis with tools and with skillsets that allow them to self-serve and to do that themselves. So, I think that’s, it seems obvious, but, a lot of people are still stuck in that old, that old way of doing things. I think people are starting to come to the realization, especially with the cloud, and with, you know, things like, semantic layers and data literacy that really everyone should be an analyst. not just an analyst.

Mariska Veenhof-Bulten: Yeah. And that is somehow, it sounds a bit scary like it, right. I mean, if you’re now a manager and maybe you went to the uni, where there were not too many data skills taught, and now you’re this big manager somewhere, and now they’re telling you like, oh, you got your analysis as well. Like yeah. But no clue. So it, I guess with, with, data literacy also by making it an online program, what we did, so learnings also, you can step over that hurdle a little bit. so, without, you know, having to admit, like, I don’t really know the difference between, you know, certain elements or how, why, and Everage why that is so important. so you can, you know, a bit, teach the skills that you feel are comfortable enough for you to learn. but on the other end, indeed set the bar a bit higher for yourself on, when it comes to analytic skills, at least.

Dave Mariani: Yeah. Yeah. And so, and so, yeah, you, you did cover a lot about this as a spot. You know, you, you definitely built a program, you staffed it, and it’s, and you measure it. so, you know, so Mariska, how do you, how do you chart your progress, and, and know that you’re, you’re making an impact within bol.com What are the, some of the things that you’ve done, to, to really sort of prove that out, that you’re, you’re on the right track.

Mariska Veenhof-Bulten: Yeah, so, that’s a difficult one because ROI is, in working data driven, and I hope maybe some of our listeners have that, but I it’s a difficult one. what I do see is I do have some really practical examples, you know, from a team that was able to realize more margin based on an insight that they had, a team that was able to positively impact the customer experience at our online customer service. So there are some nice examples, and you can even put some numbers on it, but, still, if you would try to add that up, it feels like, but that’s, that’s not even, does not even come close to how big I think the impact could be. But what we do is, we track how many training are being followed so that, you know, those people that say, Hey, I want to move from, speaking level two to speak in level three, they can track their progress. So they can really in a Tableau dashboard, click all the trainings that they need to do and see what they’re done. So that’s one thing that’s okay.

Dave Mariani: First on that. Do you have like a test or something like that, that, that the people that can take that, that training course and they can test and to sort of achieve that new status Is, is that sort of how it works

Mariska Veenhof-Bulten: We don’t have that yet. Well, maybe for some of the technical skills. So for the writing skills, we have, an exam in a, either Tableau or a big query that you have to take before getting access to certain data. but not yet. And we’re actually thinking a bit about this, like, yeah, wouldn’t that, yeah.

Dave Mariani: It’s almost like a certification, you know, it’s like, you can an internal certification that says, okay, you know, you, you know, you take this course and then, you know, you test, you test out of that course and you’re ready for the next one. And you could then chart people’s progress along that spectrum. Right. As they sort of get more skilled.

Mariska Veenhof-Bulten: Yeah, it would be really nice because it also, well, you could think about also, you know, gaming it a little bit that way, like earning points or whatever, or earning some cool title or whatever.

Dave Mariani: Yeah, yeah, for sure. Yeah. And it’s, I know I’ve seen, I’ve seen your dashboard, so, and I have seen how you chart, you do chart success really well in terms of, everything is in a, in a, a set of Tableau workbooks where you’re actually tracking this and using data and analytics yourself to measure your success of your own program. so you’re definitely data-driven when it comes to that. So look, so, you know, you’re sort of a, you know, a pioneer in the, in this whole, in this whole area of data literacy, and you’ve talked about some of the other people that were sort of our pioneers as well. so, you know, Mariska, you know, where do you see this going you know, what, w you know, what’s next and, and, and where are you thinking about the future when it comes to data literacy and, and within bowl and, and also just, and what we can do with all this.

Mariska Veenhof-Bulten: Yeah. So then there’s, let’s say within our own company next on my agenda is to roll out this program even further. And despite the, let’s say, some challenges that we had in the beginning of trying to connect data literacy skills to job titles, or to job profiles, we are actually having a bit more modest conversation about this now, and trying to talk to, our, HR consultants, like, Hey, but shouldn’t, we request this type of skill a bit more, well maybe if you want to grow as a, as a business analyst, should you maybe also show that with the courses in data literacy in our data literacy program, the modest more ma we’ve taken a bit more modest role there, but, some conversations on that. So that’s a bit of my dream that our company, you would really know, like what data skills are required for my role, that everybody would know that I, outside of my company, what I would, I keep thinking about, what, what com keeps coming back to my mind is what if we could bring these skills also to, well, maybe high schools. So, because, for example, myself, I did get some courses, you know, on business intelligence. So obviously you’re talking about data then, but, there,

Dave Mariani: Did you get, you got courses in your school about, about business intelligence.

Mariska Veenhof-Bulten: Yeah, yeah. Actually, but, oh, man,

Dave Mariani: There’s not, there’s nothing going on here on that. That’s amazing.

Mariska Veenhof-Bulten: but indeed it will, if you don’t get it at, at high school or at, at, you know, in university when you follow up, how you’re supposed to learn, and also maybe, you know, for some people that, that didn’t get all the chances or maybe took a different route in their education first and then want to learn about data literacy, Especially, you know, with, with all these graphs on Corona flying around, I think some sort of basic level for everybody would be, would be required, you know, trying to also for your personal life, trying to interpret, make sense of all that data and asking critical questions on it.

Dave Mariani: That’s a good point. Just being able to read the graph on the growth of, of, of Corona is, you know, those charts can get, you know, and they, you talk about moving averages and seven day moving average, and I’m sure that’s just, that’s a sort of like, goes right, right over the head. A lot of people on trying to, you know, who just don’t understand what that means. but you know, and it’s, yeah, like it’s not in my background. I’ve never had, you know, went to UCLA and there was nothing there’s nothing oriented around that. I mean, nowadays I think it’s data and analytics and especially data science. I see a lot of stuff going on with data science. Right. And I focus on data science, but it’s almost like let’s just get back to basics here. And I like what you said, be able to read a chart and forget about, you know, about picking the right model for a particular, you know, for a prediction that’s, to me is super advanced, as opposed to just being able to, you know, know whether to use a bar chart or a line chart with dual axes.

Dave Mariani: I mean, you know, it’s, start with the basics. so, hopefully, you know, hopefully with companies like yourselves, really pioneering this there’ll be more material and there gotta be some e-learning courses. and some things that other companies can take advantage of because, I know you guys are pioneers in this field and hopefully you can teach us all how to be more data literate, literate, and how to actually bake that into, you know, into the organization. And, I really liked what you were going with, you know, when it comes to a job title, you should be able to articulate what the data skills are required for that job title. and that would all do, go a long way to probably promote data literacy, I think, as a program.

Mariska Veenhof-Bulten: Exactly. Yeah.

Dave Mariani: So Mariska, anything else that you think the audience should know, things that it did that, that worked, that didn’t work you know, maybe some potholes you stepped in and you just, this, just something to help the audience, maybe not make the mistakes that, that, you know, maybe that you had made or, and just get to the, get to success faster. So w what can you tell us about one of the things we should be doing or not doing for that matter

Mariska Veenhof-Bulten: Yeah, so I can, I can’t emphasize enough, if, because, a lot of books that you read about, you know, the Davis strategy and becoming data-driven are all very top down high level stuff, trying to make it relevant for your business team. So, really sit with your business teams and talk to them about how they might do their job better, with the help of data. So don’t try to do their job for them. That’s maybe a, a don’t guess, or try to, prove that you know how to do their job better than

Dave Mariani: I would be a donor. Yes. Okay. That’s good.

Mariska Veenhof-Bulten: But really sit with them and listen to where they are and how they can be more successful with data, because really that makes it so much more concrete and valuable because they can really see, like, Hey, this helps me, my job. I can really be more successful in my team if I develop these skills. And that is really, I talked to a lot of colleagues or outside, you know, in the business, other companies. And it seems that a lot of companies are thinking about, you know, working data-driven. How do I get started? It’s really about making it relevant for your colleagues that are doing their job and want to do a better job. so that’s really something that I can’t emphasize enough. So I’m going to ask, so I did it again, and, and maybe, don’t forget the fundamentals.

Mariska Veenhof-Bulten: So, I really liked one of the podcasts, that Ben Jones was in where he also mentioned, like, there’s really, indeed, as you said, it feels like there’s either no data literacy or you’re a data scientist really just on some, some of the basic stuff. And, try to put yourself in the shoes of somebody who feels maybe a bit ashamed that, oh, maybe I’m not so comfortable working with that data. So I, to provide them with a way to work on those fundamental skills and not forget about them. I can make everybody a data scientist.

Dave Mariani: Yeah. I know that’s a, that’s an amen on that. amen on that. So, yeah, that’s, that’s a great takeaway and look, I love your idea of, like, don’t try to tell people what to do. That never goes down well, but by offering them tools like you do to help them be better and then let them opt in to using those tools to make them better. It’s it’s, it’s, it’s, it’s a, it’s a great approach. So, and sounds like been really successful for you at bol.com. So Mariska, as always, I love talking about this with you. You are such an expert, thank you so much for spending time with us to learn more about data literacy and, you know, and, you know, w I know that we’ve done some, we’ve done a, a podcast together or a, we’ve done a webinar together on this with some other, industry leaders in this regard. So you can find that@scale.com to hear more about, and see some visuals about just how you put things together, really good stuff. So thank you Mariska for all your time today, and for helping us understand more about data literacy.

Mariska Veenhof-Bulten: Thanks. Thanks a lot for having me.

Dave Mariani: Okay. Have a great day.

Mariska Veenhof-Bulten: You too.