The Data Mix Podcast
Brian Booden and George Beaton are very excited to introduce The Data Mix - a new show focusing on some of the leading individuals in the Data and Analytics space! Our aim is to bring you our guests in a relaxed and conversational format, where you can ask questions and we can all learn more about some of the topical items in today's Business Intelligence and Data driven world.
The Data Mix Podcast
TDM S3 Ep9 - Beyond the Buzzwords: Rethinking Our Approach to Data and AI Literacy
AI literacy is everywhere. But most teams still don’t understand what it actually means.
→ And worse - they’re skipping the fundamentals of data altogether.
This week on The Data Mix, we’re joined by Angelika Klidas - educator, author of Data Literacy in Practice, and one of the most grounded voices in the space.
We get into:
⮑ Why AI literacy isn't a standalone skill
⮑ How data storytelling beats dashboards (every time)
⮑ Mentorship, mindset, and the confidence gap in tech
⮑ And what it takes to build truly inclusive data teams
Angelika doesn’t hold back - and this conversation might just reset how you think about literacy, leadership, and learning.
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Your regular fix of the best guests from the world of data and analytics. This is the data mix with Brian Boodin and George Beatham.
Speaker 2:Hey, george, back in. Hey, yeah, we're making a habit of this.
Speaker 1:I know, I know it's getting good man, honestly, and it's really fully clicked today because we're only one week away, less than one week away, from click connect, technically speaking. So, um, one of us is going and one of us is not. But I know, um, but you're gonna miss it. You're going. You do have to go somewhere right midway through the episode.
Speaker 2:So yes, I'm going to sneak off halfway through this episode and return to my day job for a steering committee meeting that I'm not allowed to miss.
Speaker 1:I see, I see I wasn't going to mention that bit, but you have. So, yeah, it's an exciting time. It's a nice sunny day. I think some people have extended bank holidays or in-service days. Today, certainly, my kids are kicking around downstairs having lots of fun in the garden. So, yeah, it's lucky.
Speaker 2:Then all happy days yeah, the weather is amazing. I just looked at the temperature in this in my office. It's an upstairs office with a big window like a greenhouse window. It's 24 degrees in here. That's why I'm not wearing a gilet like yourself.
Speaker 1:I did just open the window. Well, I just like I seem to have it on every day now. I seem to be doing something that involves activities next week, every day now. So we are where we are, but I don't care. It's cool, righto, we've got a lot to get through today, so, and I want to maximise the time that we have with you, george, before we lose you later on in the episode.
Speaker 1:So let's get started. Super, um, right, um, first things first. Uh, let's get these things out of the way. Um, I want to say first of all that the and the last episode that we have with women who click last week was our fastest ever downloaded pod. We had more than Brendan Grady He'll be annoyed about that. We had more than Mitchell Tan, who was another popular one earlier in the season as well. So your efforts make a difference, guys, and that's why we ask for reviews. If you enjoy the show, give us a scan. Actually, tell us that you enjoy it and we'll love you for it forever, and our gratitude is more than enough, mate, I would say.
Speaker 2:I mean it's massively appreciated and I think it's just testament to our current viewers and listeners that the numbers keep growing. So thank you for everybody that's liking us.
Speaker 1:Pretty awesome, I'll tell's liking us. Pretty awesome. I'll tell you what else is pretty awesome, george, being in the spotlight every week with the data fix. So it's time just to wind right into the segment here. The data fix gives you a breakdown of what's going on in the world of tech, george, and this week, what do we have on deck mate?
Speaker 2:So I want to talk about data sovereignty today, because that's coming up quite a bit in the news. Ai sovereignty is also coming up, but I'm not going to talk about that today. That's something slightly different. Data sovereignty that is. You've probably heard it. If you work in a technology industry, you'll get people in legal, et cetera saying we don't want our data going to the states, or people in the states saying we don't want our data sitting in China or potentially in the Middle East. So data sovereignty, it's important and it's a big thing in the Middle East. So data sovereignty, it's important and it's a big thing.
Speaker 2:But for AI, what everybody knows is that AI loves data. The more data that you can throw at AI, the better, and look at companies like Meta just now, who are now starting to scrape chats just to get more data. So the interesting thing here, then, is that China has very lax data privacy rules and there is a concern in the industry now that China is going to get ahead. Whoa, sorry about that, and the concern there on that is that we're going to be left behind because of our more stringent data laws. So I don't know if you were watching the news last week, brian, but there was quite an interesting half marathon that was run in China with robots. No, it's a half marathon With Chinese robots.
Speaker 2:It's worth a watch If you go on. You can Google it. It's on YouTube. It was quite amusing, but some of the times that these robots were making were actually really good and one of the theories as to why they're managing to get ahead, because you hear of companies like Boston Dynamics, etc. You see the videos, you see the awesome robots there, but China's race for AI, for companies like DeepSeek, like Manus, where they are really innovating, is all based on data and the access that they can get to data.
Speaker 2:So, that's, I think, is a concern, and it's an opportunity. It depends where you sit politically with on China. What is clear, though, is that I think in the West, where we have more mature probably data laws that are more in favor of your personal data protection, we're probably going to get stymied a little bit in that respect because we just don't have access, or there's a lot of hoops to jump through to get access to that data.
Speaker 1:I think data sovereignty is a very prevalent issue, especially with cloud software. Right, when you talk about regions in cloud software and the different privacy rules that span the globe, it's a serious problem when the data has to travel from Asia to Europe, to the UK via all these routes to get back, because some of those places are usually not sanctioned by companies for that data to pass through, and even more so when it's a silent pass through as well. Right, you know about the ones that are being advertised by the software, as this is where this software is hosted, but where does it go through in terms of the third parties and the connectors and all that kind of thing? I think it's quite a big thing for companies.
Speaker 2:It is, and I think the pressure on these companies to potentially move fast and break things I mean read that as, just do it now and ask for forgiveness later is going to be higher, because if you have got companies like or countries like China where their laws aren't quite stringent, they are going to make leaps and bounds above other countries. Until people get, until we can control our data better, good and bad. I'm glad that we've got strict data privacy rules, but I do worry that there's going to be pressure on companies to maybe tweak these a little bit or do things outside of what is legal, just so that they can get a competitive edge.
Speaker 1:Yes, and architecture of this sort is typically not a push-button type of switchover. It seems simple to pick a dropdown and change from EU to America or North America, but what that means in reality is usually lots of IP address changes, lots of network connectivity things spinning up and spinning down in the background, and that is not a simple process, although it looks simple when you look at it from the front end sometimes. So it's definitely something to keep an eye on. Everything's just been brought into sharp focus by, we'll just say, political relations at the moment. Right, and just leave it there, but it does bring all of these things into focus in terms of the sovereignty. Fascinating stuff, indeed. Anything else to finish us off, mate, that's all I've got for this week.
Speaker 1:Alright, fantastic. Well, that was the data fix for this week, and George is always on tap to give you the best stuff that's happening in the world of the game. Thank you, super duper Right, so on with proceedings for the show. We know this guest because she was here last week as part of a different topic. Women Do Click with Gwen and steph and priscilla and angelica, so let's bring her back on again. Hi, angelica, let's bring her on. Hey, angelica.
Speaker 1:Hello, welcome back right there back again yes, back again, back again. And look, yeah, there's, there's no coincidence. We're really wearing our g-lays again now because the time is fast approaching, right? So, um, some might say it's the time to go and sit beside the pool and pretend that you're working, but for angelica and I, we are going to be working exceptionally hard on you're in orlando, so, uh, click, connect comes to your well screens, I guess on Wednesday, I think the keynote will drop live on Wednesday morning. Lots of other things going on. How are you since last week, angelica? Sorry, how are you since last week?
Speaker 3:Having a bit of cold, as you can hear from my voice, but I hope to be well. And Friday I will be traveling towards America and on Monday I have some gatherings planned, you know, to make everything to start feel green again. I am green, by the way, but yeah, I'm truly looking forward to to go to to Orlando and see the Click family again. Yeah, and on Wednesday, indeed, we have the Women who Click session and it's the only session which starts at 5 o'clock. There is no other session at this moment and we are with seven fabulous women on stage and there will be some polls you can ask questions. So we will be as open as we can be on stage and answer the questions that will be asked.
Speaker 2:Good. So, angelica, you're either going to have to do that in the bar or close the bar.
Speaker 3:then, if you're the only session on at 5 pm, the bar is in front of us and the space will be full. I believe it's theatre 2 that we are in. We just had a meeting with Mike Duval for the sessions and all kinds of tips he gave and I learned the app is live, so I put my sessions in the ones that I want to attend. Also about data quality, of course, and how important the good quality of data is for your AI solutions, because the results will be as good as the data is. Let's see how that goes and, yeah, I'm truly looking forward to it.
Speaker 1:Well, and Luke, I think these are some topics that we're going to be talking about in the interview as well. We've definitely touched some of these things, so I think, without further ado, we'll get into it and, for anyone that's watching, I'm not sure if our LinkedIn Live triggered, so this may be a replay later on, but we will run what we've got because we love it. And George's dogs are back.
Speaker 2:It's because of the sun. I left the door open because it was so warm. I'm going to mute.
Speaker 1:No worries, mate. Thanks for coming, mate, and we will see you on the next episode. All right, hope it goes well this afternoon. Thanks for coming, mate, and we will see you on the next episode.
Speaker 2:All right Hope it goes well this afternoon.
Speaker 1:Thank you very much. Bye-bye, and we will get running here, guys, we will see you in about 35 minutes. Okay, just drop any questions in the chat for us. Super hey everyone. How are you? We're back for another episode of the Datamix and, as mentioned in the main show, we've got Angelica Clydus with us, who's down here. Welcome, angelica, how are you?
Speaker 3:Yeah, I'm good. Thank you, and you guys Good.
Speaker 2:Awesome, thank you, nice to see you again.
Speaker 1:Nice one. And like we were just discussing country locations and stuff, the Netherlands, you are Angelica right. Yes, I am yeah, yeah. Country locations and stuff. Yeah, the Netherlands, you are Angelica right, yes, I am yeah, yeah.
Speaker 3:Which which part Um? I'm about 50 kilometers above Amsterdam. Okay, north Holland North.
Speaker 1:I was. I was at a dance festival in Zandvoort, just outside um Amsterdam.
Speaker 3:Yeah, that's um that's. That's not far away from my home, brian.
Speaker 1:Oh, nice, nice. I'll remember that for next time if I end up going.
Speaker 3:You have a place to sleep, huh, well, yeah, yeah.
Speaker 1:Well, there you go. Maybe a bit far to walk after the event, but there you go.
Speaker 2:I get to Chapal Airport. Every probably twice a year I'm in Chapal and it always fascinates me that when you get to at least one bit, when I'm going for the plane, it says you're currently 5 metres below sea level at the airport.
Speaker 1:I always think wow crazy right yeah, and what's the way that we pronounce? Because I hear skipple. It's really difficult to know, when you don't live there, how to pronounce it.
Speaker 3:So how do you pronounce? It's really difficult to know, when you don't live there, how to pronounce it. So how do you pronounce it? It's Schiphol.
Speaker 1:Scots, we can just about say that, but no other country in the world has even a chance of saying that properly. Schiphol.
Speaker 3:It's very difficult.
Speaker 1:Well, as much as we love our aviation, we have you here for other reasons today. Angelica right and data literacy yeah, it's been a thing that you've been involved in for a long time. So for our audience, who I can't believe anyone doesn't know who you are, but why don't you give us a little bit of an intro about who you are and what you've been up to lately?
Speaker 3:uh well, angelica Clito's, from the Netherlands uh, 62 years old, mom of three, also having a daughter-in-law and a son-in-law. We all are crazy about rugby, so all three of my children play rugby. My son is in the second class rugby, so he is playing some hard games sometimes. Wrote a book Data Literacy in Practice almost two years ago. Now I'm working on the second one, together with Kevin Hannigan, my best friend, and well, the last year I was working for a municipality here in the Netherlands which was on the German border, so it was about two hours and 15 minutes drive from my home, and we worked on data-driven working for the municipality. And now I'm involved at one of the biggest unions here in the Netherlands to help them with data and AI literacy. So something very much to my core.
Speaker 1:Well, there is the launching point, right? You said those magic words data literacy and you also mentioned AI in that sentence. So our bingo card is full and we're only one minute into the episode, which is awesome. But to ask a little bit more seriously about that, obviously data literacy has been a hot topic for the longest time now, but you did mention AI in that sentence as well, and AI literacy, from my perspective, is something that's still pretty much misunderstood about what it is, whether it's its own thing, whether it deserves its own category or whether it's just hiding in the shadows of data literacy. So, to kick us off, what do you think? Where do you stand on that argument?
Speaker 3:I think it's a misused term first of all. Secondly, I think it's a misused term first of all. Secondly, I think it's a marketing buzzword. So we need to address AI literacies in our sentences, in the things that we do, but, to be honest, everything is fueled by data. It's the foundational role of data that is included here. So all systems within an organization operate on data. Every decision, every prediction, every insight generated by an AI model is rooted in the quality and structure of data.
Speaker 3:Right, and even nowadays, data comes in the structured and unstructured way, and it's the fuel of AI. Right, and without a deep understanding of data and data literacy, you will never understand AI and the results of AI. So I think it's a subset, it's an advanced element of data literacy. That's how I look at it and it means something for organization because it goes beyond tool-specific tools, right, focus. It's broader than that. You need to develop that holistic view for an organization to work on both data, but also AI elements, but also visualization, literacy or other elements that we can think of when it comes to the data world.
Speaker 2:Okay, interesting. So is it a prerequisite to know about to do your data literacy training and become competent there before you can go into AI, or can you start with the AI and jump over that part?
Speaker 3:From my personal point of view, if I do my data literacy fundamentals now, it has the title data and AI literacy because people are so hooked on the term AI, so for marketing purposes only, so hooked on the term AI, so for marketing purposes only. But I think data and AI comes together right and that's how I also address it in my trainings. So we use AI elements as well in my trainings in the foundational skill set of data literacy. I don't like to wiggle with it because it's misunderstood.
Speaker 1:Yeah, and I think that that is a thing, definitely, and it's confusing. And it's confusing because many organizations aren't even on a solid footing with their data literacy starting point yet. So to throw in AI and to have all these misconceptions that AI might somehow preempt to answer George's question preempt the need to have data literacy training or even understand how data works, it's a very confusing circle that we're living in, right, and I mean, would you agree with that? I just think the AI has complicated things so much that it's made so many organizations just jump that whole step of what data foundationally means to them, because they think it can just be in some way solved by AI. Not all organizations, but I see that sometimes when we're going in, it's just like just throw AI at it and let's see if that can solve everything that we need. Are you seeing that a little bit as well?
Speaker 3:Yeah, I'm seeing that a little bit as well. Some organizations are more cautious, so they are more arranging things, setting up some boundaries to use generative AI, for example. But I know also organizations that say generative AI is AI, and I think, no, that's not true. Generative AI is a solution built on AI algorithms, and that makes me a little bit ticky, so I always have to address it, then address it, address it, address it, and that's hard. Don't approach it as two separate things, because they are so much intertwined and without data, structured or unstructured, there is no AI possibility and the results of AI are as good as the data that is put in. So data governance, data management, data quality, it's all there.
Speaker 2:Yeah, good, interesting, and one thing that you jumped out for me there was that it's a marketing trick almost, and that's something that I've been seeing a lot as well. People throw out this term AI all the time without really understanding what it is. Of course, I've seen chat, gpt and it's starting to enter the mainstream, but organizations feel that they have to do something with it. I think it's right for you to call it data literacy and AI now, and I just wonder if that's helping you then to reach a wider audience. Yes, it is.
Speaker 3:Exactly, yeah, and that is also the moment when Kevin and I started thinking about the new book, which is a revised version of the first book.
Speaker 3:Ai is already in there, but it's not mentioned that thoroughly, that deep, and now we decided to craft a new book and the first chapter will be about, yeah, taking the fog away in an understanding of what AI and what data is, and how everything is intertwined into different areas, because we have machine learning, we have image recognition, we have so many things, and if you like to work with it as an organization, you should have a basic understanding of what ai is just from the beginning.
Speaker 3:In, in simple words, for uh, for people to understand how an algorithm works, because we all have algorithms, right, if we bake a cake, we have to gather our ingredients, the processes, how we create the pie, and then at the end, we have the output and that is our pie. Right, and algorithms work that way as well. They have a process, they have input, but they also have output, and I think the lack of critical thinking and questioning is one of the reason that I'm always trying to push forward. You should ask questions, you should, you should look at the sources and everything. Don't assume that chat, gpt or copilot or notebook LLM is correct.
Speaker 1:I think what you said critical thinking is a very important phrase that you used there. It reminds me very much and the reason I smiled halfway through that sentence. It's reminded me of an old colleague probably of Kevin's as well Jordan Morrow, who always used to say to me be curious, right, and that applies to AI. So when you get a prompt, when you fire on a prompt and you get an answer back, don't assume that it's right. You have to re-prompt probably five to 10 times to get the correct answer. I'll give you a super simple example and then we'll move on slightly away from the AI topic. But ChatGPT has a habit of putting long dashes into all the content that it spits out and immediately you can tell AI driven content on LinkedIn because it's got long dashes in it with no spaces and you have to constantly tell it to use short dashes with spaces to make it sound more human and it does not remember. So that's the way that I pick out content that I see on LinkedIn as AI generated versus human.
Speaker 1:And it's okay to have an AI base for your post, right, but you have to put human crafting into it afterwards humans should always be in the loop period yeah, and I think, just to follow on to that as well, like having someone to be able to keep you sane on that from like the mentoring side, and especially when it comes to the mindset of using AI and using literacy and understanding what these concepts mean. I mean it's becoming more important in the day-to-day, angelica right.
Speaker 3:Yeah, it does. Mentoring is, I think, super important and as a teacher at the Amsterdam University of Applied Sciences, I love being that mentor, that lecturer, that coach that help people to grow, not only women. You know I am a part of the Women who Click team, but I think it's my core element is always to help people, even if you are a man or a woman, and I always talk about that equality, diversion and inclusion in your teams, because if you have the various looks of things right to your data project, the various looks of things right to your data project, you will have several ways to approach things as well in your data project, and I think that that's very important. So, yeah, first of all, mentorship is needed. I know you guys do that probably as well with your customers. I do it as well. My knowledge should not be restricted to me only. It should be out there for the world. I'm 62. I'm always almost five years to go and then I can retire. Probably I won't, but my knowledge should be shared.
Speaker 2:Yes, what a good attitude. I think we can all learn from that.
Speaker 1:Yeah, I think that there's not everyone stands up to be counted, and what I mean by that is that some people don't think they've got it in them to provide that guidance and that mentorship and to be able to be able to set the minds of people in the right direction. But I think a lot more people are capable of it than they know. I see what I've seen, especially on social media, as a transition of lurkers who start just getting involved and commenting on things and then they start posting on things and, before you know it, they're doing videos telling people. This is what I think about something and sometimes some things.
Speaker 1:People don't classify that as mentorship, but it absolutely is. It is, yeah, it takes many forms. It doesn't mean just sitting in a classroom speaking to people. It means being willing to give your opinion when others will not. I think that is a form of mentorship as well, and maybe not people don't realize that, um, but especially when it comes to like ai and data, I think that people should just say what they think, because if we don't say and I mean the royal, we, everyone then the machines will say for us, and that's when it gets a bit scary, right if we don't give the opinions, as humans and the machines will start to give the opinions.
Speaker 1:So it's kind of we have to, it's kind of an obligation for us, right exactly, yeah, and I think you know.
Speaker 3:You know the fun thing is being a mentor and a teacher. Sometimes I discover raw diamonds, right, and if I look back to the students that I have teached the amazing world of data and analytics and where they are now almost 40 percent of my students work in a data environment. Some of them became lecturers as well. One of them is two of them actually. They are with me now in front of the classroom because I want that one and that one. They can teach as well and I would love to see that growth in people.
Speaker 1:I think that is important. When you talk about um diversity and I know that's rich coming from a podcast that's um being run by two like middle-aged white guys but we think we're quite right. We think we read quite well in terms of the people that we have on um. I think we opened our our series this year with Roseanne Berner. We've had you on and we've also got Women who Click coming on as well pretty soon hopefully. So it really is important. And are you seeing that diversity start to have a real effect on the way that people are thinking? Are they starting to realize that there's more than one way to skin a cat when it looks at these things as well?
Speaker 3:yeah, but you have to. As a project leader or a project manager or manager, you have to guide those discussions right. What we, what we see usually in diverse groups, is that, uh, people are not confident enough, but also some people suffer from the imposter syndrome. You just put it up there and I suffered for that, of this imposter syndrome as well. I was talking to Janine, you know her, and I told her I'm not sure if my experience or me being in one of those meetups in Sweden is okay, because I don't feel that I belong that well in the technical group, because usually the discussions are very technical. And she said now, angelica, your value is that big because you can just pull them back to the business question, to the business element, and that's the, the strength that you give to the group. And she said to me you are suffering from the imposter syndrome.
Speaker 3:And I started reading about it and then I thought, all right. And then I saw a story and even Janine told me as well you know, if a man wants to apply for a job and he looks at his resume and at the skillset that is required for a job and he hits the 70%, he will just apply Bold, fearless, without any thing. But females, they want to have the 100%, and I think that's the biggest difference. But then, even though and that's what to give, to give the girls that I work with that confidence that, even when you do not hit the 100 percent mark, 80 percent is sometimes just fine enough, right, and uh, just go for it. If you, if you see something that is uh near to your happiness, right, because I truly love in ikigai, which has the four elements are you good at it? What does the world need? Can you earn money with it? And is it your passion? Wow, then you should go for it, because your story, if you are invited, your story, will help.
Speaker 2:Yeah, so.
Speaker 3:Angelica, this is it chimes.
Speaker 2:Well, just, I've got a client just now, so we're doing quite a big piece of work for them just now. But one of them is putting in a new HR system, and the head of HR is a woman and as we were going through the requirements and specifying the system, she said OK, what about the annual review system? She said okay, what about the annual review system? Is it weighted for different? When you're self-scoring yourself, is it weighted for women versus men? And I said, well, in the system? No, I don't think so. I haven't seen that as a requirement before.
Speaker 2:She explained to me then that if you're giving, if you've to give yourself a rating of one to five for a task when you're doing your annual review, most guys will do five. I'm going to say well, why am I going to say four? I'm going to say five and then they can challenge me, but I'm going to go in with a five, whereas I was told that a woman will go in with a more honest answer. And then therefore and often it's not challenged then by the manager the manager will say well, she's just a three, okay, she doesn't get a bonus, or she gets a smaller bonus than the guy. It's something.
Speaker 3:I hadn't considered before. Yeah, exactly, but that is what is happening in the world and I am truly, very, very proud and thankful that I can help some women in data to actually grow beyond and believe in themselves. Right, tell the good story and just believe in yourself because you're worth it, right. You're worth it, right, yeah.
Speaker 2:And we all know that having a woman in the team, in a data team, it brings a completely different perspective and the quality of the output I've found time and time again is you know, you're more than the sum of your parts in that case, but lots of examples over time of how it benefits the team.
Speaker 3:Yeah, that's why we need DEY right, that's why we need it in our teams. We used to work I remember, you know, when I was hiring consultants, when I used to work at the governmental organization here in the Netherlands, I was hiring one person. He did it all Getting the requirements, building the data model, building the dashboard and the reports, do the testing area and then implementing it as well. Those things are not there anymore because we need that diversity in our teams. Yeah, I think it's very important to think that way. Yeah, yeah.
Speaker 2:The problem, Angelica, and sorry, I'll pass over to you in a minute, Brian but the problem that I'm finding is that finding enough women that at this level, and what I mean by this is like coming into industry, because really you need to get them at school, even primary school school. So last year I went back to my secondary school and I gave a guest lecture to the school, the computer science class there was. I think there was 30 students in there, ages between 15 and 17. And out of the 30 students there was only two girls in that class. And get this? The teacher was a female, female. So we had a female teacher and she was saying every year at assembly I say girls, you're most welcome, please apply, please apply and join my class. But she said year-on-year and it's so difficult to get these girls into my computer science class.
Speaker 3:It should be promoted. Yeah, it should be promoted and that's, I think, the marketing element that we need at schools as well, my classes as well. Sometimes I do not even have women in my class. It happens Sometimes I have two and sometimes I have three or four but then putting them in the project teams when they have to deliver a project based on Qlik Sense in this case, I use the Qlik Academic Program and they give so much value to the group. They're working with the men who are the hardcore programmers and I love that. I love that. I love that the diversity is there. But, yeah, sometimes I simply do not have women in my group.
Speaker 1:Yeah, the dynamics are kind of weird at times and it hasn't changed over time. I'm a computer science graduate as well and we had two in a class of like 40. So it's still. I mean, I don't want to get into a whole education discussion at this particular point in time, but what I will say is that, you know, some people close to me have we've challenged the school system in terms of which I sometimes think is too broad for everyone to consume. I don't think there's really room for some people to pursue the passions that they really want to, because they're too busy having to take other subjects that they just don't care about, and I do think that we're maybe still doing it a little bit wrong.
Speaker 1:But maybe that's another topic for not even a data mix podcast, but something else. But I think what you talked about with the ClickAcademic program, that whole ethos of storytelling, I think, is something that has changed from that computer science background that maybe some of us were brought up in. Like 20 years ago as well, the concept of visual storytelling wasn't really a thing, right? It's very much you tell your story by the way that you program and the output that you create, and now it's very different and again, we've had some visual storytellers on in the past and it really is becoming quite a big thing and I guess, well, you know, with your data quizzes and stuff, angelica right, and your data challenger stuff in escape rooms, storytelling is a massive part of that, not even just visual, you know.
Speaker 3:Yeah, exactly, I think if you have that power to tell stories based on your experience, probably, or maybe something from the news, and build a story around that, it's very, very, very powerful. Uh, because it will stick. Um as uh, as a teacher, I always uh or a trainer, in this case as well I tell something about a framework. Then I put there in the story a real life story sometimes, but then they can resonate with it, right, because it will stick in their minds. I used I did a test last year in Vaughan where I was conducting a data visualization training including data storytelling.
Speaker 3:Just a section of two hours of data storytelling and the basic concepts, and at the beginning I told a story about about the price-winning project that I did here in the Netherlands of for a safety region and we measured the process between the dispatch call and the treatment, the medical treatment, and we were able saving 60 minutes 20 minutes in time and life-saving minutes. So that was a very important story and I just told the story with some sheets and I started out with actual images and even at the end of the training the people would remember that story. So it's so cool if you're able to do that and, yeah, well, I have a lot of experience in projects, so all those stories I can bring with me and tell them and that's so cool.
Speaker 1:That ties back quite nicely into the mentoring thing that we talked about earlier, right, and having a mentor usually means that you get the value of some of that experience and you get the value of those stories and I think even just as importantly, you get the anecdotal intelligence to be able to tell those stories in a way that relates to your audience. Right, and that is incredibly. It's an incredibly subtle thing to do. It's quite easy just to tell a story if it actually happened to you, but to be able to blend that story just a little bit, to be able to tell, give the right nuance to the message that you're giving, I think that's quite a skill. I respect everyone who works in education and does does this type of thing every day to get their students just to sit still. So, yeah, I think a lot what you do yeah, I.
Speaker 3:I was talking this morning to a student, a former student of mine. She just finished her thesis, so she delivered it yesterday and I was going to the thesis. She suffered from the same situation as I had last year with my mom she suddenly passed away and her mom passed away in november the year before, so it was only a few months in between and we kept in contact because sometimes you have, as a teacher, you have and as a mentor coach, you have that relation with people that you can talk for hours about things, and she was just talking this morning about the storytelling aspect and that she remembers the stories. So it's it's so cool to hear that and I'm so proud of people that are able to do it as well and get that you know, that storytelling element in the teaching materials that they have.
Speaker 1:Yeah.
Speaker 2:Yeah, and Brian was just before we went live. Brian was telling an interesting snippet of a story about somebody he knows who has a wire framing toolkit. So I was thinking, do you need any special skills to be able to do this? And I remember back well over 20 years ago I was using felt. It was actually something called fuzzy felt, but it was just thin felt that you could stick together and then build a wireframe with that. Now this was for designing sort of blocky websites, but you could then tell a story and you could interactively work with a group of people and say, ok, where should the header go and do we have a subtitle here? Ok, are we going to put a picture over here? Are we going to have a scroll bar down the side? And I have all of these little fuzzy felt cutouts that stuck together Very rapidly. You could visualize something. So I think it is something that everybody can learn. It's not something that you have to have any special skills in.
Speaker 3:No, it's just. You can choose for various options, of course. Right, the process I call it sketching and chatting, or chatting and sketching, and it is a continuous improvement. Right, because you have to sketch and you have to design things, and I think it's one of the most important elements, again from a multidisciplinary area, that you can work on a cool looking dashboard. I sometimes get the question well, aren't you taking away a lot of creativity from the people that build the dashboards? Maybe it is, but I think it's worthwhile when you work with the business and get the right requirements to actually build an amazing dashboard. That is the most important thing, because we tend to build so much graphs that people can't see the trees for the forest anymore.
Speaker 1:I think that sometimes the art of using white space is lost. I think that sometimes the art of using white space is lost Again. Just to go back to some projects that I've been involved in recently, I've seen some very information-packed dashboards. You couldn't even really call it a dashboard at times. I would say it was just overwhelming to look at. And any time I think you look at a dashboard and you sort of go like this to start with, there's a bit like okay, that's too much.
Speaker 1:But in terms of that visual storytelling element as well, I think I think there is a use case for AI here to help drafting and redrafting and redrafting. But it's critical that it's not just build me a draft of a dashboard. You have to give very specific instructions of. I want to get these points across. I want to start here. These are the KPIs that I'm dealing with no more than five titles on a screen. Can you give me a layout concept? It's not just a case of just build me a dashboard, right, and I think that's the part that we're not quite at yet.
Speaker 3:I think one of the most important things that I see in Dashboard is that people tend to forget the contextual analysis element in it. I've learned from Barry's team you know, barry, from Bitmetric that we always should start using the business question as a title In the subtitle more information, when you, when you do you want to switch between measures or dimensions, you should give that explanation in the footer. I think it's very, very powerful. But also some insight in textual elements, because in textual elements we can also make a calculation right and it always is updated. So I think the contextual part, including the visual part, they should be very, very much connected and we tend to forget that.
Speaker 1:We do, we do, and it's interesting that you talk about the landscape of data and where it sits in terms of physical applications and stuff, but in terms of real life application, you must have been involved in a lot of areas and a lot of different projects, so are there any in particular that you've focused on recently that you think are worth giving a shout out to? We've got like five minutes left, I think, so yeah.
Speaker 3:At the moment I'm am involved with, of course, with data and AR literacy, so I'm preparing the projects, the learning lines. We created data personas right and every data persona has a certain kind of skill set, so I'm not involved in dashboarding at the moment. I hope it will come a little bit because I like that type of creativity. But I was working with Van Lorde, my customer, I think you've seen it on stage in Orlando last year. They won the transformation award because we build the climate risk overview application, which is free for the world it's running on clickorg and because we suffer from the rising sea, so coastlines are eroding, sometimes even coastal lines are differently built, with new harbors or homes or whatever, and the coastlines are not protected. So with this um, with this application, we identify all hot spots around the world, with the number of people living there and what would be the causes. Due to all kinds of data from nasa, from oh, whatever, um and um, we were able to find those hotspots in local governments or local organizations and even from ORT can do projects all around the world, and I like the way they build things from a sustainability perspective because they they have two solutions the soft one and the hard one.
Speaker 3:The soft one one is built about 35, 40 kilometers from my home.
Speaker 3:That was the weakest spot in the Netherlands and they build it with the soft elements like sand, and they created a whole new area, protecting the coastline but also creating a new world for all kinds of elements and flowers, and it's so beautiful there. And then in senegal the coastline was eroded in sally senegal and the fishermen would couldn't protect their boats anymore, but also the coastline was eroding due to wrong building and everything, and they built with a hard solution with rocks and everything. They built protection walls for 4.5 kilometers from my head and the coastline is protected. Now the fishermen can protect their boats, they can go out for fishing and even tourism is growing again. So that's amazing how those things can work and help.
Speaker 3:And I really, really like that from the author. Rachel Terry is the director of sustainability and she's an amazing lady, and Gerben is the technician we are now building, or he is building. Actually he's the magician. He's now adding new data of finding out where the farmer land is near the coastlines in that 10 kilometer area, but also how salty the area is at the moment.
Speaker 3:So because when it's salty you can't build that much vegetables anymore and that is what we would like to uh to add before connect so we can give the result also again to julie k from from click yeah that's right.
Speaker 1:I think what's super interesting about that and just to sort of book end the the conversation here is, obviously that means, if you want to talk to Angelica more, she will be at Click Connect in Orlando this year and there's there's a theme here we can see, but it's only five weeks away now as as of recording of this episode. It's five weeks away. Um, when we get it out, um, it will be a bit closer. But, angelica, just like a massive, massive thank you for coming on with us. And also, you know we have Women in Click coming very soon as well. So this is not a goodbye, it's just a farewell or the other way around. I can't remember what you said, george final closing thoughts here.
Speaker 2:Yeah, thank you. I mean we've covered a lot of ground here. I feel that we could have used double the time, but fascinating insights, lots of takeaways from today and lots of food for thought. So thank you very much for your time, angelica.
Speaker 3:You're most welcome. All right, yeah, you're most welcome.
Speaker 1:Thanks, angelica. We appreciate it a lot and we'll see you back in the mainstream shortly. Cheers, see you soon. Okay, stream shortly. Cheers, see you soon. Let me remember to unmute us. There we go. I unmuted us, so hopefully you can hear me and I can hear you. So we lost a person. And obviously, yeah, we had a bit of a problem with the LinkedIn live stream but we're going to get that all rebroadcast and it's all going to be good.
Speaker 1:I really enjoyed that conversation. You know I've had two conversations with you in recent weeks and different guises. It's fascinating to me how the world is divided with data literacy right, there are those that really embrace it and there are those that are still to get on the train or still think that analytics and data is a practical exercise where you physically build things and you don't need prerequisites for that. And we talked about things like frameworks. We talked about things like data versus AI literacy and, again, I would imagine this is one of the big messages that's going to go in or come out of Connect next week. Right, what are your top three messages that you want to deliver at Click Connect next week? Put you on the spot.
Speaker 3:I think that yeah, you put me just there. Don't think that AI has nothing to do with data, first of all. Secondly, don't assume that people know what data or AI literacy is. And I think the third one, you need to address it from an organizational perspective high over, and from there build it downwards and let leaders lead by example.
Speaker 1:That last one is super important. That last one is you don't often get cries from people further down the chain that we need data literacy, but if you don't have that training, you can end up in quite a pickle. If you're rolling out advanced stuff too quickly, it can be quite hard to recover from in terms of the reputation of the tool. Is doing it wrong or we didn't build it right, or it's not giving the right answer when really what the case is that you don't understand, as a user, how to interpret the information that's being put in front of you, or it hasn't been guided in the right way using data literacy principles. So I think it's an interesting segue and I feel like this is the year Angelica. I feel like this is the year that really yeah.
Speaker 3:Since this year. Last year, data and AI literacy is booming and I see a lot of requests passing by. I have two projects running now, big projects, um. And then the fun thing is and I think that's very important to share I'm I'm working in this big, big, big organization since I believe it's February or something the two trainings about data and AI literacy there and I'm doing my stakeholder analysis right. So I go through all the organization, talk with everybody from the how do you say that in English? High rec Within an organization.
Speaker 3:Yeah, so first the management, then the leaders, team leaders, then the people that do the work actually, and I'm trying to follow that path. And then what I found out is that usually within the organization there are so many data-savvy persons. We just have to connect the dots right and build that community. And if you make it a community and have once-in-six-week sessions with each other, talk about data, talk about small problems that maybe somebody else knows it now and now you know who to find for what kind of questions, but also discover new insights from combined data sets during a data time, you can do a lot of amazing things. So, yeah, I really love what I do.
Speaker 1:I can see that, and I can see how important not only that initial tranche of training is, but also the maintenance mode that you talked about there, of like every six weeks or every month.
Speaker 1:You need to have the like-minded people together, because otherwise you forget about data and it sounds preposterous, right, but you absolutely do. If you don't practice these things, then they will disappear from your mind, just like any other topic as well, and that's when we regress back to. Let's just build it and hope it gives the right answer, right? Whereas it's quite a simple philosophy to just head back to the business use case and be sure, are we answering a question here? If we're not, then why are we building it? There has to be a very, very good reason behind it all. So, anyway, I'm sure we will hear many, many more things about data literacy and AI from your session and from many other sessions at Click Connect, and it's very exciting now because we mentioned in the show there when we were recording five weeks ago. We recorded now and actually we did Women who Click first before this episode.
Speaker 3:So it's crazy.
Speaker 1:And now we're like four days away, five days away from it all.
Speaker 3:Yeah, so I'm so looking forward to it. As I said, I'm so, so happy to go and see see the family, but also learn from others. I, I love that. Yeah, I love that.
Speaker 2:But first, some things to do.
Speaker 3:Two days to go full with work doing the first pilot training of ai awareness, uh, at one of my projects. Um. So yeah, I'm very curious how it will run and how it, how it is, will be perceived. Something about history, something about how an algorithms work, what types there are, just from a basic understanding what is it?
Speaker 1:and what can you do with it? I know, I know and um the one of the reasons I'm very excited for next week, as well as everything you've talked about, but also to see everyone um. I also have you know my um interview with my phone. I'm very excited and that will be broadcast live um on linkedin if it all works hopefully.
Speaker 3:Yeah. Yeah, we have the same right. We have it on wednesday from four to five. We have also the uh, the data voyages, uh broadcasting from the broadcasting zone. We have two amazing guests um malcolm from click, who's the product director, and then we have gwen dolin's time. She's from a big organization that uses click sense as well, so it's good to bring those people together. You have mike capone, and there will be so many other amazing people that we can talk with and learn from.
Speaker 1:A quick sneak peek. I got my recording kit arrived today, my wireless recording kit, so I'll be able to talk to people a bit more easily just walking around the show floor. So hopefully there'll be quite a lot of content from me and the Datamix coming from ClickConnect and Orlando as well, with lots of other surprises. So we have been focused on that. But it is an important event in our calendar and, yeah, I'm excited. I'm excited. So George had to disappear. I just want to. We're running off to the hour now, so again, I want to be respectful of time and hopefully we'll get this out again on LinkedIn before the end of the week.
Speaker 1:That would be amazing, but thank you so much, Angelica. I'm looking forward to spending some quality time with you, and this has been a very, very enlightening episode for everyone that's out there as well. Thanks to everyone that's out there, we'll bring George back for the full episode next time around, and we look forward to bringing you some cool live content for Click Connect as well. We'll see you then. Bye-bye, bye.
