 Hello and welcome to my Career and Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I am your host Shannon Kemp and today we're talking to Ben Shine at DOMO. With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.dativersity.net and use code DVTOX for 20% off your purchase. Hello and welcome my name is Shannon Kemp and I'm the Chief Digital Officer at Dataversity and this is my career in data, a Dataversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who make those careers a little bit easier. To keep up to date in the latest in data management education, go to dataversity.net forward slash subscribe. Today we are joined by Ben Shine, the Senior Vice President of Product at DOMO. And normally this is where a podcast host would read a short bio of the guest. But in this podcast, your bio is what we're here to talk about. Ben, hello and welcome. Thanks Shannon, really happy to be here to talk about data, data careers, data journeys, all that fun stuff. You know, when we started this podcast, you were one of the first people that I thought of because when I first met you, your title was a Vice President of Data Curiosity. We had a great conversation around that. So I'm really excited to dive into this. And now congratulations on your promotion. You're the Senior Vice President of Product at DOMO. So let's start with what is DOMO and what is it that you're currently doing? Yeah, no. So DOMO, really talking about DOMO is a data experience platform, right? So we're creating the spoke, meaningful, relevant data experiences for our users, for people everywhere and really those experiences to us should be unlocking data not just for a data scientist or someone with data in their title, but really that they should be experiences that everyone in the organization read. I think there's lots of studies and research you can look at that five or 10 percent of people actually use data in an organization. And our goal is that our data experiences are accessible to everyone, even if you're on a factory floor in a retail outlet or a coffee hut or whatever it is that data and experience with data is impactful. And ultimately, the reason we want that is because we want everyone to have you know, an impact on their business or their organization, right? A positive impact, an exponential impact. If you do that correctly. And so that's sort of our overall vision is to create those data experiences so that everyone can have a positive impact on their business. All that being said, that sounds great. And that's rational. I get to see that a lot with our customers. The day to day can certainly be a little different. I used to joke that I could never give up the data curiosity title because it was too good of an intro and a hook and all those things. And for a long time I did it and it really let me expand as a thought leader around data as a coach and a mentor to our customer base as an advisor and input to our product teams and how we're developing things. But the chance in January to really take over all our overall product strategy, including product management and UX really was was was too good of a chance to do those things to create those great data experiences. And so while I still have that that love for the for the title, I do joke that I feel like before people listen to me and now they listen to me. Right. It's a different a different kind of listen that they weren't, you know, I had it but now I have a lot more say. And so day to day, what does that mean? Where do I see my job and my role in the company? I think a lot of times it's about connecting dots, right? There's lots of different work going on, you know, in different areas of our product in the different components that make up the static experience platform, whether it's, you know, magic ETL or it's the data sets or data ingestion or integration or visualization or app building. And so a lot of times I'm trying to have that big picture and say, well, you know, how do these things connect? How do I, you know, maybe solve multiple problems in one way so we can be efficient with our resources? And so some of that's just my own observation and my own, you know, I use the product. They actually checked when I when I took this job in January and I have the card in Domo somewhere. But I in my time at Target before Domo and at Domo, I've created almost over 18,000 different objects, you know, visualizations, data sets, data transformations. And so I use it. So I bring that perspective as a practitioner to the product strategy. But also part of my job is how do we how do we listen to the signal? How do we listen to customers, listen to users? Both their actual voice and their sort of derived voice in the data that we have about what they're doing, right? You know, how do we how do we let that be the fuel? But not always the, you know, it's not always about doing exactly what someone's asking. It's OK, well, what's the pain? What's the friction? Let me understand that I underline friction. And then let me connect those dots and say, well, these five frictions that customers might be articulating in different ways. Actually can be solved together holistically by reducing this friction, creating a better experience, letting people have that business impact. And so that's a lot of fun. I mean, there's frustrating moments for sure and a lot of different people and stakeholders to try to balance, whether it's industry analysts versus our own internal teams, versus our customers and our leadership and marketing. But but it's it's a lot of fun day to day to most days, at least. I love it. That is so great. And we'll come back to that a little bit in a moment because to your uses of data, that's very interesting. But let's let's back up a little bit to begin with. And so tell me, Ben, when you were in elementary school, was this the dream? Did you dream that I'm going to grow up and be the senior VP of product? So definitely wasn't the dream. I will say I was just probably a little dorky. What one of the things that comes to mind from that time period is I was obsessed with airports and designs and like looking at airport maps. So when we go to the airport, like, how are the gates arranged? And while in Atlanta, they do a train and a dullest. They, you know, experiment with the mobile lounges and one of that work. And so I never thought I would really grow up and design airports. But that was one of my one of the things I was really passionate about, you know, sports and other things. But there probably was a better shot that I could become an airport designer than like a majorly baseball player. But it was. But I do think like it does come down to like, how do you organize people? How do you organize the complex system? It it those kinds of challenges, those kinds of problems still are what excite me. But I never got to. Although now I do travel a lot for my job. So I also am an expert on Delta Skyclubs and which gate is my wife makes fun of me that I know which gate is better at the Minneapolis airport. You're trying to get there quickly and stuff like that. But but I never got to actually design the airport. At least not yet. I shouldn't say never, right? I think, you know, that goes to the point, like from very, very young curiosity was instilled within you. Like that was a big, huge thing. Yeah, no, it definitely was. And I think, you know, I just I wanted more. And it was such an esoteric topic. It's not like there were tons of books about airports, right? But I probably have to ask, I should have asked my mother when I saw this question that she remembers, like how much I feel like I remember having like brochures and like doing I just I like I wanted to engage and understand it, right? That's that's fascinating. I love that. So tell me then, how did that evolve? And when you got in as you got older and started selecting your topics in school, you know, what changed and what did you start studying? Yeah, I mean, so it's funny because I don't think I certainly don't have a very traditional background. I I would, you know, probably say I'd never taken really a full college course on data specifically. I mean, maybe adjacent economics or statistics. And in undergrad, I studied philosophy, politics and economics. You know, sort of like good pre-law. I did a little bit. I did a minor like urban public policy. So again, like there are these themes of like complex systems, like a city is a complex system. I went to Penn and West Philly, which was, you know, a city with the good and bad and, you know, how does crime interact and all those things. And so I really enjoyed that. And it's funny, though. And I think a theme for me is just, you know, you have to take the opportunities that come. It's not a linear path. And so I actually, my junior year in college, I spent a semester in Washington, D.C. And so you had classes down there that you were supposed to get an internship. And I had a couple of offers to, you know, intern on the Hill International Relations Committee or just more traditional things. And then choose some sort of random connections I had to offer to work in the national campaign to prevent teen pregnancy, which was very different. I think they paid, which was nice, but that wasn't the main driver. It was just sort of like, this is something really different, right? And so I'm like, oh, well, maybe I should try something different, not just everyone's going to go work on the Hill. This is an advocacy group, still very Washington based, tied into policy. It was one of the only men that I think were in the small office. And they actually were doing a ton of really interesting work around media, like working with Buffy the Vampire Slayer to send good messages around safe sex and things like that. But through that, I met a communications company in Philadelphia with a Wharton alum and started an African-American Wharton alum that sort of specialized in urban communication. So they did everything from like focus groups for like, I see these movies to public health campaigns. And so that's how they were connected to the national campaigns for pregnancy. And so, again, that's what happens, right? You take a chance, you do something different, you meet someone else. I worked for them my senior year. I went and worked for them full-time for a little bit after I graduated. And they had a small database system that they were using, right? And so I started using the data and understand their different contacts for like HIV education campaigns and all this stuff. And I slowly, and it's actually twice in my career, I left for a vendor, separated by 20 years, right? And so when I was 21, 22, I think it's sort of like that moment where like, when you start calling support and you know more than the support person, right? I just, I ate it up. I knew how to use the system. It was called MSAS, Member Service Action System built on itcher-based and Borland technology, which was very old technology, but powerful. And I was building reports and doing groupings and all the stuff you do with data, right? And so I ended up leaving, I think especially when you leave, you know, passionate leaders, there was definitely something when I was 21, there was some yelling between two founders of a small tech startup and a small communications startup and negotiations of how I would sell health, which is flattering. But so that's really how I got to data was this Euclid technology that had like an association management software. And I started using, you know, we moved from Interbase, which was sort of an open source database to SQL Server was like our big upgrade. And so I started learning how to build views and sort of procedures. And as a small company, you just, you needed to be scrappy, right? You couldn't afford to like, like Deloitte or someone to like, you know, just build people to make things bespoke every time you did it. And so, you know, I just started doing that and then, you know, it's, you know, 20 years later, I did the same thing where I was at Target and I was a customer of Domo and I sort of decided I had this vision for this practice around data curiosity and I made the leap as well. And I think a lot of it for me in my time at Target, too, I always talk about like, if you're a consumer of the technology, you end up pushing the envelope. And at some point you want to have a seat at the table and build bigger envelopes, right? And so I was able to do that at Target, you know, even within Target moving, I was originally in finance and then I moved over to more of the data analytics team. In between there, I got my MBA, met a girl from Minnesota, moved to Minnesota to get my MBA and then stayed here. So like, but I think that the big theme is, to me, is being open to new experiences, being curious, right? But not always being so linear that like I must do A, B, and C. I must be a data analyst at Google, then I must do this and I must do that. You know, I had to do A, B, and C to become head of product. Well, I didn't have a linear path to that either. It's like, do interesting things, meet interesting people. And the last thing is have really good leaders and bosses. I think I've been lucky over those years to have people I could trust that could protect me sometimes when I needed protecting that would, you know, encourage my curiosity and my exploration and my growth. And I think without those people, you know, probably, probably could count in one hand that was the people, but it makes a big difference. I would agree with that, absolutely. Did you know Dativersity offers free monthly webinar series and online conferences throughout the year? Stay in the loop when you follow us on Twitter at Dativersity or on Instagram at Dativersity underscore edu. Get podcast extras and bonus content when you subscribe to our channel at youtube.com slash Dativersity. And again, what a testament to you and your curiosity. It's not many people who would try those new things go, hey, I want to just do something different. I want to push myself. I want to explore. And that's a really great story to tell and a great way to approach it. Sometimes the universe is just sort of telling you something, right, whether it's the nudge because it was paid versus not paid or the fact that, you know, and fine, it's a target. I was doing fine, but it felt like I was always pushing, right, like sort of chafing against the technology. And so, you know, the universe tells you things and then things present themselves and you have to grab them. And if you miss them, you might end up on a much different path. You know, it's so true. So what is your definition of data and how do you work with it? Yeah, so thinking about this one, you know, I think and at the core to me, data is an observation, right? It's an observation of the world that has recorded somehow. And I'm often observing many things. Sometimes the things that I observe or notice my wife, I don't understand, why do you care about that? But whether it's, you know, how a restaurant is trying to organize or, you know, what's going on, you know, even how people are collecting data in the world. So, you know, some bathrooms have like the happy face, smile, you know, sad face. Is this clean or not, right? To try to get more data inputs. And so at the core, I think, you know, we walk through life with a lot of information around us. A lot of things happening. Some of that is recorded. Some of it's not. A lot more of it is recorded than it used to be. If you're thinking about cell phones or, you know, if I think about, you know, we have like life 360 to track our kids. My oldest is 15. His best friend just got his license. He wanted to go for a ride and I can look and see, oh, he went to Culver's to get ice cream, right? I mean, that's data that didn't exist for my parents, right? Or, you know, existed for like the Navy 30 years ago as a, you know, multi-billion dollar investment. And so we do have more and more of that data, which in some ways makes the job of working with data harder, right? And I think, you know, one of the inflection points for me at DOMO, you can actually, you can see, and if you look at the data of like what I created, like when I first joined DOMO, like I didn't, I created, but like I wasn't creating a lot of content, you know, around data at DOMO. And then when COVID hit, that really changed some of my approach in my direct, right? So we sort of had a SWAT team to create a COVID tracker and early in the early days, we're gonna, you know, tens of thousands of users every hour because we're compiling data from John Hopkins and other places we're updating more frequently and how do we blend it? And so that's a lot of that created those kinds of data experiences, right? Which I talked about for DOMO, but this was like a real relevant way to talk about what we did. And I think I learned a lot too of like, you know, relevant data that makes sense to people is a way to tell my own journey. It's a way to tell the journey of DOMO and what we do. And so we've gone on from, you know, using COVID data to inflation data to even, you know, when Taylor Swift had all top 10 songs on the Billboard charts, we did a blog post I did around the Billboard charts and had anyone ever done that before? And how do you look at, you know, past people and how many songs do they have there all using like a, there's actually a Python plugin for the Billboard charts, you know, anyone wants to do it. I have the code out on GitHub. But all of that to me again, that's sort of that need and we do this all on a DOMO and data blog. Like it does speak to like it is, there's information out there, there's observations. How do I make sense of it? How do I make it meaningful, right? Cause you could have data, there's lots of data. How do I make it meaningful? I think it's where it gets really powerful and interesting and where I get excited. What a great way to use data for, you know, during COVID and, you know, to make a difference. Yeah. So, Helen Ben, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years and why? So I think overall it will increase. I think it'll change though to what it means and how you do it, right? And certainly, you know, even in the last five months with ChatGPT and LLMs, it has changed a lot of how we think about what's possible. But there's still sort of that human element of how do you guide, you know, a ChatGPT or how do I use ChatGPT to give me code as a starting point? And then I make those last, you know, 10% of adjustments that sort of do that. And so I think there's so will be that human element. I think, you know, we continue to automate more and more. And so I think purely the collection of data or the pure management of data will, you know, and maybe, and who knows how it sort of, that could become more and more automated and maybe a little bit more simple, but it always has, right? I think it's like, you know, every year things get different and changes. But I think that challenge of, you know, how do I get value out of the data? How do I get business impact? How do I create an experience that everyone wants with the data will continue to be there? And that's part of where ChatGPT somewhat randomly, they didn't know. They sort of released it to the wild in November as like almost a last-ditch effort after some more bespoke efforts to train specific models for accounting or something like that. But why it's like, it resonates because it is so simple and so usable. And so I think finding ways to do that, finding ways, you know, becoming experts on how to prompt a large language model in a way that's responsible. How do you, you know, how do you get the right data out of it? How do you organize your data in a way that can be leveraged by a plugin or by a large language model? I think all of that is only going to expand. The people who actually can access it might change, right? So before you maybe needed to go to a data expert to access it. Now I'm relying on the data expert to help translate and mold and deliver it in a manner that I can use. So, you know, I might not need them to answer my question, but I need them to make sure that my question is answerable. That makes sense, yeah. Makes sense a lot. So then what advice would you give to people looking to get into a career in data management? Yeah, so I think there's a few things. I think one is, I mean, obviously be curious. I don't have to say that. But I think when I, certainly from a career perspective, it's thinking about how do you explore new technology? Think about what your approach is. That's something I ask people a lot. It's like, I don't care as much about which technology, but I want to know how do you learn, right? How did you learn something brand new? How did you change the way you did things? Because that's the only thing I know for sure is that they'll continue to be new technology that you need to understand, whether it's Python or R or GPT or vector databases or whatever it is. And so the more that you build that muscle and show to me, so well, I guess sometimes I'm hiring for an expertise, I more want to hire for someone who shows me they can adapt, right? And so if you've gotten really good at one technology but can never tell me a story about when you had to explore new technology from scratch, except for that one technology, look, there might be times when you need that or you need a specialist. But I think having that, it's not lack of specialization, but having that ability to pick up a new specialty, I think it's really big and being able to do that. And then look, I think the other thing, like I sort of said before is like, keep your eyes open for the different pathway. Like you don't know that linear path and keep your eyes open for who you're working with and for, because end of the day, like that's really what makes, at least from a career perspective, that makes a difference. And who are you spending time with? Who are you traveling with? Who are you in the trenches with that there's a big deadline or a project? And so all of that, it's really hard if you don't trust and respect the people you work with. And so I would pick certainly better people, more interesting problems over title and pay right away. But those things matter. We all want to make more money. We all want a nice title. It's nice, all those things, but I think you have to sort of balance between them. I agree with that. That's great advice. And along with your curiosity, it sounds like there's also some advice to be uncomfortable. It's okay to be uncomfortable to push yourself in new situations, new environments, new things. So which really great message. I think a lot of it, I often talk, a lot of the research actually around curiosity overall, and there's been Harvard, business review articles and stuff, like talks about the concept of intellectual humility. Right, and I think that's something I try to go on. And it's hard, because I know a lot. I think I know a lot. I think I'm right a lot, but sometimes you just have to make sure like you're letting out of your guard, you're questioning whether someone else knows more than you, right? Like I'm not always the opposite of intellectual hubris. I'm open to learning something new. I'm listening to someone else who might have a different opinion or a different approach. And it doesn't mean like you're perfect. There's plenty of times when I'm sure my team or my customers would tell you, I have exercised intellectual hubris in my interactions, but again, if you can check yourself and reset to that, I think it is that openness, the humility to be able to know what you don't know or to want to learn something new, because if you're not comfortable with that ambiguity, if you're not comfortable with that being humble, it gets really hard to learn, because like it's hard, right? It is uncomfortable, like you said. And so if you're not willing to do that, you're gonna sort of have an issue learning something new. Such great advice all the way around and not just career advice, I think great life advice. So indeed, and I can attest, I love my job and my colleagues and Tony Shaw is one of the best human beings that we've to work for. But we've all been there with those bad managers and not just you're right, it can make life miserable and it's so important in your choices. So and if you follow your passion, follow that was, that curiosity, like you say, the salary and type, most will come. Yeah. I believe so. Well, Ben, so I would be remiss though if I didn't ask how, if people wanted to learn more about demo, how would they find out? So you certainly can always find me on LinkedIn or email me your direct message me if you have questions or if you're a customer and your products feedback, I'm always, always open to that or it's ben.schian at Domo. But on our website, Domo.com, we actually did a lot of revamping at part of our user conference in March in terms of focusing around these data experiences, being clear around the architecture, walkthroughs of different parts of the platform and whatnot. The Domo data blog has some, if you wanna explore how Taylor Swift is doing now or Miley Cyrus had like some record of number one hits in a row or whatever. So all that is out there, but we're always looking for good data conversations and help people on their own curiosity journeys, right? What are they trying to learn? Oh, it's so fun. Well, Ben, thank you so much for taking the time to be with us today and to all of our listeners out there, if you'd like to come up to date on the latest in podcasts and the latest in data management education, you may go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. Subscribe to our newsletter for podcast updates and information about our free educational webinars at dataversity.net forward slash subscribe.