Cream City Calculation
Three friends talking about data and how it impacts our lives and the lives of others.
Cream City Calculation
Behind the Mic: Frankie Chalupsky
In this episode, Colleen Hayes and Sal Fadel interview their cohost, Frankie Chalupsky. This series is designed for listeners to get to know us better as well as learn our best practices.
Welcome to the Cream City Calculations podcast. We're three colleagues and friends that love data and to talk about how data is impacting our lives. I'm Colleen. I'm Frankie. And I'm Sal.
Sal:Welcome back to the Cream City podcast. We are continuing our series on getting to know the hosts. Today we're gonna talk to Frankie, understand how learned about analytics, developed her career in analytics and data, and kind of what interested her and then, learn a little bit more about who she is. So Frankie, kind of tell us initially maybe like a quick dive of your career path and how you
FRANKIE:Yeah, absolutely. So when I was in college, I had no idea what I was gonna do. I still like to say to this day that I still don't know what I'm gonna do when I grow up. I. And I am a grownup, so I still, I still don't know what I wanna do, and I never know what's next, but I just always, you know, keep putting one foot in front of the other and figuring it out as I go. So that's been my, my strategy. So when I was trying to figure out what I was gonna do next after college, I applied to probably, I don't know. A hundred different internships. It was an absurd amount of different internships while I was in school.'cause I just had no idea what they were. All these different business titles, I mean, they had no meaning to me at the time. So trying to figure out what, what internship was and what that entailed. And then also just trying to find one that actually paid you something rather than just working for free. That was my, my goal. So, yeah. Yeah. Right. And I ended up finding an internship at American Family Insurance where I kind of, I, I got this business title and I couldn't even tell you what it was. It was like the longest title I've ever seen. And what it really was, was a claims data analyst internship. But I couldn't even tell you what the title was. It was so convoluted, but I took that role and I really enjoyed it. I was really happy with it and I didn't know what to expect going into that job, but I had heard really great things about the company and was excited to get to, to work for a company like that. And it was close enough to home and all the good things, right. So, ended up starting off with, working with data and starting to use. Some of my mathematics background and figuring out claims, predictions, things like that, trying to understand, okay, with the weather coming, if we have, you know June, June through August, we have storm season in Wisconsin in particular, what kind of claim impact can we expect? Or if we know there's a big storm coming and we have a hunch, from the weather folks that. It's going to impact a certain area. What kind of claim numbers can we expect again for that? And that was really important for working with the actuarial team and understanding how much they should be reserving and things like that. So that was really a fun job for me and I ended up staying there for a couple more years and was just really fell into data and analytics at that point.
Colleen:You had mentioned somewhere in there about your mathematics background. Is that what your degree
FRANKIE:Yeah, so I finished my degree was, ended up being a math major with an actuarial science minor. I had considered going the actuarial route and then decided I really didn't wanna have to. Be told what to learn. And so going the actuarial route, I would've had to take like 10 exams and they're all set in stone of what you have to learn to pass them. And for me, I'm kind of like a, again, I'm flying by the seat of my chair, like I'm trying just. do what I wanna do in the moment. I'm not planning exactly what's gonna go on in my career, which is really the quite the opposite of what I'm like in real life. Like at home. I'm a big planner.
Colleen:So, yeah, I was gonna say, knowing you, Frankie, I feel like you are a big planner. Were you like that as a kid? Like were you a big planner as a kid too, or were you more fly by the seat of your
FRANKIE:I was definitely a fly by the seat of my pants kind of kid. I. Doing whatever. You know, when it came to sports, I didn't plan like what kind of sports I was gonna do. I wanted to do everything. And that is part of my character to this day is I always wanna do everything. And like when I'm learning a technology, I have a hard time acting as if I'm an expert until I've done everything and I know everything and I'm never gonna know everything. But, I did just kind of bounce around and just did what I felt like in the moment.
Sal:Do you think that, played, a role in your evolution of your data? Career is like being able to adapt and kind of have a more of a, I would say like a free spirit to data and where your career is mostly around every data set that you work with is always a little bit different, and so it gives you that flexibility of being more open to things. I would love to know if that, that helped you, and overall with understanding data
FRANKIE:Absolutely. It, it really did help me in my career and data is constantly changing and technology in general is changing all the time. So for me, like one I. I'm ready to, ready to learn and figure something out, and I'll, if I'm interested, I'll figure it out. And if I'm not, maybe I won't, I don't know. But I'll really dive into things and spend a lot of time figuring things out. And that has really helped me. The other piece that has helped me is that because I am, you know, just ready to go with the flow when things like AI came into the picture. I could dive into something like that and figure it out and start learning and, and both of you guys are like that too. And it is something that's kind of a necessity in a career path like that.
Colleen:I think it's really important to, if you're working in it in any way, to have that open mindset, to not think, oh, this new thing came along. That's not my job, but rather, Hey, I'm gonna check that out. That kind of sounds cool.
FRANKIE:Absolutely.
Sal:Has there been any like pivotal moments Of shaped your ability with working with data? Like,'cause understanding how data flows, how data is structured, it is that learning experience and learning new things that you wanna know a bunch, everything about it. But are there any like mentors that kind of steered you into the right direction of how to work with,
FRANKIE:Are you asking because you want me to say you?
Sal:No, I was actually thinking Chris, Patrick, but okay.
FRANKIE:I had, I really did have amazing mentors. And so after I was done working with American family, I went to continuous Technologies, which is where I got to meet Sal and Colleen and some other amazing people. And I got randomly placed on a company and it happened to be the same company that Sal was on. And then our other good friend Chris, Patrick, was on this company as well. And both of them were just amazing mentors. I could not say enough great things about both Sal and Chris. I was coming into an industry, into finance, and I had no knowledge of finance besides my actuarial background and insurance background. And so to come in and try to figure that all out and understand all the terminology, the calculations, all the things that go into finance and. It's a completely different game. And although I say that, working with data across industries doesn't really mean that much because you know, a calculation's, a calculation and a visual is a visual and we, we can figure out how to build'em. Finance is a beast. And so I had amazing mentors. Sal was really helpful in guiding me and into like understanding. All the different formulas and calculations. And then Chris was really hands-on and helped me with figuring out how to query the data and model the data visualize the data, all of those different things. So it was monumental in my career, I guess.
Colleen:That's very cool. That's great that you had those, those folks to kind of help you stretch your career skills and get you to that next level.'cause I know you're very good at
FRANKIE:Thank you. Yeah, and I would say like having mentors is one of those things that you'll never grow out of in your career. And I hope I never do. And, and if you find the right people, even when you move jobs, Sal and I have both moved on since then and we still are connected. And I have a question. I can go to Sal and if Sal has a question, he can go to me. And that's a really great relationship to have and something that will be monumental, for career building and career pathways.
Colleen:Yeah, absolutely. Can we just step back just a little bit'cause I feel like we're skipping over a really big part of your life. And Frankie you talked about your undergrad degree in mathematics, but I just wanted to call out that you've recently earned your master's
FRANKIE:Yeah.
Colleen:well, right? Can you tell us about
FRANKIE:Yeah, So going back for my master's, this was actually my second attempt at getting a master's degree maybe four years ago. I wanted to get a master's degree in analytics and it just wasn't a really good fit for me. I did one class and I didn't like the program. It was a Python class and I know Python. Decently well, and I was having a hard time passing that class, but ended up just deciding it wasn't the right time and maybe it wasn't the right program for me. So when I went back to school, I put a lot of effort into figuring out what the right program was. So for me, I needed something in person. My first one was online, and I just felt like I did not have any connections with anybody. I didn't. Know the professors and so I picked a small program where I was able to be in person and make those connections because that's just the type of person that I am and how I operate. So I went to Carroll University, which is where I got my undergrad as well. I went back to school there because it was just the perfect fit for me that had, 25 people in my classes. And I know my professors like. You know, our professors would, would go out for a drink after class with us. Like that's not something you always get with your master's program. But pretty fun that
Colleen:That seems like a.
FRANKIE:totally. It was just great to have relationships and I think for me that was really what having a master's degree was about and getting that master's degree was okay. I'm now at a point in my career where I can apply that knowledge and put it into my work. On the daily, but I can also grow my network a little bit more and get to know other people and work with other people.
Colleen:Mm-hmm.
Sal:That brings up like two really good things there. One is. In your master's program, how has that changed your thought on data? Now seeing it probably from a, master's level right? Or a, a business MBA of how executives might think through things and work with data. And then the other thing I was gonna ask you is like, now how, like, how important is that network that you've now created with this? have you seen. That community with within your MBA program kind of flourish
FRANKIE:Yeah, so I'll take the first question first. I had a class that was a business simulation course that we were competing against other groups within our class, and it was simulating a pharmaceutical company and growing that company. So I actually got to put myself in the shoes of the business decision maker and utilize the data. And this is gonna hurt so bad to say out loud, but. I loved the tables and I understand where people are coming from. Like when people are looking at visuals and tables, I understand the need for having a table, but I also understand the need for having something graphed out. So I had a completely different perspective when I was making these decisions and thinking about it than when I used to build the visualizations. And I used to be like, man. Why does everybody just want me to build a table? I didn't understand it, but sometimes you just need to see the number. Seeing the trend and seeing the number is different in my eyes now. So that was one thing that I took away that was pretty impactful. The other piece that I would say about that particular course is that I understand at a deeper level how data is just a tool in the toolbox, your decision can't always be strictly made upon your data. I mean, yes, we should be making data-driven decisions, but it was much more than that. We had to think about how are other companies thinking? And like, yes, we think that, you know, the market is gonna grow. That's what the prediction is from looking at the data. But what other companies are doing, are they focusing in on a certain market? Is are they focusing in on. Like France or the United States. Like things like that, that played into my decision. I also didn't realize just how much plays into your decisions when it comes to things like that. Like me and my team, we spent probably more time than I'd like to admit, just kind of going back and forth, trying to work through some of these solutions and figuring things out. And even though I'm a data expert. I just loved that having those conversations with my group. We all pulled different things from the data, so even the same visualization for all of us. We were seeing different things, so having those conversations when you are making data-driven decisions are gonna be really important too.
Colleen:It's cool to hear you say that, that you kind of saw the perspective from that side, and I guess that's really the point of doing something like a master's degree is to get that insight and that intelligence that, you wouldn't have had a way to get that perspective otherwise,
FRANKIE:absolutely. And then Sal, to take your second question, I have really seen my number has increased drastically just from being even in a small. Program of, of master's education. But I really enjoyed seeing those people flourish too. Now that we're all connected on LinkedIn and whatnot, it's seeing them grow in their careers and making big moves. And although I haven't, I'm utilized this network too much yet, it's a small, a smaller network. And more recent, I haven't had a chance to utilize them in finding a role or anything like that. I still feel really satisfied, seeing them growing and finding new roles and people are coming out of their master's degree with new opportunities and well-deserved opportunities.
Colleen:I suppose it probably feels like it matters, right? Like what you've done, the work that you've done really matters and really is impactful to, to the. Real
FRANKIE:It does. Yeah. And I, I would say too, like when I did my bachelor's degree, it was like. I just need to get through this. I just need to do it and we need to be done. And I maybe didn't, I didn't put my full effort into it because I was also trying to work and do school full time and it was just trying to scrape by and get through it. But the different perspective on the master's degree is that I wanted to be there. And I wanted to do it. And I think that also had a really big impact on getting through it. And I wanted to learn. And although yes, I wanted to learn when I was in college for the first time, like my bachelor's. You're, you're really just wanting to get out so you can start making money and have a job and like, you know, start life, right? Whereas the second time around, you're already doing life and you're in it and you've got a career and you're just applying those skills instead of just learning them.
Colleen:I remember very much that feeling too. And, and I have a son that's gonna be going to college later this summer, and I'm, that was one of the things I said to him was, I want you to like fully be part of this. Like go have the full college experience.'cause I remember, I. When I was in college feeling very much like, let's just get this done. Like, where's the next step? When am I gonna actually be making money? When am I actually gonna be doing something meaningful? So, that's, that's good perspective that you had this, this time around. I.
Sal:I would love to kind of dive back into now you've had a career, you've worked at data quite a bit, and you've kind of developed your career and who you are. Do you see, like you as when you were a kid, like little traits of like, oh, I had that skillset when I was a kid and I and now I'm using that. Like, and, and obviously it matured, but are there things that you remember as a kid of in like, oh, I always did this or did
FRANKIE:So that's a really good question Sal, and honestly, like going back to. One of my very first core memories as a kid was when I was in kindergarten. We were in a private school and so we were working on like adding and subtracting in kindergarten, which is maybe an issue that was probably a little advanced for a kindergartner, but. I was having such a hard time with figuring out, adding and subtracting, and I remember this, this particular day where when we were done with our worksheet, we got to go and play for a little bit, and I remember being. The last person sitting there trying to figure out the adding and subtracting and watching everybody play while I'm just like, I have no idea what I'm doing or what I'm doing here, or anything like that. So that's like one of my core memories where I was a terrible math student in kindergarten. So fast forward, obviously I ended up being a math major and it, everything was fine, but even like all throughout, my, younger days I was in a lower level math when I got into middle school.'cause we had to take a test to see where we placed and I placed in a lower level. So I ended up struggling with math and struggling with that. And when I went to high school, I even struggled with math there. Even though I went into more advanced courses at that point and was doing better. I was still struggling and I took calculus for one semester in high school and then graduated early and went to college and I took it again. But the first time I took calculus, I had no idea that stuff was crazy. And the second
Colleen:Mm-hmm.
FRANKIE:it and it was all like me. I think figuring out my learning style and my learning pathways. And when I took it the second time and I, I like, went to our supplemental instruction and got extra help at Carroll it was so great and I ended up being a calculus tutor myself. So just navigating that and understanding that, it's funny just because I was not like that as a kid. I didn't figure it out until I was an adult actually.
Colleen:Yeah, but, but what a
FRANKIE:Yeah. Yeah. And it was just, just navigating and, and trying to figure it out was an entire, I don't know, 18 years, right? But yeah, once I set my mind to it and really applied myself and found the ways to learn that worked for me. It worked so well.
Colleen:I mean, it, it speaks to like, you know, never giving up, right? Like you. Originally had such problems with math and to be somebody who goes on to tutor other people in calculus, like what a huge range of growth that is. And if you had just been like, screw it, I hate math. I'm not doing math. Or let somebody tell you you weren't good at math, you would've never gotten to the place where you are. And I think a lot about like people's learning styles. Like I have one son that's got a DHD, and he had a real struggle. For him, he showed lots of signs of being very, very smart. He just learned in a different way than the other kids. He had issues with like focus and he had to learn, I need a certain environment when I'm studying or taking a test in order to be successful. And I think that goes a long way toward, you know, helping you learn those skills for the rest of your life. So I'm sure those. Things that you picked up, your study habits, your perseverance, the way that you went to additional resources to get help, and you never really took no for an answer, that's probably really served you very well in your career in lots
FRANKIE:Yeah. Yeah. Thank you. I, I appreciate that. It's a really nice compliment. even as a senior in high school, I had a teacher as a senior, my math teacher, when I had told him that I was interested in going to school for math, and I was specifically looking at actuarial science at the time. He told me I probably should look at something else, and I was like, you know what? No, I'm not going to do that. And I mean that particular story was kind of what drove me through finishing that math degree. Like I never wanted somebody to tell me I couldn't do something
Colleen:So you got your
FRANKIE:like, you know what, in a way, yeah, I did,
Colleen:I'm just kidding. But you know,
FRANKIE:I always really liked math, even though it was challenging and I, I just really enjoyed it and so that's what I ended up doing was just a generic degree so that I could figure out what I wanted to do after that.
Colleen:Yeah. But think about how many of the greats had those stories of how many times they got cut from the team, or how many times their, their book or their movie script got turned down or turned away, or how many times they didn't get hired for the job. And if they had just stopped there, we would never know of their
FRANKIE:Right.
Colleen:know?
Sal:Yeah, I think perseverance is one of the best traits a person, and that's gonna drive their success typically.
Colleen:Yeah, absolutely. That grit like of being like, Hey, for, I don't care what you say. You can tell me I'm bad at this. I'm gonna get good at it.
Sal:so we got to know a little bit about your past and now we kind of wanna learn about what you're currently doing. I know you're working for. A cloud service won't get into the name of this of the company and but I would love to know how your history of what you did is now developing
FRANKIE:Yeah, so when I was at continuous, I got to learning about one of the cloud technologies and. I started learning it and I fell in love with it. I thought it was super cool. There's so much that you can do with, with having your data in the cloud and these different platforms and services that are provided these days, and when I got an opportunity to go and work there after learning the technology, I was like, you know what? Let's do it. Like, let's, you know, try something a little different. I'm now in a solution engineering role. So I'm kind of helping other customers figure out how they're going to use the platform and guiding them through that, answering any questions that they have, maybe like challenging some of their visions when I have, previous experience that might say otherwise. It's a cool opportunity and I've actually really enjoyed it. It's been about six months now. That I've been in this particular role, and it was great for me because I used to be really focused in on Tableau and that was my majority of my skillset. And when I got that opportunity to grow and learn this other platform and do more of the, the data modeling and querying and things like that, it's been great for my career because it set me into something that's new and coming. Whereas like Tableau was kind of on the outskirts of that. Most people like have heard of Tableau and they've worked in the visualization tool or some sense of it. But now I feel like I'm doing something that's, that's gonna be monumental and getting to learn more about AI and instead of catching customers up on what's going on. It's, let's push forward instead and let's get ahead of the game and ahead of other companies because we wanna be cutting edge.
Sal:Just knowing the company that you work, work at and where you kind of came from. How, like you came from more of the visualization end or the consumer end of it, right. of data. Now that you're in more of that storage kind of manipulation, ETL side of it I would love to know your perspective versus other people that have come from more of like a, maybe an architect background or some computer science background that know the infrastructure but not really know the consumption side. How does that change your strategy of working with, with
FRANKIE:Yeah. So what's changed the most for me from moving from vis to like cloud services more generic, is that I have gotten to grow my, that skillset drastically. Because yeah, I was very focused in on one aspect of a cloud service platform, and that was analytics. And now I'm at a point where I need to know. The like how to be an architect, how to be a data engineer, how to still be an analyst, how to be a business user, like all these different pieces. And that's something that I didn't quite have before in my last role. So I've had a lot of time to, like, they, they had a really good ramp up program where I was able to do like a capstone project and figure a couple things out. So I needed To learn how to connect to an S3 bucket and how to work with data bigger than I had ever worked with. So it's been a lot of diving into documentation, doing my own projects, figuring things out, and just tinkering, right? The best way that I learn in particular is by doing. And so for me, I just needed to go in and, and start practicing. And that's been, the biggest change going from like that one focus to having a broad focus, googling is such a, an acquired skill. Like you don't even, you know, like you don't even know sometimes what the customer is asking. And so you've gotta figure out what they're, what they're really asking for, and then you need to figure out how to find it. And really, Googling is such a great skill to have and, and you know, knowing what to search for and knowing those key terms when you're gonna use AI is also super important.
Sal:I was just gonna ask that is like, do you see AI changing How you Google and how you review your
FRANKIE:it already has.
Sal:Like is it a, a starting point? Yeah.
FRANKIE:I would say from when I started, I would've been, and we have some approved technologies, but like, I'll just, when I say chat, GBT, I'm usually like actually meaning Gini because I can't stop saying chat GPT. But that's not bad.
Sal:Kleenex. There are
FRANKIE:chat, TBT to me.
Sal:close. Kleen.
Colleen:that's.
FRANKIE:But what, when, yes, when I use technology such as that, I'm trying to figure out the best way to prompt it and how to get it to, to do exactly what I want to do. And a lot of the time, like when I'm asking it questions, I have to ask multiple questions to get to that point of getting it. To understand what I'm looking for, and I don't think that's unheard of at all, and I think I'll get better as I go with figuring out how much detail I need to add into my prompt. But the more detail that I can be usually the less number of questions that I need to ask to get to what I need.
Colleen:Yeah, this is like second time in two days that I've had conversations about prompt engineering and about how important it is to really fully think through what it is that you're asking for, because. very black and white, right? This is not a person that can infer from the inflection of your voice or from what you're saying, what you're looking for. This is just computer code that's gonna spit out other computer code back at you. And so it makes me think of that. You ever hear of the exercise where you ask a person to describe how to make a peanut butter and
FRANKIE:Oh yeah.
Colleen:You ever. Yeah, where like you don't think about how many steps that you take as like a human individual just making a sandwich, taking the bread out a bag, you know, spreading the peanut butter. Like if you don't describe those things, that chatbot is not going to know that they're part of the procedure. And in case anybody hasn't heard of this thing, it's usually a funny exercise where like, students describe. a peanut butter and jelly sandwich, and then the teacher follows the directions that the kids have written out. And it usually is like something that doesn't even resemble a sandwich in any way, but because people forget to put in every single step that they're taking while they're said sandwich. But I think that's a really hot topic right now, this prompt engineering. And how do you help your end users who may not be as technical write? Prompts that are gonna get them the information that they need or that they're looking for.
FRANKIE:Yeah, especially when you're thinking about coding specifically, how can you get your end user to put into words what they're trying to do with that query? That's, that is a really difficult thing to do.
Colleen:Yeah.
Sal:So. A little bit of the future, right? I'd love to know kind of where you think your career is going or where you want where you hope it's going. I'd love to kind of, if you're forward looking at, at, at all. I'd just kind of love to know a little
FRANKIE:Yeah,
Sal:that.
FRANKIE:you know, as I referred to before, I always say I don't know what I'm doing yet, and I don't know what I'm gonna do when I grow up. Because I think, leaving your career a little bit open-ended is a really great plan because you just never know what kind of opportunities are gonna arise, and you never know when you're gonna rise to the occasion. I didn't think that I was gonna make a move to be a solution engineer. I didn't even quite know what a solution engineer was. And now that I was presented the opportunity and decided to jump in. I love it and I, I think it's a really awesome career path for me personally. So given that I'm only six months into this particular role, I imagine I'll spend a decent amount of time here. And since I do love it so much and love the, the different opportunities that I'm getting to learn right now, I think down the road. And part of why I did take this position is that I'm trying to get more into the business side of things and. I know so much about data and I can use data to make those data-driven decisions, but I'm wanting to have those opportunities to make decisions and start to think more, and use my critical thinking skills. So that's, I think, like what my overarching goal is. But as for specifics, I have no idea what my next title would be or what I'd want it to be. You know, maybe down the road. Being in like a C-Suite position would be cool. Maybe, I don't know. CEOs get a lot of hate these days and I'm like, I don't know if that's what I want.
Colleen:Yeah, but I think it's, it's sufficient to say that, you'll be following AI trends in your current position as well as probably whatever you do next. Is that true?
FRANKIE:Yeah. I think with AI being as forward thinking and as a hot topic today, that's something I think I wanna ride the wave of a little bit and be a part of, make some waves myself. With that, I.
Sal:That brings kind of two question me. One is. For people that are wanting to ride that wave. Right. You're, you're in it. How do you suggest starting to take that on. And then the second one is, is what trends do you see? Like ai, we obviously all know AI is coming. Is there any other trends that you've seen kind of throughout your career that like, Hey, I think it's gonna go this way, and kind of have your insights?
FRANKIE:Yeah. So for the second part, I'll tackle that before I forget what I'm thinking. So I think, in the past we've been so focused on all these visualizations to get customers or our business users into a self-guided approach. We want our customers to be able to, work with the data and ask and understand whatever questions they have of that data. So we've always been like building out these visuals, trying to meet their every need. And I think that that's gonna go away. And I think that with AI and being able to have these chat bots created, business users are gonna wanna be able to ask it any question. And if we can build that on top of our company data and keep it protected, our business users could ask those questions. They could ask that to build out a visual. There's so much that you can do and you can almost eliminate some of those visual roles because you can enable your users to use AI and be able to answer whatever question they have on their mind.
Colleen:I.
FRANKIE:as for getting into AI and being able to be a part of that wave and make waves yourself, the biggest part in my eyes is having the interest and having the drive to learn. If you can go and. Find some YouTube videos and some series that you really like or read a book about it. Find somebody that you are seeing value from and just listen to what they have to say and start to develop your own thoughts and opinions on it. Go and test some things out, get a trial account through a cloud provider. And just see what that looks like write some Python code with some fake data or even find some data online using a free data website. Make a project and if you can just go through and do that, you'll have so many job opportunities. Like AI is such a huge topic right now and. People want AI engineers. So if you can figure those skills out or have a a degree that says you've figured these out, that will be impactful.
Sal:Before we wrap up, I, I have one more thing here. It's around with AI and your thoughts on, I think it's hard for people to get started right outta college. How, how would you suggest kind of getting started and kind of developing your career? Because like the job market's a little tougher now. And just getting into it.
FRANKIE:Yeah. So for the people who are coming out of college I think you need to have some sort of project put together that can showcase that you know what you're talking about. There are so many times where people come into the room and they interview for a role, but they bring nothing to show that, yes, I have done this and I can do this. You can talk about it, and that's great. But you need that like physical project that's, that maybe it's a piece of code or a visual that you've built out or something of the sort that just shows that you really know what you're talking about. And that's the piece that people are missing coming out of colleges. They don't have a a project put together showing their skillset.
Colleen:Yeah, I almost think of it like an artist
FRANKIE:Yes.
Colleen:Yeah.
Sal:Yeah. I mean, that's really what it is now. It's,
FRANKIE:Mm-hmm.
Sal:you gotta build a portfolio.
Colleen:Mm-hmm.
Sal:Awesome. I, I think that's a wrap on our episode of Behind the Mic. A huge thanks for to Frankie for sharing her journey. Kind of how she navigated the analytics world, data world and her career was really insightful. And if you wanna get a hold of Frankie or connect with Frankie find her on LinkedIn well. and then until next time, keep calculating.