Welcome to episode #063 of the Super Data Science Podcast. Here we go!
Today's guest is Aspiring Data Scientist Erika Dorland
As a beginner in the field of data science, you may be wondering how to get in and keep up. Tune in to hear Erika Dorland talk about all the ways she involves herself in the data science community and continually keeps herself updated on the evolution of this field.
Erika also shares her interesting story of how she changed careers and even her entire mindset and attitude about learning mathematics as someone from a liberal arts background.
We discuss a broad range of subjects, including the good that disruption can bring, and the benefits of being involved in the community of data scientists.
Broaden your worldview with this episode now!
In this episode you will learn:
- Why Mathematics? (10:38)
- The Way Data is Changing the World (14:44)
- Ways to Keep Up With Data Science (17:10)
- Women in the Data Science Community (25:03)
- Philosophy Terms in Data Science (30:07)
- Importance of Communication Skills (31:55)
- Disruption and Change (44:20)
Items mentioned in this podcast:
- EMC Analytics Big Data Science Textbook
- Who Moved My Cheese?: An Amazing Way to Deal with Change in Your Work and in Your Life by Spencer Johnson
- Learning to Love Data Science: Explorations of Emerging Technologies and Platforms for Predictive Analytics, Machine Learning, Digital Manufacturing and Supply Chain Optimization by Mike Barlow
- Talk Like TED: The 9 Public-Speaking Secrets of the World's Top Minds by Carmine Gallo
This is episode number 63 with aspiring data scientist Erika Dorland.
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Welcome to the SuperDataScience podcast. My name is Kirill Eremenko, data science coach and lifestyle entrepreneur. And each week we bring you inspiring people and ideas to help you build your successful career in data science. Thanks for being here today and now let’s make the complex simple.
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Hello and welcome everybody to the SuperDataScience podcast. Super excited to have you back, and today we've got an inspiring guest, Erika Dorland. Erika is the business development executive at Brilliant Data, and if you're following this podcast, then you will remember that a couple of weeks ago, we had Randall Scott King, who is the Managing Partner at Brilliant Data. And Randall was sharing his insights about Hadoop. Well today, Erika is here to talk about how she is breaking into the space of data science, how she is learning about data science. And Erika's journey is extremely inspiring because Erika is not only a mother of two toddlers, and she finds time to learn about data science, but she also comes from a completely different background.
She comes from a background of arts, and so as you'll hear from the podcast, she never actually never got along with mathematics when she was studying it back in high school and college, and therefore her journey is a great example of how you can become a data scientist even if you're coming from a completely different background. And also you'll get some tips on how you can leverage your unique strengths when it comes to data science, whichever background you're coming from.
So prepare yourself for a very relaxed, casual-style podcast. Prepare yourself to get to know our guest Erika a little bit better, and you'll get a lot of value out of this episode, especially if you are just starting out into the space of data science, or if you're stuck somewhere in the space of data science, and you need a little bit of extra inspiration and motivation. And without further ado, I bring to you aspiring data scientist Erika Dorland.
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Welcome to the SuperDataScience podcast, everybody. I've got a super exciting guest today, Erika Dorland, an aspiring data scientist. Erika, welcome to the show. How are you going today?
Erika: Hello everyone, I'm doing well, thank you Kirill.
Kirill: Fantastic to have you on the show. A couple of weeks ago, we actually had your boss on the show, Randall Scott King, and he was sharing information about Hadoop. Tell us about what happened there. So you got in touch and you actually recommended Scott for the show, is that right?
Erika: I did, yeah. My husband and I have actually been fans of yours for a while, so I immediately thought I wanted to get Scott on your show. So I just took the initiative and reached out.
Kirill: And it went really well, it was a great podcast. Now we have you on the show. It's great to have you here, and I'm really excited to chat about this. So you work in the same company as Scott, right? Brilliant Data.
Erika: Yes, exactly. We've been together now working for about two years – oh, maybe a year and a half now.
Kirill: Ok. Awesome. And how did you initially start at Brilliant Data?
Erika: It's an interesting story because it was just after I had my second child. I was really exhausted and post partum, and just not sleeping at nights, and I had just left my last job, maybe 3 months prior to that. So only a 3 month gap there. But I was VP of Marketing and Sales with an international telecommunications company, and then I just focused on being a mom for a little while, but I was just focused on trying to survive every single day without sleeping, with diaper changes and crying, and I finally got away one morning and went to my parents' house to take a break. And my husband watched the kids while I was away, and my sister was there, and she offered to take me out for a cup of coffee at our local Starbucks. So I went with her, she bought me the cup of coffee, and I sat down at one of the chairs, and I just happened to start talking to a guy there, who started talking to me about Big Data and data science, and at the time, I had very little knowledge about what any of these things meant.
I'd heard of Big Data, but I didn't know any details about it, really. And so he started talking to me about it, and then he mentioned that he's looking for an assistant, and I just said, "Well, you know, I'm here! I'm looking for a job." And so it turns out that was Randall Scott King, and we've been working together ever since.
Kirill: Fantastic! And actually got told that story to me, I think before you were even on the podcast, or before the podcast, and yeah, it was fascinating. And now I find out it's actually you, you are the assistant that he found.
Erika: I am that one, yes, I am that one that he mentioned.
Kirill: Such a random story!
Erika: It started off as me just working as an assistant because it appealed to me at the time. I could still be home with the kids and work part time, but eventually, I found that the blossoming love for data science. And if you listen to his podcast, every time I talk to him is like getting another Master’s degree. He has so much information all the time. I’m like, “You’re going to have to hold that, let me get my notebook,” you know. I can’t keep up with it. (Laughs)
Kirill: Yeah, that’s for sure. I learned so much from his podcast myself, it’s insane.
Erika: Yeah. And he does a great job talking about really complex IT and business issues, but telling you about them at a level where you are, and not in a condescending way. So I’ve learned so much from him and because of that, because he instructs and takes his time to actually explain everything, I found that I just love this space of data science so eventually I moved on into more of a business development role and then as I was working in business development, I told him, “I just can’t help it. I have to learn more about data science. I have to get my hands on the data. I have to learn. And I was like, “Do you mind if I use part of my time to learn? Is that fine?” And he was like, “Absolutely!” He sends me classes, you know, I take these different classes and he gives me books to read and he really fosters my education. I’m so appreciative for that.
Kirill: That’s so wonderful. So you started off at Brilliant Data as an assistant and then you moved into a business development/sales role. We’ll talk about that in a second, but originally you came from a completely different background. That’s what I find so fascinating about your story. You had no relationship to data, to mathematics, to physics, to any of that. Tell us a bit about your background. Which area did you come from? Which education did you come from?
Erika: I am heavily, or have been heavily, entrenched in liberal arts. I got my Bachelor’s degree in English Literature. I pursued my Master’s in Religious Studies, the philosophy of religion. You know, as I look back, but also as I was taking the courses, I always knew what I loved about both of those studies, of English literature, and of religion as a philosophy, was the analysis. I loved to analyse the literature down to the minutia. “Why do they use this word in the sentence at this time in the text?” That goes also into religious beliefs and philosophy, you know, “What does it mean about the human mind, the human condition, that we have these mythologies, we have these philosophies behind us?”
So I have just always really been in a hot pursuit of understanding humanity. (Laughs) It’s always been a passion of mine. So I think that translates very well to data. But I really was not involved in mathematics very much at all. I mean, it’s hard to say, because I was one of those kids — when I was in the public school system, I skipped a lot of classes, but I skipped classes to go home and teach myself something, so I taught myself French — I used to rent books, because back then you had a library. You go to the library and you get whatever they had and I would rent books on mathematical philosophy, like Pythagoras, sacred geometry and things like that. I love the philosophy behind mathematics, but in classes I could not get my head around how they were trying to teach me math. It just didn’t appeal to me. And I think there’s a lot of reasons behind that. You know, I’m not trying to blame the education system, but I think that you kind of mature into different stages of your life, and different things appeal to you based on wherever you are in your life. And maybe at the time, mathematics did not speak to me, but I remember in math class in high school I was just doodling snowmen. (Laughs)
Kirill: (Laughs) That’s what you do at mathematics, right? You draw snowmen.
Erika: Right. Well, because for me, I always had the question of why. I always had that big why. Why are we learning this? And I felt like English, history, the arts – they always spoke really well to that “why”, but I could not get a good answer as to “why” for math. And I actually remember in one of my high school classes I raised my hand to my teacher and I said, “I’m not trying to be obnoxious. I really just want to know why do we need to know this?” And I forget what we were studying at the time, but I just wanted to know why. And she — God bless her, being put on the spot like that by a high school student, she said something abstract about, “Well, if you ever work on cell phone towers, you’ll use this.” And I just thought, “Okay, I’ll never work on cell phone towers, so I’m back to my snowman. This one’s got a straw hat. This is great.” (Laughs)
So, yeah, it just didn’t really click, but it actually came about later on when I was getting my Master’s that we talked about different mythologies. There are so many complex understandings of mathematics throughout ancient religions, and even into obviously modern day Hinduism, as our oldest recorded religion. And they have such a complex understanding of time that it blows your mind.
And from there we started to learn about — I mean, I started to look into actually about what you can find, how you can find mathematics in the world around us. I discovered the Fibonacci sequence, and that nature really expresses itself in math, you know, you find sequences and patterns in math. So I remember hearing at one point that if there is a God, he would express himself in mathematics. And then I also heard a little bit later on that if there was an alien race that tried to contact us, they would probably not speak English. They would speak mathematics. And it just dawned on me all of a sudden that I’m illiterate. I don’t know any of these things. And that bothered me and I had to look into it. You posted something on a “Five Minute Friday” a couple of weeks ago, I think, about the nature of reality. You suggested a TED talk – Donald Hoffman, I think.
Erika: He explores this idea of what is the nature of reality and he addresses something that hit me too. That we have these visual representations of reality, or truth, or whatever, around us. You know, they’re kind of like shortcuts to information, like “This is a snake. Be careful.” You don’t need to know all the genetic code of the snake, or how that snake feels that particular moment, that particular day. All you need to know is, “this is a snake so be careful and back up. It could be poisonous.”
In a way, that makes us blind to the depths of reality. And that was another thing that really hit me, is that I also feel oddly blind and oddly illiterate at the same time. So me being the lifetime student I am, I had to proceed and I want to learn more and more.
Kirill: Okay, wow. Cool, so you have your answer now. So you need mathematics to understand the depth of reality and to speak with aliens in case they come here.
Erika: (Laughs) Right, right.
Kirill: So you got your why.
Erika: You know, short-term goals. Also talk to God. Yeah.
Kirill: All right. Fantastic. Now let’s talk a bit more about Brilliant Data. You were an assistant and now you’ve become a business development executive. What exactly do you do? Because I want to get to the why behind why you’re learning about data science. It’s not directly required for your role, but nevertheless you’re pursuing it. So let’s start with what exactly you’re doing as a business development executive at Brilliant Data.
Erika: So, I see it as I create — I look for relationships and opportunities. That sounds like something you hear salespeople say a lot, but it really is true. I really do look to establish relationships. People have real significant problems on their shoulders, business problems, a lot of the time with the kind of clients we deal with, and they need help finding solutions. So I work through LinkedIn or different social networking events to reach out to people, to talk to people, to find those relationships, but then also to find opportunities, to find out where data science is projected to go, where it’s trending, where there might be unexplored opportunities that no one else is really looking into yet. So that’s kind of what I do. It’s a lot of research which I also love about it. It’s not just trying to sell something to someone, which is not something I would be interested in. It’s more about reimagining what we can do together, I guess.
And that’s really the why behind data science for me, is that it explores the creative edge of humanity right now. It really is redefining how we are as a society, how we’re going to look, how we do business, how we interact, how we understand each other, and those are big things. I mean, we’re able to look at where there could be a flu outbreak before it even happens. That’s amazing stuff. We’re starting to talk about medicine being more customized because of data. No more is it going to be one pill for everyone, now it speaks more to your individual makeup. I think that’s amazing.
Kirill: Yeah, that’s really cool. And I totally agree with you that the way the world is changing with data is really fascinating and it’s fun at the same time. And just before the podcast you mentioned that in your role you get to speak to a lot of the executives of these companies that are pretty much driving change in the world and you get to talk to them to understand their pain points and see how Brilliant Data can help them with those pain points. Do you find that you need the data science acumen in order to have those conversations? And the reason I ask is because a lot of the times executives don’t have that knowledge themselves, so I would assume that you might not really require data science knowledge to be able to have those conversations. But nevertheless, you are pursuing these extracurricular activities to learn about data science. Can you tell us a bit more about why?
Erika: Yeah. I think part of it is always my drive speed, over-preparing for something. But then also there was a really great conversation that Scott, the managing partner and I had a few weeks ago with a client. This client was thinking about hiring a full-time pricing analyst. I had not even questioned that, but Scott immediately said, “Well, what about an algorithm? Have you considered running an algorithm instead of getting a full-time employee?” and I was like, “I don’t even know what that means.” (Laughs) I mean, I do know what that means, I understand what he’s saying, but I would never have thought to suggest such a thing!
Business is changing. Right now you’re seeing a lot of CEOs who struggle with the data science knowledge, but time and time again, and I’m sure you’ve seen it, they’re publishing article after article that if you’re going to keep up, if you’re going to keep your business relevant, if you’re really going to be on the cutting edge of business, the bleeding edge, whatever you want to call it, you need to know your data, you need to be involved in data. So right now, we’re at this point where people are kind of familiar with data and maybe kind of ignorant, but that’s going to increasingly change and that’s something else that a knowledge in data science is doing. They’re saying that in the 80s and 90s, if you had a marketing sales background, then you were on track to be a CEO. And now it’s like if you have a data science background you’re on track to be the head of a company, you know, you’re on track to be the next breed of entrepreneur. So I think it’s changing, it’s shifting.
Kirill: That’s really cool. I love that description. That’s in theory. Is that exactly what you’re seeing when you’re speaking to these people?
Erika: Oh, yeah. They’re getting more and more versed in their data.
Kirill: So you have to keep up?
Erika: Well, no. Believe it or not, I actually have a richer knowledge sometimes of data than they do, but I can tell they’re setting, they want to know. They don’t want to be left behind. They don’t want to be taken advantage of. They don’t want to just be blindsided by a trend. These are usually very sharp people. These are smart people and they want to be on the cutting edge of something, so they’re studying and they’re trying to talk to their team. Yeah, I mean, I don’t want to be left behind, I guess is how I say it.
Kirill: Fantastic. That’s such a good description. I know that we have about 10% of our listeners who are either business owners or executives or entrepreneurs, and I think this is a challenge to them. So if you’re from one of those groups of people and you’re listening to this podcast, then that’s a challenge to you, how are you keeping up with your data skills? Thanks a lot for sharing that. That’s wonderful. Tell us a bit more about how you’re going about your education in data science. What kind of courses are you taking? What books are you reading? Where are you getting this information and knowledge to keep up with data science?
Erika: I am sort of constantly — actually it’s something I try to say, because sometimes I’m so exhausted by how much information I take in and I try to reframe that in my head and say, “I’m not exhausted. I’m absorbing.” So it just reframes that issue and it empowers and sort of demotivates. But I do a lot of things because data science is an emerging field. Even the most experienced data scientists, there’s not a full understanding of what a data scientist is still. It’s like everyone wants to put on a bunch of roles and a bunch of hats onto what it is to do data science. It’s still such a new field and it’s such an emerging field that it can go in lots of different directions and we’re still trying to figure all of that out.
Yeah, I take specific courses like Python, I’ve signed up for your Python course. I’ve done Tableau. I’ve reached out to some Tableau Zen Masters because I want to create that relationship and I just say very humbly, “Would you take a look at my work as I complete it? I would love to have your thoughts and any feedback you have.” These are the things I do. I get involved with the people, I get involved in the courses, I study, I read, I have books—do you want me to give a book recommendation?
Kirill: Let’s do that at the end of the podcast.
Erika: Okay. But I do have a textbook that I keep on me constantly and actually, when I can’t take any more thinking and I need to do something active, I will go to a local track with my textbook and I’ll walk around reading. And I get complimented for how I can walk and read at the same time.
Kirill: Hold on. “Track” as in, like, running track?
Erika: Yeah, right. I will walk and highlight and read at the same time.
Kirill: Hold on. “Track” as in, like, running track?
Kirill: Oh wow. I hope you don’t bump into anything.
Erika: I guess that’s like a Miss America talent I can provide some day, walking and reading. So I do that, but I also stay up-to-date on all kinds of things. I read the Atlanta Business Chronicle morning and afternoon over here to know what’s trending in Atlanta. Atlanta right now is actually the number three tech city in the United States. So I’m honoured to be here, I’m honoured to be a part of that community.
I was actually at the Georgia Technology Summit a few weeks ago and it was amazing, the talent that I found and the people that I spoke with. And that’s another thing I do, I get involved in in-person activities. So I do a lot of those networking things. I follow the Atlanta Business Chronicle, I stay up-to-date on LinkedIn, I follow people who are data scientists, people I admire. But I think that when you’re in data science — the way I see it is that you’re either solving business problems or human condition problems. That’s kind of where I see it if you’re going to compartmentalize, that’s kind of where I see it right now. Or even doing education, I guess.
So you have to kind of read into all those camps because it’s all fleshing out into a new reality for all of us. Yeah, it’s a lot to absorb. It’s a long answer to your question, but that’s because it takes a lot of education. There are a lot of things that I do to stay up-to-date and to learn.
Kirill: No, I totally appreciate that. I like the enthusiasm and the passion that you’re sharing. I think a lot of people should get inspired by that. A lot of people limit themselves to doing just one thing, doing courses or reading a book or even listening to this podcast, but it’s a very multifaceted thing. There’s so many things going on. There’s events, as you said, you can follow people, you can reach out to people, you can learn through courses, you can read books and walk around on tracks at the same time and do lots of interesting things. I think people should get in on that more. Tell us about how you feel about your progress. You started Brilliant Data about nearly two years ago. Since then, how do you feel that you’ve matured in the space of data science and how you’ve learned new skills?
Erika: I’m very pleased with it. I did very amateur-style versions of Tableau thanks to you, Kirill. (Laughs) So I know how to do some of those things. I have learned about Linux, which is really not something I’ve learned about before. I mean, I was an 80s child, and you kind of couldn’t have a computer in the 80s without knowing a little bit of coding. It was just kind of the nature of how — if you even played a game on your computer back then, you had to type in commands and, you know, it’s just how it is.
But now I’m learning about that, about how to work with Linux, how to understand Hadoop, because my firm specializes in Hadoop so I’ve learned a lot about Hadoop. I have an overview into all of these things. I would say I have an overview into a lot of things, though I don’t think that I have a deep enough knowledge into the hands-on material, and that’s kind of where I’d like to go. But I’m thrilled with how I’ve progressed. It is the love for learning that keeps me going. I’m just so thrilled to learn as much as I can. I mean, MapReduce is something we’ve been talking about looking into. And R — I was debating between R or Python and Scott said Python was a little easier so I decided to start with that first.
Yeah, it’s all been great. And honestly, the people I’ve met have been one of the most enriching things. I find that people involved in data science — I think we’re all called. All of us are being called to something new. We all feel this, you know, we’re being called to something new, something emerging. And because of that, I think we want to share experience together and share knowledge together and be a community together. And I find that particularly true with women involved in the community, women in tech. It’s almost like they’re really looking out for each other and I think there are a lot of reasons for that. They want to empower other women.
Kirill: Can you give us an example of how you felt that in your learning?
Erika: Yeah. I mean, there are some women on LinkedIn that I’ve connected with that are just way higher up and they want to talk to me. You know, they’re just way above where I am but they’re just so excited to talk to me about all kinds of things when I’m at summits. If I go to a conference, it’s like a radar. You can look across the room and just connect and be like, “Hey!” You know, you’ve got heels on or you’ve got longer hair or whatever it is and it really is true. You just talk to each other because of that. You go up to each other by default and just start talking to each other. And I just see it, I see it a lot.
I actually have a sales mentor too, and she is in tech sales so she’s so involved with technology, but she always says that tech is a very male-dominated space. She’s older than I am and she feels very driven to help out the younger women who want to get into this, and she’ll connect me with other women who feel the same and then I will talk to women on LinkedIn. They just want to empower women to be more mathematical, to be more data-oriented, to be more scientific. Whatever they can do to assist with that, they try and they do a great job with it.
Kirill: Gotcha. That’s so amazing because, as you say, it’s historically been a male-dominated field but there’s nothing preventing women from getting into this space and being successful. We’ve had some very successful female guests on the podcast already, and I think it’s a great thing that women look out for each other and help each other out. So if there are any women who are getting into the space of data science listening to this, make sure to reach out to Erika at the end of this podcast and get in touch.
Erika: Oh absolutely. Yeah, please do. I feel like I want to pass that along as well. I feel like the torch has been passed on to me and I would love to inspire and empower however I can.
Kirill: Okay, fantastic. Thank you so much for that. And what I wanted to ask you here is, you’ve already mentioned about your background and how you’ve always been passionate about the analysis that goes into philosophy or into religion, into understanding why those phenomena exist and how they work. But tell us now how your background actually helps you in your pursuit of data science. What elements from your background do you leverage when you are learning about data science?
Erika: The art of communication for sure. Hands down first thing. When you’re learning about religious beliefs and you’re teaching classes — I taught at Georgia State University, a phenomenal program at Georgia State University. A lot of the professors have Ivy League educations so I had essentially an Ivy League education even though I was here at a local university.
They really taught you how to navigate classroom with diverse religious backgrounds. You know people get passionate about religion, they believe what they believe and they’re going to stick with it. So you have to be in a class of 35-40 people of different ages, different backgrounds and different religious beliefs and you have to navigate really sensitive material in a way that’s comfortable for everyone and enlightening at the same time. And you have to encourage discussion and get people talking and understanding. That is the art of communication hands down. That’s definitely something I’ve learned. If you can get around people’s religious beliefs and still get them to shake hands and agree on points, then you can definitely dive into pretty much anything else. (Laughs)
Erika: That’s for sure. But I’ve also noticed a really strange overlap. This is definitely my religious studies Master’s degree rearing its head, but there is this weird overlap of religious naming conventions within data science. You have Oracle, you have Tableau Zen Masters, even the idea of a Unicorn is kind of fairy-tale, folklore kind of a thing. Demons, which some people pronounce Daemons — that’s an ancient understanding of a demon, which is interesting.
In Plato’s symposium — you know, Plato, the famous philosopher, in his symposium he’s talking to a priestess and she tells him about demon. She says that what they essentially do is they translate and transmute information from the immortal to the mortal, back and forth. And if you look at what a Demon does, you have these name nodes and different things and they translate exactly that. They speak from human to computer. It’s interesting.
Kirill: I’m not familiar with that term. Are you referring to something in Hadoop, because you mentioned name nodes?
Kirill: Okay. So you’re getting into Hadoop terminology here. Okay, gotcha.
Erika: Yeah. Well, it is the background, yeah.
Kirill: All right. Scott is going to be pleased when he hears this podcast for sure. Okay, that’s really cool. The reason I asked that question is because a lot of our listeners are coming from non-technical or semi-technical backgrounds, and it’s always a challenge for people to understand that you don’t have to have that technical background to be successful in data science. In fact, your diverse background in arts or something else can give you an advantage which other people don’t have.
And what you mentioned, the art of communication, I personally believe that that beats a mathematical background hands down 10 days out of 10, every single time, the art of communication is going to be the most important thing. Yes, you can crunch numbers, but if you cannot communicate your insights, then the value that you’re adding is very, very low. Whereas if you can communicate, even if you can’t crunch numbers, you can become the bridge between the insights and the people that you’re speaking with.
Erika: That’s right, exactly. Actually, I will add to that, because one of the women I really admire as a data scientist works at Disney and I was talking to her about my background. I said, “Just tell me outright, is my liberal arts background kind of a deterrent? Are you looking for someone who has a Master’s in statistics or something?” She in particular loves people with liberal arts background, and they actually hired someone who’s a philosophy PhD to do data science, because they find they’re great communicators. And for them at Disney — I’m speaking on her behalf, but she said that is as important to them, the fact that you can communicate what you find is as important as the mathematical knowledge, if not more important sometimes.
Kirill: Fantastic. And speaking of Disney, how about we do a quick talk about Nicholas Cepeda and his podcast? We were talking about this before. So Nicholas was on this show a couple of weeks or months ago and you told me that you got really inspired by his talk. Tell us more about that.
Erika: Yeah, he is my super student rock star role model. (Laughs) I actually didn’t hear his podcast first. My husband and then my sales mentor, they both heard him at the same time and they both sent his podcast recording to me and said, “You have to hear this. He’s just like you. He’s just like you!” So I listened to it and I was like, “Yes, except I think that Nicholas definitely has more of the technical language behind him and that kind of experience.” But yes, I was, like — you even said it when you set up the podcast. It’s inspiring, it gets you pumped up. What did you say? You said something — “I walked away from this interview ready to take on the world….”
Kirill: —energized.” That was so energy. So much energy, yeah.
Erika: Right, exactly. And I think you did a great job with that because it was such a success story. He just really crammed end of semester-style to make this interview successful. And he did and now he’s an intern and he’s also one of my LinkedIn connections and we check out each other’s profiles from time to time. So I’m going to send him this recording. (Laughs)
Kirill: For sure. And speaking of that, obviously you and your husband and some of your colleagues, you’re following this podcast and possibly other podcasts as well. Tell us about the value you see as somebody who is getting into the space of data science, the value you see in learning about other people’s successes, about other people’s experiences or even learning about some expertise from other people who are coming onto podcasts.
Erika: Well, you know, I think the expertise is great, and I do follow a lot of podcasts. So I’m going to give you a little bit of praise to start out. There are so many podcasts and classes where the speaker is so monotone and over your head. And as just a student of data science, it’s so hard just to keep up and — I don’t know how they get people who are half awake to record these sessions, but it’s so hard to understand really complex technical information, especially from someone who is monotone. And you are not like that. You’re very engaging, you’re a warm interviewer, you’re obviously a fun person to talk to, so that is a good thing. I think I told you that the first time I reached out to you, that I’m very appreciative that you’re not monotone and you’re engaging.
Kirill: Thank you. I’m blushing. I’m all blushing now. (Laughs)
Erika: (Laughs) Right? But I think something you actually touched on with Nicholas is important because a lot of the podcasts, they want to speak with people who are really experienced because there are a lot of important questions people have, especially if you’re a business owner of a large corporation, you have a lot of questions and you really want to know who has the answers. But if you’re someone like many of us who are just learning, you hear the really experienced people and you’re like, “This is just kind of over my head. I don’t know how to keep up.”
But with Nicholas, I thought his interview was really great because it took someone who recognized he was at the beginner level and it didn’t stop him. And that’s how I feel about myself. It doesn’t stop me that I’m at the beginner level and it doesn’t stop me that I’m a mom of toddlers because I am. It doesn’t stop me that there’s only so much time in a day. You just keep going and you keep learning and that’s what I think that interview portrayed. And I don’t hear that on a lot of podcasts. It’s like, “Keep up with it. It might be overwhelming, but you keep going with it and you keep learning because we’re all learning.” Data science is so new. We’re all learning what it means to be in data science, so don’t let that hinder you. Be a part of it and define the trend in your own way, mark out your own fate.
Kirill: Exactly. I totally attest to that. Let this be a huge inspiration to everybody listening. Do not stop, just keep learning, keep powering through. You can do it. As Erika pointed out, you’re not alone. There’s lots of people taking on this challenge. It’s totally possible and there’s lots of great examples of people who have achieved a lot in relatively short periods of time just because of the dedication and the passion towards the subject. So it’s all totally doable.
I really like the comment about “mark out your own pathway in data science.” It’s such a broad field. Find out what you’re passionate about and how you want to take on this field and you can totally do it. You can totally create a career for yourself in this space.
Kirill: That’s a really cool excurse into how you’re learning and why you’re learning. Tell us about a challenge. What’s the biggest challenge that you’ve had learning data science? Probably apart from waking up at 4:00 A.M. every night because of your kids and then not having enough sleep in the morning.
Erika: I think my biggest challenge would be the art of redefining myself. Even though I was a liberal arts person and even though I’m a woman and, let’s face it, we’re not a majority in the field — I mean, when I was in high school and college, I used to joke around that math and I had an understanding. I leave it alone and it leaves me alone. (Laughs) So I had to redefine myself and take charge and I had to be, like, “No, I’m going to learn statistics! I’m going to sit down and I’m going to learn it because I am going to enjoy it and I do enjoy it!” So it’s been that maturation of realizing I’ve changed and embracing that new side of myself and following my gut instinct and learning to follow that intuition and dive in deep where I wanted to and be fearless about it. You have to be fearless in a lot of ways.
I heard a quote on a radio this morning that I really liked. “You can’t cross the street until you step out in front of traffic.” And I think that that is what it is to be involved in data science, especially coming from a background like mine. You have to just do it. Sometimes the best thing you can do in life is just close your eyes and keep walking and just go with it.
Actually, when I told my dad that I was going to start learning data science, I said — you know, I talked to my managing partner Scott and he said, “Go ahead, start learning,” and I said to my dad, “I really don’t know how this is going to turn out. I don’t know what the end goal is. I don’t know if I’m going to be the next major data scientist. I don’t know.” But my dad said to me, “You know, there’s this quote by Ralph Waldo Emerson, a great American writer, and it says, ‘Do the thing and you’ll have the power.’” So that’s my mantra. I do the thing and eventually all of it will unveil itself to me. I do thing and I’ll have the power.
Kirill: Fantastic. Thank you so much for sharing this. That’s a great way to overcome that challenge. And then on the flipside, what’s a recent win that you can share with us that you had in the process of learning data science, something that you’re super proud of?
Erika: In learning?
Kirill: Or anything. Even in your work just in data science in general.
Erika: Okay, I may give a three-part answer to that. I mean, I’m very proud of my little baby Tableau adventures. (Laughs) I think they’re wonderful. They’re probably not anything anyone really needs to look at, but I love them. I look at them from time to time. But one of my biggest wins was when I went to the Georgia Technology Summit here this year just two months ago, maybe three, and I’m in a room with the guy who owns the company that operates the New York Stock Exchange. And a guy from MIT, Caleb Harper, the things he’s doing with agriculture and farming… I talked to him and now we’re connected on LinkedIn. He’s making portable, essentially in-home farming units and they’re making them also data points, so you can start observing the data of these plants and the climate to create these plants and you can transfer essentially recipes of how to grow this plant wherever you want. So you could be in Russia and want to grow avocados and you can do that. It was just amazing to be in the room with these great minds.
But then they had an opening act to the summit that was an improv jazz playing robot. The robot just responded on the spot to the other “band members”. And that’s how they opened the summit. And I’m sitting there at my little table listening to a robot play improv jazz for me, and I thought, “This is amazing that I’m here! How many people in the world have heard a robot play improv jazz for them? I’ve done that. I’m there because of data science.” That just blew my mind. It was a beautiful moment for me.
But then also a win that really deals with what I do on a daily basis — we just recently talked to a client who has a company that’s been passed down from generation to generation over the course of I think four generations, so a pretty old company, and they’re starting to understand that if they don’t keep up with data, they’re going to become obsolete. They’ve been very successful and they’re still successful, but the CEO understands that if we don’t keep up with data, we’re going to be obsolete. We had this really great conversation and we’re helping them do that, to imagine that goal, to stay at the edge of business, to stay relevant.
And that really speaks to me because we’re talking about something that has been passed down from parent to child, and he wants to pass it down to his children and I’m helping preserve that dream, something that generations before him wanted to keep alive. I’m helping with that and it matters to me.
Kirill: That’s really cool. I think that’s a great example because everybody knows or many people have heard the statistic or the forecast that the Fortune 500 companies, just because of this disruption that is coming with the new data era, only 20% will still be alive in the next 10 years. And what you’re doing there is you’re helping somebody who can feel this threat. You’re helping them to assess it and turn data from an enemy into a friend, into an ally that they can use to not only enhance, but preserve their business for future generations, which is very admirable.
Erika: Right. And I think you touched on something there too, this idea of disruption as this inherently bad thing. It’s really not. It’s changing. I don’t know if you heard this story about a lobster, when a lobster outgrows its shell. You know, a lobster doesn’t just find a new shell. It outgrows its shell and grows into a new one. But it’s through an act of discomfort, an act of need, a sense of, “This no longer fits me. I need something else.” That’s exactly what we’re going through right now. As a world, that’s what we’re going through right now. So, yeah, change is uncomfortable, it can be uncomfortable, but just embrace it as a growth opportunity, embrace it as an opportunity and just go with it and find out where it takes you.
Kirill: Yeah, totally. If anybody listening to the podcast is still a bit iffy about this whole situation with change and disruption, I totally get it. It’s never 100% comfortable, it never will be. It’s uncomfortable because it puts you out of your comfort zone when things change around you. There’s a really good book I can recommend – and Erika, we’ll get to your books towards the end, but I just wanted to put this in here – it’s called “Who Moved My Cheese?” It’s a very short book. You can read it in half an hour or maybe an hour or so. It’s exactly about change, about how to deal with change, how to psychologically be prepared for it. And when I was working at Deloitte, the company at some point was going through quite a major shift in management, in how it’s operating and the structure of the company.
And the CEO of Deloitte went and bought lots and lots of copies of this book for every single employee at Deloitte Australia and sent them out by post. 6,000 copies of this book went out by post in one day to all of us at Deloitte. You can imagine how much he believed in this book and how much he also believed in the necessity of change. So, if you are uncomfortable with change, check out this book “Who Moved My Cheese?” I think it can get you a bit closer to being appreciative of disruption and taking it as an advantage rather than as a threat.
That’s my two cents on that. And the next question I wanted to ask you is an interesting one. I think you might have something interesting to share here. What is your most favourite thing about being a data scientist and about learning about data science and working in this area?
Erika: You know, the thing that inspires me the most is just — I’m going to put this in a really succinct way, but just redefining who and what we can be, exploring the possibilities, the edges of our potential. And it sounds like a big scale thing, but it’s true. That’s really what speaks to me. I love even the things that try to predict behaviour. I love that we can try to look down at the minutia of what it is to be a human and to think about how to relate to each other better. I like the things that speak to that kind of human condition, the things that give us a sense of purpose.
I think that data does that. You can see it in different levels that we’re redefining ourselves in a lot of ways about who we are, how we relate. And at the centre of this is really the data we’re collecting. I mean, I feel like companies are becoming more transparent, there’s greater emphasis on customer experience, user experience, whereas before I think advertising and marketing had been almost brainwashing to a point. And now you’re finding that companies are learning people have beliefs and they have desires. And if you just really talk to them about what they want, what they really want, and you’re transparent with them, they’re going to be more receptive.
And I think that’s really interesting and really cool, just the way it can unlock itself in many different ways. We’re looking at fintech, we’re looking at how all kinds of fields are changing. I actually read a really interesting article about law and they’re talking about how data science and law should be more engaged because data scientists might know a lot about data, but they don’t know a lot about law. Actually in this one article, this guy was a partner at this firm and he started learning data science because he felt like, “We need to know how this is going to impact our firm. We need to know about — yeah, okay, you have data governance, but what does it mean in a legal way?” So it’s just everything. You have doctors who are worried about losing their jobs because you have different opportunities to diagnose through machine intelligence and AI. It’s kind of new and fresh and unexplored and really exciting to be a part of.
Kirill: That’s so cool. Thanks for sharing. I like the way you describe the world we live in, the world we’re headed towards and that you’re super excited about it. But I wanted to ask you, is there anything that concerns you about data? Is there anything that you are worried about when you think of data and the future and where the world is going? Are there any things that are bothering you about data?
Erika: Well, I think you always do have that shadow side where security obviously is a big concern. And then you have companies that are not interested in doing noble things with data. And that was actually one of my major questions for Scott right off the bat when he hired me with his firm. I was like, “Do you have a standard for your clients? Will you just work with anyone or are you discriminating? Do they have to meet certain levels of what you find acceptable?” And that was something that he and I shared. You want companies that use the data for good and they’re not in it to exploit their resources or manipulate the people.
Obviously, there’s that shadow side to it. There are a few really good documentaries about that too, by the way. I can’t remember them off the top of my head, but they explore this idea of the good versus evil of data, to put it in that dichotomy. You know, there are always going to be those opportunities where people want to use it just to make more money or to have more power, but that’s why I really like to share knowledge and have conversations and just spread the ideas because I want to empower as many people as possible to understand data, to be a part of the data culture. It’s really important to me that people stay up to date with this, that they don’t get left behind just because they thought they’re more of a liberal arts kind of angle, and that they consider themselves part of this trend.
Kirill: Gotcha. That’s a good description. Definitely using data for good is something we’re all interested in and everybody should be cautious of that. Of course, data can be used for many different things, but data for good is the goal. Slowly wrapping up the podcast, I have one interesting question for you: For people out there who are also learning data science and who are also in the same boat as you, who are trying to break into this field and understand and get as much knowledge as they can, what kind of tips would you like to share with them? What inspiration can you give to them in this answer to this question?
Erika: I would reiterate the fact that I’ve heard from this person at Disney that they like people who have diverse backgrounds, they like people who communicate. The field is so new really that there is so much opportunity to even be a thought leader. There is opportunity in all kinds of dimensions, even just as a religious studies background. Let’s just say there’s 1% maybe of your listeners who have the experience in religious studies. I would love to be a part of an increasing conversation as AI and machine intelligence matures and we start to understand how we can impart an idea of ethics into machines. I would love to think that I could contribute something to that conversation. I can talk about where humanity has been and where it will go. I think that speaks to opportunities we haven’t even seen yet.
So I think you really have to follow your own gut and find out what your strengths are and be willing to explore your vulnerabilities and dive deep. Just keep diving and diving until you find yourself, and then once you do, just go for it and find the right field, the right fit for you. There are so many opportunities. Smart cities – that’s something I’m really energized about and it’s got exponential growth projection for the next few years. Fintech is another huge opportunity, health care obviously, machine intelligence, AI, and like I said, law. You can have all kinds of backgrounds and find your own niche in each one of these categories. So I think the important thing is just to really hone in on your instincts and learn your strengths, work on your weaknesses and follow your gut.
Kirill: Thank you very much for sharing that. Love it. That’s some amazing inspiration for those listening out there. You mentioned a couple of books that you’re reading. Can you share with our listeners what you think might be a good way to learn about data science through reading?
Erika: Yeah. So, one of the first books that I was introduced to that I think would be a great overview for where data science can go and where it has been, it talks a little bit about technical, it talks a little bit about business, it speaks to that maybe blossoming Unicorn in all of us — it’s like a little girl’s dream. I’ve always wanted to be a unicorn. I just didn’t know it happened through data. Yay! (Laughs) So this book kind of covers all of that and it’s called “Learning to Love Data Science” published by O’Reilly. So that’s really good. It’s just kind of almost a series of articles, just easy to read. It was actually one of the first gifts that my Managing Partner gave me to expose me to data science.
But then there’s another one that — actually, Nicholas Cepeda said it and I will go ahead and support that and also say the EMC “Data Science and Big Data Analytics” textbook. That is one I keep me with me all the time. It’s so helpful. It really does explain things in a simple way, so you can do it in chunks and understand it and take it in little sound bites as you go throughout your day and refer to it when you need to. But then also, if you’re looking into talking more, public speaking, doing presentations, my sales mentor gave me a book called “Talk Like TED,” so like Ted talks, and it gives you tips on how to present to an audience and how to have the right cadence and posture and just be yourself in front of an audience.
Kirill: Fantastic. That’s a good variety of books for people. Whatever you’re into, whatever you want to learn, Erika has recommended a book for you. So we have “Learning to Love Data Science,” we’ve got the EMC textbook and “Talk Like Ted.” So there’s a choice and maybe some interesting things that you might want to pick up if you’re looking for a good book. On that note, thank you so much, Erika, for coming on the show. If our listeners would like to contact you, get in touch, follow your career, ask you questions, what are the best ways to follow you online?
Erika: LinkedIn is a great opportunity. You can also e-mail me, of course. It’s [email protected]
Kirill: Okay, gotcha. We’ll definitely show those. Guys, connect with Erika, especially if there are women in the audience who would like to get in touch and inspire each other, Erika is your person to go to. Once again, Erika, thank you so much for coming on the show and sharing your time and knowledge with us.
Erika: Thank you, Kirill. I had such a great time. Thanks for inviting me.
Kirill: So there you have it. I hope you enjoyed today’s podcast and all of the inspiration that Erika had to share with us. Her story is definitely very motivational because as you can imagine, being a mother of two and entering a brand-new field which you’ve never encountered before which is as complex as data science, that can be very off-putting at the very least, if not frightening and scary. But nevertheless, Erika is powering ahead. She’s got her vision. She’s got her mission and she’s just ploughing at the courses at all of the ways she’s learning about data science and I think a lot of us can learn from that.
Personally, the most exciting part for me was when Erika spoke about how she gets involved in data science. She goes to events, she follows people online, she reaches out to people. She learns from courses, from books, she reads articles about data science. So she’s always on top of the game in whichever aspect or whichever medium you can imagine. And that, I think, is the best way to learn. You shouldn’t just limit yourself to one approach, just doing courses or just listening to a podcast or something else. There are so many other different ways and when you combine them, that’s when you get the synergies and that’s when you get the additional benefits of having multiple sources of education. That’s how you can propel yourself to the next step.
So I hope you enjoyed this podcast. Definitely reach out to Erika and connect with her on LinkedIn. Also you’ll be able to find all of the materials mentioned in this podcast in the show notes, which are located at www.superdatascience.com/63. And on that note, I really appreciate you being here today and spending some time with us. I can’t wait to see you next time. Until then, happy analyzing.