 Hello and welcome to My Career in Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host, Shannon Kemp, and today we're talking to Krishna Subramanian from Comprise. Visit dataversity.net and expand your knowledge with thousands of articles and blogs written by industry experts, plus free live and on-demand webinars covering the complete data management spectrum. While you're there, subscribe to the weekly newsletter, so you'll never miss a beat. 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 help 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. So today we are joined by Krishna Subramanian, a co-founder at Comprise, and normally this is where a podcast host would read a short bio of the guests, but in this podcast your bio is what we're here to talk about. Krishna, hello and welcome. Hello, Shannon, thanks for having me. Thanks for being here. Okay, so tell me. You're the co-founder of Comprise. So tell me what type of business is Comprise? Yeah, I'm one of the three co-founders of Comprise, and this is actually our third company together for me and my two co-founders, and we started Comprise a few years after our last company got acquired because many of our customers from our prior two companies told us that they're literally drowning now in data, particularly in unstructured data, like this podcast you're recording right now, this is a great example of unstructured data because it's not sitting in a database, it's audio and video files, and 90% of the work there today is unstructured and there are no good ways to manage it, and that's the problem that Comprise solved. Oh, I love that so much. And how impressive that you're a third company. We'll get into that, I'll come back to that because I want to know what the other two were, but so what do you do then for Comprise and what's your typical work week look like? Yeah, I do. So I am the COO of the company chief operating officer, and basically what I do is I manage the sales, marketing, and alliance organizations. So the leaders of those organizations report into me. Becky, as a growing company, basically what that means is that I do a lot of meetings with customers and with partners, and that's basically what my day looks like. I understand. So tell me, Krishna, was this the dream, is this what you wanted to be, like say when you were six years old, when you grew up, like I'm going to be a co-founder of a company that helps solve unstructured data problems? Well, I always did want to create a business. I think I did want to do that from early on. But like most kids, I probably, maybe today, kids are dreaming of starting an IT company, but back then, no, that's not what I was dreaming of. Actually, as a kid, I was very interested in biology, and I was pretty fascinated by things like genetics, and I thought that's what I might end up doing. I did want to create a company doing something interesting, but really in high school, in my junior year, I took a programming course, and I was just fascinated by all the things it could do, and that's what made me change my mind to go into high tech. Oh, very nice. Gosh, but you have that entrepreneurial spirit from, you were born with it, it sounds like. Definitely has a dream, I don't know. I think it was fascinating. Actually, as a kid, I grew up partly in India and partly in West Africa because my father was for the Indian government, and he had an assignment in West Africa, so I did my high school years there, and I was always fascinated by all these people who went to a new country and set up businesses in those countries. I got to see that in West Africa. Maybe that's what led me to think I wanted to do that myself. Oh, I love that story. That's very interesting, very diverse culturally, good experience. That's amazing. So you've decided you've delved into computers, you decide you love that, so where do you go from there? How did you develop that passion? Yeah, in my college, in my undergrad, I actually came to America for my college education because after West Africa, there was some political instability there in my final high school year, so we ended up going back to India, and I finished my high school in India, but I'd also taken the SAT, and so I got a scholarship to come to America and do a really small town in Texas called San Angelo, Texas, and that's where I did my undergraduate degree, and I did it in computer science because I had gotten interested in programming in high school, and I really enjoyed it, and so I went to the University of Illinois in Urbana for my master's, and that's where I met my two co-founders. They were doing their PhDs there, and we became friends then. We all moved to the Silicon Valley, and I worked at Sun for 14 years across two, 10 years actually, and we had kept in touch with my friends from college, and we kind of were chatting, and one thing led to another, and that's how we created our first company, and yeah, and we enjoyed it so much, we did it two more times. Before we get into those companies too, so tell me what you did for Sun, was that your first job out of college? Yeah, Sun was my first job out of college, and initially I went to Sun doing something called parallel compiler technology. Basically, just like in a factory, you might have somebody doing the first part of the manufacturing, and somebody assembles the wheels, and then somebody puts the finishing touches, and then somebody puts it in a package. So that's an assembly line. Computers also can create pipeline stages like that, and can process a lot more stuff faster if you can give them things in parallel, that's called parallel computing, and that's what my master's thesis was in, and Sun was creating a chip called Ultrasport, which was a parallel chip, and so my first job out of college was to design a way to make that chip run faster through software, and that's what I did, and then this thing called Java came out from Sun, which allows the same program to run on any computer, and I led a product group for a product called Java Studio at Sun, so that's kind of what I did at Sun. Oh, that's very cool. Yeah, I know. With that little thing called Java. It's really strange, but at that time people at Sun were saying the network is the computer, and they were saying, hey, one day your toaster could send you a message and tell you when a toaster is done, and everybody thought they were just crazy for saying those things. And here we are. As somebody with an automated house, I can appreciate that. So then you decided to get to, so with your friends, your two other friends, you decided to start your first company, so how did that come about? Well, actually in my work at Sun, I used to work with a lot of our big customers, and in that I realized that there's a lot of tools to track what salespeople do, or to forecast sales and things like that. They're not too many products to engage and have accounts collaboration with big accounts, so that's what our first company actually did. It was like a sales post, but for big accounts, you know, so it did customer accounts, strategic account management is what it's called, and we created that company, and it was a great experience. It was Ventureback, NEA was one of our first investors, and it was, I mean, the company got acquired, but it also went through 9-11. Yeah, it was not the easiest of times, but we went through all that. It had a reasonable outcome, and we learned a lot, and after that company, Sun actually asked if I would come back and do mergers and acquisitions for them, and so that's what I did for six years, and I went back to Sun, and I held a corporate dope control, and then we created our second company after that. So what was the second company? So the second company, what we did is, you know, it was a time when SaaS was kind of becoming a thing, everybody was trying to run everything in the cloud, and we realized there was an opportunity to actually run the PC itself in the cloud, you know, and create this thing called virtual desktop, and it fit well with our background, because our background is parallel computing, parallel distributed computing, and SaaS is inherently a parallel distributed computing model, so we created a company to create virtual desktops in the cloud, and what was available then, because the technology was not new, there were ways to create virtual desktops, but it required expensive storage, and what we did is we changed that to a distributed architecture, which would cost less than the cost of a laptop to run virtual desktops in the cloud, so it was very cost efficient, so a lot of school districts bought our products, and, you know, a lot of companies that needed secure environments, you know, government or, you know, regulated environments, hospitals, a lot of those people bought our solutions, Citrix wanted to partner with us, because Citrix was sort of the big Citrix and VMware were the two giants in that space, and Citrix said, you know, they would license us their protocol technology, if we would allow them to resell our product, so we entered into that, and then they liked it so much, they bought the company, so we got acquired by Citrix. Oh, congratulations, yeah, that's awesome. Yeah, it was good, it was good, and so yeah, we did that, then we were, you know, running some teams at Citrix for a few years, and then many of our customers from our first two companies told us about all these issues, they have the data, and we said, wait a minute, that's a distributed computing problem. Oh, I love that, so you just, you're a problem solver. Yeah, I think that's kind of the fun thing in technology, right, I mean you can kind of, I think that's what I enjoy the most about entrepreneurship, and I don't think you have to be a founder to experience that, you could be part of a startup and experience that, but it's really, it's irreplaceable, that feeling of like starting with nothing, and just creating something, and then get it to a point where customers actually love it, and then they start telling you what to do better, and then, you know, it just takes a life of its own, it's like raising a child, you know, if you're raising it as a group. That's really nice, and how impressive that you three just keep going together, company after company, because that could be a hard thing to work together so closely like that. People say that, but I will tell you when I was a son doing acquisitions, and I did about five or six acquisitions per son, one thing I realized is that most successful companies, the founders have some history, you know, they're either friends or their siblings, or sometimes there's, you know, family, if you have some prior relationships with your co-founders, because there's already trust, I mean as long as you don't get on each other's nerves, there's already kind of trust, and you know each other's, it's comfortable, because you know each other's strengths and weaknesses, and you kind of know how to work with that. 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.dataversity.net and use code dbtalks for 20% off your purchase. Yeah, for sure. Oh, so tell me, so what has been your biggest lesson then so far in your career? Two things. I think personally, what I've enjoyed doing is going after things I'm really passionate about, because the company, you have to spend a lot of your time in it through ups and downs, and you can't do that unless you truly, truly believe in it. And so I think being passionate is important. It's something we look for in every person we hire in the company, because it's not just the founders, you know, the whole team. If they believe in it, you know, that's when you're going to get the kind of magic to happen. But I think the most important advice I got, especially in entrepreneurship, was actually from our attorney, you know, in our companies. The same person has been our lawyer for all three companies. Then we met him first, his Cuban and Cuban-American, but, you know, when we met him first, you know, I asked him, you know, you've been with so many startups, you know, what advice do you have for entrepreneurs? And he said, the only thing I'll say is never make the same mistake twice. And I thought that was very interesting, because, you know, there are no perfect answers. I mean, nobody knows for sure what's going to happen. All you can do is try to learn, you know, there's going to be failure along the way, and you just have to learn and adapt. So that's such great advice. Because so many people just expect that perfection. But you can't, but as you say, you can't learn unless you try and fail. Yeah, you really can't. I mean, it kind of sounds cliched, but I think that's the basic truth of entrepreneurship. I mean, you always are taking calculated risks. Yeah, indeed. So tell me, so now that you're working with data, and, you know, what is your definition of data? Yeah. So, you know, we manage unstructured data, and I'll tell you what we mean by that. You know, data keeps growing. I mean, you've probably seen it in your own life. Every time you buy a new phone, it seems to have more cameras than you know what to do with with it. And yet, we want to take more and more pictures. We fill up the memory card, and we have data everywhere. Every time you're getting in your car, it's generating data. Every time you go to your doctor's office, and they do imaging or they do blood work, that's generating data. So data is everywhere, and it's just going to keep growing. And most of the data is not in a database. It's all unstructured. So what does that mean? I mean, it means two things. First thing, we have to be extremely efficient about what data we keep and how we store it and how we manage it. You have to reduce those costs because the costs are climbing faster than budgets can hold. And it's not even sustainable environmentally. So you have to be more efficient with how you keep data. So that's the first thing we do. We help customers optimize their data footprint to help them reduce the costs and improve the efficiency of the infrastructure. So that's the first thing. But the second question is, why are you keeping all the data around if you never plan to use it ever again? 60% plus of data in enterprises is never opened after it's created. That means it's just sitting there. It's sitting there for years. And why are you doing that? So the big thing is how do you get more value out of your data? And that's where AI and machine learning, these are applications that now can read unstructured data. So how do you feed those applications? How do you enrich context? How do you know what you need to keep? So that's the second thing we do. As we help you improve the cost of the data, we index all the data, then we enrich it with machine learning, and then we help you feed data workflows with it to get more value from it. Oh, I love that. You're speaking my language. Probably everybody in the data communities language. Yeah, exactly. These are the two biggest problems with data. It's cost and how do you get value. And those are the problems we handle from structured data. That's very nice. And is it manageable for small companies as well as enterprise-level companies? I mean, I know small companies also struggle with these types of things. Yeah, of course. I mean, it's a cloud-based service. Anybody can use it. I will tell you that a lot of our customers are multiple petabytes of data. And it's not that it's a big company or a small company. It's just that it's a data-intensive business. There are ambulance companies with petabytes of data. Most companies now, I think. So then as you are working with customers and their data, and so do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next years and why? Yeah, I know a lot of people that have said like data is a new oil. And maybe oil is the wrong word. I mean, I don't know what you would say today, but it is actually true. Yes, I think from a material perspective, knowing how to work with data is extremely important. It's going to become increasingly important because everybody's trying to be data-driven. And it's especially important now because when humans have to process all data, we tap out at a certain point. There's only so much data we can harness in our mind. But now that you can use machine learning and AI on the data, it becomes vitally important that you know what data to feed it. You know how to know when it's hallucinating. You know how to interpret the results and you know how to push that envelope the right way. So I think, yes, data will be extremely important and so many other implications from data like security of data, privacy of data, governance of data. There's so many angles to data in the future. I agree. So then what advice would you give to people looking to get into a career in data management? I mean, you mentioned that you look for passion in your employees. Yes. I think, I mean, we see this in high tech all the time. The technologies evolve really rapidly. And so I think sometimes when people say, oh, I'm going to learn this technology or I'm going to learn that technology, you know, at some point they realize, no, that's not the hardest thing anymore. Something else has taken over. It's really hard to predict, but what does not change are the principles and the fundamentals. So I truly believe, you know, you should learn algorithms. You should learn computing principles. You should learn the foundations of programming. It doesn't matter what language you pick, but how that works. You should learn some data science and analytics techniques. You should learn all these things because these are skills that are applicable regardless of whether there's a data science job or whether the job has evolved to an analyst job or whatever it is. Those skills are what are going to kind of take you forward. Yes, absolutely. Yeah. And through trying all those things too, you can find your niche, your passion that you... Yeah. Yeah. That's one thing, you know, a lot of people, I'll tell you like probably the biggest thing I've learned from a founder perspective is a lot of times people think, oh my God, you know, I have to be so careful. Somebody's going to steal my IP. And, you know, I understand that feeling, but what I've come to realize is it's not even the idea. It's really your approach to solving problems that is hard to replicate because that's the secret sauce that you bring in. You know, and that's where you add value because the perspective you bring colors everything that you do. So I think, yeah, if you go up to something you're passionate about and you develop a unique point of view on it, I think that's a skill set everybody would value. Absolutely. And yeah, it's so very, very true. And there's so many different areas and ways to approach this, right? So many ways. Yeah, exactly. Yeah. I mean, and I think, you know, for a lot of people, I mean, I honestly think the generation now, the younger generation, it is tough for this generation because there's a lot of uncertainty, you know, in the world and there's a lot of uncertainty around how much automation will come into, you know, proficient sort of historicity has been very much human centric like high tech. I mean, high tech has been, you know, really benefited from automation so far. But those jobs have always been done by people. But, you know, you can envision in 10, 15 years, machines might be doing more of those jobs. And so I think, but what will always be valued is those human elements of decision making, of problem solving, of creativity. Those are the things that are going to be very hard for a machine to replicate for a long time to come. And so that's where you can really differentiate yourself. Yeah, that's very, very true. Perfect. Well, Krishna, I would be remiss if I didn't ask you, you know, if people wanted to look up your services, how do they find out more about Comprise? Yeah, absolutely. You could go to Comprise.com. You can, you know, look at a lot of product videos there. You can look at literature. And if you're interested in learning more, you know, just reach out. I love it. And I will qualify that and say that Comprise is filled with a K, K-O-M-P-R-I-S-E. Yeah, thank you. All our companies have served with a K, because that's the one letter of the three founders we have in common in our names. Oh, I love that. Oh, that's really nice. I love that story. So, Krishna, anything else that you want to add? You know, do any advice out there that you're giving to your customers that you want to, like, slip in or anything else that you want to add? Well, I think the biggest thing with data is knowing what you have. I mean, it sounds kind of silly, but data, there's so much data piled up everywhere. I mean, just think about ourselves. Do you remember what's on your computer versus what's on the phone you have now, versus what you kept in the cloud? We don't remember, right? And think about a business with thousands of employees. Like, everybody has piled up data in places. So, I think data management really starts with visibility to data. You know, really understanding what you have, how much is it costing you, where is it sitting, who's using it. So that visibility, I would advise everyone to kind of get that visibility first, because the rest becomes very clear once you have analytics and visibility into data. Correct. Well, Krishna, thank you so much for taking the time to chat with us today. Thank you, Shan. Really appreciate it. And very interesting, again, I'm always in awe of entrepreneurs and especially somebody who started not one, but three companies. Congratulations on that. That's really, truly amazing. Thank you. I bet. I bet you that's stressful at times, but it's got to be so fulfilling. Yeah, it's new morning. It is a very new morning. Yeah. Well, thank you. And thank you to all of our listeners out there. If you'd like to keep up to date on the latest podcasts and in the latest in data management education, you may go to dataversity.net forward slash subscribe. Stay curious, everybody. And until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity. 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