 Live from Washington D.C., it's theCUBE, covering AWS Public Sector Summit 2018, brought to you by Amazon Web Services and its ecosystem partners. Welcome back to the home of the Stanley Cup Champion, Washington Capitals. You're watching theCUBE's exclusive coverage of AWS Public Sector Summit 2018. I'm Stu Miniman, my co-host, John Furrier, and happy to welcome to the program Brett Dennis, who's the head of product management with Helio Campus. Thank you so much for joining us. Go Caps, thank you very much. Appreciate it. Absolutely, Ovechkin really, you know, bringing that drodoveve of, you know, having won the cup, lots of celebration, and a lot of energy here at this show. So we were hidden into day two. What's your, how have you felt the show so far? It's good, it's been good. I did the Ed Start program early in the week, and we did a sales pitch competition for startup ed techs, so it's been really exciting. So lots of fun things going on. We love talking to startups here on theCUBE. Talked to a number of companies, cybersecurity, it's like, oh okay, wait, which agency do you come out of? It's the NSA and the like. You have a similar story coming out of the University of Maryland, so give us a little bit of background on Helio Campus. Yeah, so we were spun out in 2016 from the University College. The Maryland Board of Regents had recognized the value that we'd brought to the University over about six years of development in terms of the technology platform and the services we were bringing to the University and decided this would be really useful to other universities, so let's spin it out into a company and go to market, and that's what we've been doing for the last two years. So it's been very exciting. Talk about the product. What does it do? I mean, obviously you guys incubated in the college for this equity arrangement, so you got a grant. Tell the story about the funding, and then now as you expand, what's that plan look like and how does Amazon fit into the whole next? So we had an initial grant from the Board of Regents from the State of Maryland, and the idea was to assist colleges and universities to help them ask and answer their most pressing questions, but using data, and in order to effectively do that, we wanted to bring a full solution that included platform technology as well as a services approach. So we're using Amazon Web Services and the Redshift database and platform to collect data from universities, and then we have a services team that works with Tableau dashboards to not only help visualize data in meaningful ways, but also to explore how different data sets can be cross-seated together across the student life cycle. Who's the user for you guys? Obviously, big data analytics is awesome. We're seeing that clearly as one of those things where it's completely changing businesses, and getting these kinds of insights that are actionable and different. Sometimes new questions can be answered. Who's the buyer? Who's the user? How is that working? So institutional research is a key stakeholder for us. They are traditionally seen as the data owners of universities and colleges. Do most of the research, do most of the numbers crunching. But our idea is that we want to really democratize access to data to enrollment managers, to admissions managers, even to financial managers that want to have their own power to explore and interrogate the data, but do it in such a way that it's a very intuitive process. So they don't have to be SQL query writers or really hardcore database developers. We're trying to get to those functional types of users to give them access to the data. So business users basically who want to, you don't have to be a data scientist and know Python and wrangle data. Sure. You're thinking about more of like turning them into analysts on the fly. We want them to be able to ask and answer their own questions without needing the technical skills. Now that's precisely why we bring the services in. So if they decide, I really want to use a predictive algorithmic approach to forecasting or to admissions modeling, and we have data scientists available to provide that services level on top of the platform. Yeah, wondering if you might be able to give us an example either generically or if you can mention a specific company just to help illustrate how they're transforming the use of data. So we work with the system at the system level for the University of North Carolina. So they had a need where they had done a lot of work on building up base data extracts of their own, but they needed a way to get that data out to campuses in a more effective way than usually using rich visualizations. So we won an RFP with them and we're able to help them not only at the system level but also at the campuses to make sure that the campuses and the Board of Regents and the Board of Governors are getting the data that they need to, again, understand what are my patterns and trends for success, what are specific student populations that we want to help and we want to use data to help get to those insights. So that's been a real success story for us. Talk about the public sector impact of Amazon. Obviously, Amazon's well known in the startup community. You can spin up a server that kind of changed the whole provisioning of a data center. Now they got large enterprises doing all kinds of stuff, taking database from big Oracle systems. The public sector, certainly education, we've seen community colleges all the way up to premier institutions like the University of Maryland. This is now a game changer. So how are you seeing that evolve in other universities? What are your peers doing? What's their mindset? Where are they on the progress bar using cloud, if you will, cloud native? Are they thinking microservices? They're thinking about Kubernetes. They're thinking about containers. Where are they on the evolution? Yeah, it is a game changer and it is because scalability and security are probably two themes that I would bring up. So regardless of the amount of data that you want to use as part of the analysis, there's no limit in terms of using AWS and performance. From a performance perspective, if we want to bring in a new data set, test it, see if there is correlation, see if it's useful in helping answer their key questions, we can do that. But also it goes without saying the security. So we don't really have to do a lot of selling in terms of the security of AWS because the level of approvals and a level of certifications at AWS is far exceeds beyond what any university could get on their own or what any vendor individually could do on their own. So that's a natural benefit that comes with the platform. Yeah, Brett, I wonder what other features or services in AWS are important for what you build? Obviously scalability, security, kind of a given when you talk about AWS. The Redshift platform has been really useful to us. The way that we architect our model is that we use Tableau on the front end for BI, but also any user could have access at the database level and go into Redshift that we supply security models so that only authorized users can get to that. So it's very helpful to have the security model on top of it, but the Redshift data structure really enables us to provide that experience at any level depending on what the need is of each user. So how many functional users would be going to that level? But Redshift really enables us to have the technical users and the traditional SQL query writers and the ones that are doing the cross-seating of the data that have access at that level. It's interesting you have a services model built in because it kind of makes sense because one of the benefits of the cloud obviously is speed, you get performance just raw performing, but also speed to value. You don't have to kind of do a lot of heavy lifting to kind of understand where the value points are. So how has that changed the services piece because Amazon's constantly introducing new services. How are you seeing that evolve? Because you can do some heavy lift. Okay, here's a data set. Is that the way the services are? How is the services changing with cloud? So our services model is really to hire individuals from universities that have the subject matter expertise. So we have ex-directors of institutional research, ex-admissions officers. So from our perspective, we want to leave the technical, the platform, the architecture, the security services to the experts in that realm. That's not what our universities are asking us for. They want to know, how can you bring a subject matter expertise in the functional areas where we're struggling? We don't, we want to not have to worry about the technical piece at all. So I think that's where from a cloud perspective, we're able to rely on the expertise at AWS and Amazon where, again, we're not having to worry about that. We can focus squarely on what the institutional needs are. So you're more efficient. I think so, yeah. You're spending your time doing a lot of wrangling of tech, standing up anything. Just pretty much turn key on the cloud side. Yes. Focus on getting the users up and running. Yes. With the tools that you guys have. Exactly. And we've had instances where institutions have asked, oh, you know, we want to do this research project. We need additional space. We can turn that up instantly through the value of the services provided through Amazon. Which if we were to do that on our own, it would be very expensive and a manual process. This is the benefit of the cloud. You can actually deliver services that values it to the customer. So, okay. So I got to ask you questions. I'm looking forward. Where's the headroom? If you look at your business and how it's evolving, what's the headroom that you see coming down the road that you're going towards that you're going to bring to your customer base? Right. So with evolving technologies that we all know the buzzwords about AI and machine learning, sort of taking the data science to the next level. I think that's what eventually will be asked to do is to look at, well, how can these be brought into education in a meaningful way? How can they provide us insight in ways that we're not doing today? Again, more efficiently. We also value time or accelerating time to value. So again, I think right now we're moving data around and we're shifting data and sometimes it can take a bit of time to do that. I think in the future, we'll be able to turn up customers and start delivering that time to value in a much more accelerated way. All right, so Brett, you said you attended some startup activity here at the show. Yes. I've also seen quite a few universities here. So it sounds like you're learning to help build your business as well as, from the customer standpoint, why don't you give us a little bit of insight as to the value you get out of a show like this? Absolutely. So when universities attend, we have meetings and we get an understanding of where they are now, what kinds of questions that they have. That's really what we want to get to. Analytics is really nothing unless you understand what problem am I trying to solve? So being able to have those meaningful conversations in this type of environment is very helpful to us to understand again, where are you now? What is your vision for where you want to go and how can we meet that at their point of need? What's the low hanging fruit for these universities use case-wise? What are they using you guys for the most? Have you had to look at the patterns? So it can be a range. So it can be, I am not able to provide my stakeholders meaningful visualizations and insights and have them use data in a more meaningful way. So instead of giving you a table of lines and numbers, I can give you something that's actually actionable. That's really where we start at the dashboard level. The more advanced institutions, and everyone we work with has smart people on their teams, but they may have other projects. They may not have time. They may not have the ability to hire expensive data scientists. So from that perspective on the advanced analytics side, we can help with that advanced piece with our services team. I mean, they can get up to speed faster. I mean, sometimes these projects can take months to stand up. It is, it's the acceleration that's huge. Great, what's the show vibe here? If you had to describe it for the folks that didn't make it. Yeah. What's the show about this year in your mind? What's the main big story here this year? Yeah, it's a lot like last year for me. It is understanding, and I look at it from a data perspective, of course. And it really is all about new technologies and new vendors and how we can understand again how these technologies can not only make us more efficient and from a time perspective and cost perspective, but again, how can we more meaningfully answer the important questions that we have? All right, final question, because you're a startup kind of within a cool environment at the university, which has got a lot of resources and access to some real day use case data. What's the biggest thing you've learned over the past few years? Looking at the cloud, you're right in the middle of it. Cloud native super hot, there's people born in the cloud, people migrating in the cloud, all kind of different levels of cloud-ifying businesses, some pure play cloud. What is the things that you learned the most? Looking back and saying, okay, these are the top three things that we learned. So I've worked for a foreign institution as well as for a number of different vendors in the space and I think the theme that I see is, I want to go buy a technology. Oh, I heard I need predictive analytics. Oh, I heard that I need to have machine learning. That's great that you know that, but have you really refined what your challenge is and what you're trying to solve? And that goes for any technology, whether it's cloud or a new server or a new application, really need to understand what is that core challenge? And that's where we always start. Like any good product manager, as we spoke about earlier, you got to start with what problem you're trying to solve and then apply your solution in a meaningful way. So I think that would be my answer for that. Brett, thanks for coming on theCUBE. Thanks for sharing your story. Appreciate it. It was a pleasure. Thank you. Brett Dennis here. Spin out from University of Maryland. Great startup doing big data analysts. Obviously the cloud's perfect for that and obviously creating more values. theCUBE, bringing you the action here live in Washington, DC. I'm John Furrier, Stu Miniman. We'll be back with more coverage after this short break.