>> Live from Washington DC, it's theCUBE. Covering the AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Welcome back to 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, and my co-host John Furrier. Welcome to the program. Bret Dennis who's the head of product management with Helio campus. >> Thank you. >> Thanks so much for joining us. >> Go caps, thank you very much, appreciate it. >> Really bringing that [Inaudible] of having won the cup, lots of celebration, and there's a lot of energy here at this show. So we're heading into day two, what's your ... How do you feel about the show so far? >> It's good, it's been good. I did the Edstart program earlier in the week, and we did a sales pitch competition for startup Edtechs, so it's been really exciting, lot's of fun things going on. >> We've loved talking to startups here on theCUBE. I've talked to a number of companies, cyber-security, it's like, "Oh, okay, wait, which agency did you come out of." because of the NSA and the like. You have a similar story coming out of the University of Maryland >> Right. >> Give us a little bit of background on Helio campus. >> 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. >> Tell me about the product? What does it do? I mean obviously you guys incubate it in the college, so there's equity arrangements, 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 mess? >> So we had an initial grant from the board of regions 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-seeded together across the student life cycle. >> Whose the user for you guys? Obviously big data analyst is awesome, we're seeing that clearly as one of those things where it's completely changing businesses >> Sure. 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'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 the access to data >> So business users basically who don't have to be a data scientist to know Python and wrangle data, 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. >> 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 using rich visualizations. So we won an RFP with them and were 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 databases from big Oracle systems. But 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, are they thinking about [Inaudible], are they 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 with out 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 the level of certifications at AWS 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 a platform. >> 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, now 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 not 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-seeding of the data to 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 performance, but also speed to value, so you don't have to do a lot of heavy lifting to kind of understand where the value points are. So how does that change the services speed because Amazon's constantly introducing new services, how are you seeing that evolve? Because you can do some heavy lifting, 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 x directors of institutional research, x admission 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 us subject matter expertise in the functional areas where we're struggling, 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 and we can focus squarely on what the institutional needs are. >> So you're more efficient? >> I think so, yeah. >> You don't spend your time doing a lot wrangling of tech, standing up anything, just pretty much turnkey on the cloud side, focused on getting the users up and running with the tools that you guys have. >> Exactly, and we've had instenses where institutions have asked, "Oh, 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. >> You can actually deliver services that values to the customer. I got to ask you a question, now looking forward, where's the head room? If you look at your business and how it's evolving, what's the head room that you see coming down the road that you're going towards, that you're going to bring to you 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 we'll 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. >> So you said you attended some startup activity here at the show >> Yes. and 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 that you get out of a show like this. >> Absolutely. So when the Universities attend we have meetings and we get an understandings of where they are now, what kinds of questions are they having, that's really what we want to get to, analytics is really nothing unless you understand what problem are you 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, 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, if you had to look at the patterns? >> It can be arranged, 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 analytic side we can help with that advanced piece with our services team. >> They can get up to speed faster. 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? >> It' 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 from a time perspective and cost perspective, but again, how can we more meaningfully answer the important questions that we have. >> Alright 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 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 is super hot, there's people born in the cloud, people migrating the cloud, all kind of different levels of cloudifying businesses, some PurePlay cloud. What is the things that you learn 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 this space and I think the theme that I see is I want to go buy technology, "Oh I heard I need predictive analytics, Oh I heard that I need to have machine learning", well that's great that you know that, but have you really refined what your challenges 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've 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. >> Bret, thank for coming on theCUBE, thanks for sharing your story >> Thank you. Appreciate it, alright >> It was a pleasure. >> Bret Dennis here, spin out from University of Maryland, great startup doing big data analyst, obviously the clouds perfect for that and obviously creating more value. It's theCUBE bringing you the action here live in Washington D.C. I'm John Furrier and Stu Miniman. We'll be back with more coverage after this short break. (light electronic music)