 From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards. Brought to you by Amazon Web Services. All right, welcome back to theCUBE's coverage here from Palo Alto, California in our studio with the remote interviews during this time of COVID-19 with our quarantine crew. I'm John Furrier, your host of theCUBE. And we have here the award winners for the best EDU solution from North Bay Solutions, Jim Keller, the president and from Harvard Business Publishing and University of Pittsburgh, Chad Burton, PhD in Data Privacy Officer of University of Pittsburgh IT. Thanks for coming on, gentlemen, appreciate it. Thank you. So Jim, we'll start with you. What is the solution that you guys had got the award for and talk about how it all came about? Yeah, thank you for asking and it's been a pleasure working with Chad and the entire UPIT team. So as we entered this whole COVID situation, our team really got together and started to think about how we could help AWS customers continue their journey with AWS, but also appreciate the fact that everyone was virtual, that budgets were very tight. But nonetheless, the priorities remain the same. So we devised a solution which we call jam sessions, AWS jam sessions. And the whole principle behind the notion is that many customers go through AWS training and AWS has a number of other offerings, immersion days and boot camps and other things. But we felt it was really important that we brought forth a solution that enabled customers to focus on a use case but do it rapidly in a very concentrated way with our expert team. So we formulated what we call jam sessions which are essentially very focused, two-week engagements, rapid prototyping engagements. So in the context of Chad and the UPIT team who was around a data lake and they had been, and Chad will certainly speak to this in much more detail. But the whole notion here was how does a customer get started? How does a customer prove the efficacy of AWS, prove that they can get data out of their on-premises systems, get it into AWS, make it accessible in the form, in this case, a data lake solution and have the data be consumable? So we have an entire construct that we use which includes structured education, virtual simultaneous rooms where development occurs with our joint rapid prototyping teams. We come back again and do learning. So we do all of this in the construct of the agile framework. And ideally by the time we're done with the two weeks, the customer achieves some success around achieving the goal of the jam session. But more importantly, their team members have learned a lot about AWS with hands-on work, real work, learn by doing, if you will. And really marry those two concepts of education and doing and come out of that with an opportunity then to think about the next step in that journey which in this case would be the implementation of a data lake in a full-scale project kind of initiative. Chad, talk about the relationship with North Bay Solutions. I'll see your customer, you guys are partnering on this. So it's kind of your partnering but also they're helping you. Talk about the relationship and how the interactions went. Yeah, so I was faced with a challenge that I think a lot of people in my role are faced with where the demand for data is increasing and demand for more variety of data. And I'm faced with a lot of aging on-premise hardware that I really don't want to invest any further in. So I know the clouds in the future but we are so new with the cloud that we don't even know what we don't know. So we kind of zeroed in on AWS and I was talking with them and I made it very clear. I said, because of our inexperience, we have talented data engineers but they don't have this type of experience but I'm confident they can learn. So what I'm looking for is a partner who can help us not only prove this out but it can work, which I had high confidence that it could but help us identify where we need to be putting our skill, skilling up. What gaps do we have? And AWS has just so many different components that we also needed help just zeroing in on for our need. What are the pieces we should really be paying attention to and developing those skills? So we got introduced to North Bay and they introduced us to the idea of the jam session which was perfect. It was really exactly what I was looking for. We made it very clear in the early conversations that this would be side-by-side development. That my priority was of course to meet our deliverables but also for my team to learn how to use some of this and learn what they need to dive deeper in at the end of the engagement. I think that's how it got started. And then I think it was very successful engagement after that. Talk about the jam sessions because I love this. First of all, this is in line with what we're seeing in the marketplace with rapid innovation now more than ever with virtual workforces at home given the situation. You know, rapid agile, rapid innovation, rapid development is a key kind of thing. What is a jam session? What was the approach? Jim, you laid a little bit about it out but Chad, what's your take on the jam sessions? How did it all work? I mean, it was great because of the large team that North Bay brought and the variety of skills they brought and then they just had a playbook that worked, right? They broke us up into different groups from the people who'd be making the data pipeline to the people who then would be consuming it to develop analytics projects. So that part worked really well. And yes, this rapid iterative development, you know, like right now with our current kind of process and our current tools, I have a hard time telling anybody how long it will take to get that new data source online and available to our data analysts, to our data scientists because it takes months sometimes and nobody wants that answer and I don't want to be giving that answer. So what we're really focused on is how do we tighten up our process? How do we select the right tools so that we can say, you know, we'll be two weeks from start to finish and you'll be able to make this data available. So the engagement with North of the Jam session, you know, scheduled like that really helped us prove that, you know, once you have the skills and you have the right people, you can do this rapid development and bring more value to our business more quickly, which is really what it's all about for us. Jim, I want to get your thoughts because, you know, we see time and time again with use cases with the cloud. When you got smart people, certainly people who play with data and work with data, they're not, they're pretty savvy, right? They know the limitations, but when you get the cloud, it's like a car versus a horse, right? You know, kind of, you got to go from point A to point B, but again, the faster is the key. How did you put this all together and what were the key learnings? Yeah, so, John, you know, a couple of things that are really important. One is, as Chad mentioned, really smart people on the UPIT side that wanted to really learn and had a thirst for learning. And then couple that with the thing that they're trying to learn and the actual use case that we're trying to jointly implement. The couple of things that we've learned that are really important. One is, although we have structure, we have a syllabi and we have sort of a pattern of execution, we can never lose sight of the fact that every customer is different, every team member is different. And in fact, Chad, in this case, had team members, some had more skills on AWS than others. So we had to be sensitive to that. So what we did was we sort of used our general formula for the two weeks. One week one is very structured, focused on getting folks up to speed and normalize in terms of where they are in their education of AWS solution we're building. And then week two is really meant to sort of mold the play together and really take this solution that we're trying to execute around and tailor it to the customer so that we're addressing the specific needs both from their team member perspective and the institution's perspective in total. We've learned that starting the day together and ending the day with the recap of that day is really important in terms of ensuring that everyone's on the same page, that they have commonality of knowledge. And then when we're addressing any concerns, this stuff, we move fast, right? Two weeks is not a long time to get a lot of rapid prototyping work done. So if there is anxiety or folks feel like they're falling behind, we want to make sure we knew that, we want to address that quickly, either that evening or the next morning, recalibrate and then continue. The other thing that we've learned is that in Chad and the entire UPt team did a phenomenal job of this was really preparation. So we have a set of preliminary set of activities that we work with our customers to sort of lay the foundation for so that on day one of the jam session we're ready to go. And since we're doing this virtually, we don't have the luxury of being in a physical room and having time to sort of get acclimated to the physical construct of organizing rooms and chairs and tables and all of that. We're doing all that virtually. So Chad and the team were tremendous in getting all the preparatory work done. The only thing about what's involved in a data lake, it's the data and security and access and things our team needed to work with their team. And the prescription and the formula that we use is really three critical things. One is our team members have to be adept at educating on a virtual whiteboard in this case. Secondly, we want to do side by side development. That's the whole goal and then we want team members to build trust and relationship side by side. And then thirdly and importantly, we want to be able to do over the shoulder mentoring. So as Chad's team members were executing, we could guide them as we go. And those three ingredients were really key. Chad, talk about the data lake on the outcome as you guys went through this. What was the results of the data lake? How did it all turn out? Yeah, the result was great. It was exactly what we were looking for. The way I had structured the engagement and working with Jim to do this is I want to do accomplished two things. I wanted to one, prove that we can do what we do a day with a star schema, mart model that creates a lot of reports that are important to the business, but doesn't really help us grow in our use of data. But there was a second component of it that I said, I want to show how we do something new and different that we can't do with our existing tools so that I can go back to our executive leadership and say, hey, by investing in this, here's all the possibilities we can do and we've got proof that we can do it. So some natural language processing was one of those and leveraging AWS Comprehend was key. And the idea here was there are, unfortunately it's not as relevant today with COVID but there are events happening all around campus and how do students find the right events for them? They're all in the calendar, well, with a price of natural language processing using AWS Comprehend and link them to a student's major so that we can then bubble these up to a student, hey, above all these thousands of events here that you might be most interested in. We can't do that right now, but using these tools, using the skills that North Bay helped us develop by working side by side will help us get there. The beautiful thing is with these jam sessions, once you get some success, you go for the next one. This sounds like another jam session opportunity to go in there and do the virtual version as the fall comes up, you have the new reality. And this is really kind of what I like about this story is you guys did the jam session, first of all, great project, but right in the middle of this new shift of virtual. So it's very interesting. So I want to get your thoughts Chad, as you guys looked at this, I mean, on any given Sunday, this is a great project, right? You can get people together, you go to the cloud, get more agile, get the proof points, show it, double down on it, playbook check. But now you've got the virtual workforce. How did that all play out? Anything surprise you? Any expectations that were met or things that were new that came out of this? Cause this is something that everyone is going through right now. How do I come out of this or deal with current COVID as it evolves? And then when I come out of it, I want to have a growth strategy, I want to have a team that's deploying and building. What's your take on that? Yeah, you know, it's a good question. And I was a little concerned about it at first cause when we had first begun conversations with North Bay, we were planning on a little bit on site and a little bit virtual. Then of course COVID happened, our campus is closed, you know, nobody's permitted to be there. And so we had to just pivot to 100% virtual. I have to say, I didn't notice any problems with it. It didn't impede our progress. It didn't impede our communication. I think the playbook that North Bay had really just worked for that. Now they may have had to adjust it and Jim can certainly talk to that, but you know, those morning standups for each group that's working, the end of day report outs, right? That's what, those were the things I was joining in on, you know, I wasn't involved in it throughout the day, but I wanted to check in at the end of the day to make sure things are kind of moving along. And the communication, the transparency that was provided was key. And because of that transparency and that kind of schedule they already have set up at North Bay, we didn't see, we didn't have any problems having that a fully virtual engagement. In fact, I would probably prefer to do virtual engagements moving forward because we can cut down on travel costs for everybody. You know, Jim, I want to get your thoughts on this. I think this is a huge point that's not just representing here and illustrating with the example the success of the EDU solution you guys got the award for, but in a way COVID exposes all the people that are been relying on waterfall-based processes. You got to be in a room and argue things out or have meetings set up. It takes a lot of time. And when you have a virtual space and an agile process, yeah, you make some adjustments, but if you're already agile, it doesn't really impact too much. Can you share your thoughts because you have deployed this very successfully virtually? Yeah, no, it's certainly, the key is always preparation and our team did a phenomenal job at making sure that we could deliver equal to or better than virtual experience than we could in onsite experience, but John, you're absolutely right. What it forces you to really do is think about all the things that come natural when you're in a physical room together, but you can't take for granted virtually, even interpersonal relationships and how those are built and the trust that's built and the whole, as much as this is a technical solution and as much as the teams did really phenomenal AWS work, foundationally, it all comes down to trust and as Chad said, transparency. And it's often hard to build that into a virtual experience. So part of that preparatory work that I mentioned, we actually spend time doing that and we spend time with Chad and other team members understanding each of their team members and understanding their strengths, understanding where they were in the education journey and experiential journey, a little bit about them personally, right? So I think, look, I think the reality in the short and near term is that everything's going to be virtual. North Bay delivers much of their large scale projects virtually now. We have a whole methodology around that and it's proven actually it's made us better at what we do, frankly. Yeah, and definitely puts the pressure on getting the job done and focusing on the creativity and the building out. I want to ask you guys both the same question this next round because I think it's super important as people see the reality of cloud and there's certainly it's been around the benefits are there, but still you have the mentality of, we have to do it ourselves, not invented here, it's a managed service, it's security, there's plenty of objections if you really want to avoid cloud you can come up with something if you really looked for it. But the reality is, is that there are benefits for the folks out there that are now being accelerated into the cloud for the reasons with COVID and other reasons, what's your advice to them? Why cloud? What's the bet? What comes out of making a good choice with the cloud, Chad? As people sit in there going, okay, I got to get my cloud mojo going. What's your advice to those folks sitting out there watching this? Yeah, so I would say, and Jim knows this, we at Pitt have a big vision for data, a whole universe of data where just everything is made available and I can't estimate the demand for all of that yet, right? That's going to evolve over time. So if I'm trying to scale some physical hardware solution, I'm either going to under scale it and not be able to deliver or I'm going to invest too much money for the value I'm getting. What by moving to the cloud, what that enables me to do is just grow organically and make sure that our spend and the value we're getting from the use are always aligned. And then of course all the questions about scalability and extensibility, right? We can just keep growing and if we're not seeing value in one area, we can just stop and we're no longer spending on that particular area and we can direct that money to a different component of the cloud. So just not being locked in to a huge expense upfront is really key, I think. Jim, your thoughts on why cloud and why now? Obviously it's pretty obvious reasons, but benefits for the naysayers sitting on the fence who are... Yeah, it's a really important question, John. And I think Chad had a lot of important points. I think there's two others that become important. One is agility, whether that's agility with respect to if you're in a competitive marketplace, agility in terms of just retaining team members and staff in a highly competitive environment we all know we're in, particularly in the IT world, agility from a cost perspective. So agility is a theme that comes through and through over and over and over again. And as Chad rightfully said, most companies and most organizations they don't know the entirety of what it is they're facing or what the demands are going to be on their services. So agility is really key. And the second one is the notion has often been that you have to have it all figured out so you can start. And really our mantra on the jam session was sort of born this way. It's really start by doing. Pick a use case, pick a pain point, pick an area of frustration, whatever it might be and just start the process. You'll learn as you go. And not everything is the right fit for cloud. There are some things for the right reasons where alternatives might be appropriate. But by and large, if you start by doing and in fact, you know, through jam session learn by doing you'll start to better understand enterprise. We'll start to better understand what's most applicable to them where they can leverage the best bang for the buck if you will. And ultimately deliver on the value that IT is meant to deliver to the line of business whatever that might be. And those two themes come through and through. And thirdly, I'll just add speed now, speed of transformation, speed of cost reduction, speed of feature rollout, you know, Chad has users begging for information and access to data, right, he and the team are sitting there trying to figure out how to give it to them quickly. So speed of execution with quality is really paramount as well these days. Yeah, and Chad also mentioned scale too because he's trying to scale up as key. And again, getting those cloud muscles going from the teams and culture is critical because, you know, matching that incentives I think the alignment is critical point. So congratulations gentlemen on a great award, best EDU solution. Chad, while I have you here, I want to just get your personal thoughts but your industry expert PhD had on because, you know, one of the things we've been reporting on is a lot of in the EDU space, higher ed and other areas with people having different education policies, the new reality is with virtualized students and stack of the alumni in community, the expectations and the data flows are different, right? So you had stuff that people use systems, legacy systems kind of as a good opportunity to look at cloud to build a new abstraction layer and again, create that alignment of what can we do development wise? Cause I'm sure you're seeing new data flows coming in. I'm sure there's kind of thinking going on around, okay, as we go forward, how do we find out who's what classes to attend if they're not on site? This is another jam session. So I see more things happening, pretty innovative in your world. What's your take on all of this? My take, you know, so when we did the pivot, we did a pivot right after spring break to be virtual for our students like a lot of universities did. And you learn a lot when you go through a crisis kind of like that and you find all the weaknesses and we had finished the engagement I think with North Bay by that point where we're in it and seeing how if we were at our future state you know, the way I envision the future state I can now point to these specific things and give specific examples about how we would have been able to more effectively respond when these new demands on data came up when new data flows were being created very quickly and you know, able to point out to the weaknesses of our current ecosystem and how that would be better. So that was really key. And then, you know, it's a, this whole thing is an opportunity. It's really exhilarated. A lot of things that were kind of already in the works and that's why it's exciting. It's obviously very challenging. You know, and at Pitt, we're really right now trying to focus on how do we have a safe campus environment and going with a maximum flexibility and all the technology that's involved in that. And you know, I've already got, you know I've had more unique data requests into my desk since COVID and in the previous five years, you know. New patterns, new opportunities to write software and it's great to see you guys focus on that hierarchy of needs. Really appreciate it. I want to just share with you a funny story, not funny, but interesting story because this highlights the creativity that's coming. I was riffing on Zoom with someone in a higher ed university out here in California and it wasn't official business was just more riffing on the future. And I said, hey, wouldn't it be cool if you had like an abstraction layer that had leveraged Canvas, Zoom and Discord. You know, all the kids are on Discord if they're gamers. So you go, okay, why Discord? It's a hang space. People are, it's connective tissue. Well, how do you build notifications through the different silos? So, you know, Canvas doesn't support certain things and you know, Canvas is the software that most universities use. But that's a use case that we were just riffing on. But that's the kind of ideation that's going to come out of these kinds of jam sessions. You guys having that kind of feeling too, I mean, how do you see this new ideation rapid prototype? Because I only think it's going to get faster and accelerated. Yeah, as Chad said, you know, his requests are multiplying, I'm sure. And people aren't, you know, folks are not willing to wait. And you know, we're in a hurry up, hurry up I wanted now mentality these days with both college attendees as well as those of us who are trying to deliver on that promise. And I think, John, I think you're absolutely right. And I think that whether it be the fail fast mantra or whether it be, can we even make this work, right? Does it have legs? Is it even viable? And is it even cost effective? I can tell you that we do a lot of work in ed tech. We do a lot of work in other industries as well. And what the, you know, the courseware delivery companies and the infrastructure companies are all trying to deal with as a result of COVID is they've all had to try to innovate. So we're being asked to challenge ourselves in ways we've never been asked to challenge ourselves in terms of speed of execution, speed of deployment because these folks need answers, you know, tomorrow, today, yesterday, not six months from now. So the, I'll use the word legacy way of thinking is really not one that can be sustained or tolerated any longer. And I want Chad and others to be able to call us and say, hey, we need help, we need help quickly. How can we go work together side by side and go prove something? It may not be the most elegant. It may not be the most robust, but we need it kind of tomorrow. And that's really the spirit of the whole notion of jam session. And new expectations means new solutions. Chad, we'll give you the final word. Going forward, you're on this wave right now. You got new things coming at you, getting that foundation set. What's your mindset as you ride this wave? I'm optimistic. It really, it's an exciting time to be in this role. The progress we've made in the calendar year 2020, despite the challenges we've been faced with, with COVID and budget issues, I'm optimistic. I love what I saw in the jam session. It just kind of confirmed my belief that this is really the future for the University of Pittsburgh in order to fully realize our vision of maximizing the value of data. Awesome. Best EDU Solution Award for AWS Public Sector. Congratulations, North Bay Solutions. Jim Keller, President and University of Pittsburgh. Chad Burton, thank you for coming on and sharing your story. Great insights. And again, the wave is here. New expectations, new solutions, clouds there. And you guys got a good approach. Congratulations on the jam session. Thanks. Thank you, John. Chad, pleasure. Thank you. Okay, this is the CUBE coverage of AWS Public Sector Partner Awards. I'm Sean Furrier, host of theCUBE. Thanks for watching.