>>Mhm Hello and welcome to the cubes coverage of AWS amazon web services, Global public Sector partner awards program. I'm john for your host of the cube here we're gonna talk about the best covid solution to great guests. Benham or with healthcare and life sciences lead at palantir Ben welcome to the cube SAm Michaels, Director of automation and compound management and Cats. National Center for advancing translational sciences and Cats. Part of the NIH National sort of health Gentlemen, thank you for coming on and and congratulations on the best covid solution. >>Thank you so much john >>so I gotta, I gotta ask you the best solution is when can I get the vaccine? How fast how long it's gonna last but I really appreciate you guys coming on. I >>hope you're vaccinated. I would say john that's outside of our hands. I would say if you've not got vaccinated, go get vaccinated right now, have someone stab you in the arm, you know, do not wait and and go for it. That's not on us. But you got that >>opportunity that we have that done. I got to get on a plane and all kinds of hoops to jump through. We need a better solution anyway. You guys have a great technical so I wanna I wanna dig in all seriousness aside getting inside. Um you guys have put together a killer solution that really requires a lot of data can let's step back and and talk about first. What was the solution that won the award? You guys have a quick second set the table for what we're talking about. Then we'll start with you. >>So the national covered cohort collaborative is a secure data enclave putting together the HR records from more than 60 different academic medical centers across the country and they're making it available to researchers to, you know, ask many and varied questions to try and understand this disease better. >>See and take us through the challenges here. What was going on? What was the hard problem? I'll see everyone had a situation with Covid where people broke through and cloud as he drove it amazon is part of the awards, but you guys are solving something. What was the problem statement that you guys are going after? What happened? >>I I think the problem statement is essentially that, you know, the nation has the electronic health records, but it's very fragmented, right. You know, it's been is highlighted is there's there's multiple systems around the country, you know, thousands of folks that have E H. R. S. But there is no way from a research perspective to actually have access in any unified location. And so really what we were looking for is how can we essentially provide a centralized location to study electronic health records. But in a Federated sense because we recognize that the data exist in other locations and so we had to figure out for a vast quantity of data, how can we get data from those 60 sites, 60 plus that Ben is referencing from their respective locations and then into one central repository, but also in a common format. Because that's another huge aspect of the technical challenge was there's multiple formats for electronic health records, there's different standards, there's different versions. And how do you actually have all of this data harmonised into something which is usable again for research? >>Just so many things that are jumping in my head right now, I want to unpack one at the time Covid hit the scramble and the imperative for getting answers quickly was huge. So it's a data problem at a massive scale public health impact. Again, we were talking before we came on camera, public health records are dirty, they're not clean. A lot of things are weird. I mean, just just massive amount of weird problems. How did you guys pull together take me through how this gets done? What what happened? Take us through the the steps He just got together and said, let's do this. How does it all happen? >>Yeah, it's a great and so john, I would say so. Part of this started actually several years ago. I explain this when people talk about in three C is that and Cats has actually established what we like to call, We support a program which is called the Clinical translation Science Award program is the largest single grant program in all of NIH. And it constitutes the bulk of the Cats budget. So this is extra metal grants which goes all over the country. And we wanted this group to essentially have a common research environment. So we try to create what we call the secure scientific collaborative platforms. Another example of this is when we call the rare disease clinical research network, which again is a consortium of 20 different sites around the nation. And so really we started working this several years ago that if we want to Build an environment that's collaborative for researchers around the country around the world, the natural place to do that is really with a cloud first strategy and we recognize this as and cats were about 600 people now. But if you look at the size of our actual research community with our grantees were in the thousands. And so from the perspective that we took several years ago was we have to really take a step back. And if we want to have a comprehensive and cohesive package or solution to treat this is really a mid sized business, you know, and so that means we have to treat this as a cloud based enterprise. And so in cats several years ago had really gone on this strategy to bring in different commercial partners, of which one of them is Palin tear. It actually started with our intramural research program and obviously very heavy cloud use with AWS. We use your we use google workspace, essentially use different cloud tools to enable our collaborative researchers. The next step is we also had a project. If we want to have an environment, we have to have access. And this is something that we took early steps on years prior that there is no good building environment if people can't get in the front door. So we invested heavily and create an application which we call our Federated authentication system. We call it unified and cats off. So we call it, you know, for short and and this is the open source in house project that we built it and cats. And we wanted to actually use this for all sorts of implementation, acting as the front door to this collaborative environment being one of them. And then also by by really this this this interest in electronic health records that had existed prior to the Covid pandemic. And so we've done some prior work via mixture of internal investments in grants with collaborative partners to really look at what it would take to harmonize this data at scale. And so like you mentioned, Covid hit it. Hit really hard. Everyone was scrambling for answers. And I think we had a bit of these pieces um, in play. And then that's I think when we turned to ban and the team at volunteer and we said we have these components, we have these pieces what we really need. Something independent that we can stand up quickly to really address some of these problems. One of the biggest one being that data ingestion and the harmonization step. And so I can let Ben really speak to that one. >>Yeah. Ben Library because you're solving a lot of collaboration problems, not just the technical problem but ingestion and harmonization ingestion. Most people can understand is that the data warehousing or in the database know that what that means? Take us through harmonization because not to put a little bit of shade on this, but most people think about, you know, these kinds of research or non profits as a slow moving, you know, standing stuff up sandwich saying it takes time you break it down. By the time you you didn't think things are over. This was agile. So take us through what made it an agile because that's not normal. I mean that's not what you see normally. It's like, hey we'll see you next year. We stand that up. Yeah. At the data center. >>Yeah, I mean so as as Sam described this sort of the question of data on interoperability is a really essential problem for working with this kind of data. And I think, you know, we have data coming from more than 60 different sites and one of the reasons were able to move quickly was because rather than saying oh well you have to provide the data in a certain format, a certain standard. Um and three C. was able to say actually just give us the data how you have it in whatever format is easiest for you and we will take care of that process of actually transforming it into a single standard data model, converting all of the medical vocabularies, doing all of the data quality assessment that's needed to ensure that data is actually ready for research and that was very much a collaborative endeavor. It was run out of a team based at johns Hopkins University, but in collaboration with a broad range of researchers who are all adding their expertise and what we were able to do was to provide the sort of the technical infrastructure for taking the transformation pipelines that are being developed, that the actual logic and the code and developing these very robust kind of centralist templates for that. Um, that could be deployed just like software is deployed, have changed management, have upgrades and downgrades and version control and change logs so that we can roll that out across a large number of sites in a very robust way very quickly. So that's sort of that, that that's one aspect of it. And then there was a bunch of really interesting challenges along the way that again, a very broad collaborative team of researchers worked on and an example of that would be unit harmonization and inference. So really simple things like when a lab result arrives, we talked about data quality, um, you were expected to have a unit right? Like if you're reporting somebody's weight, you probably want to know if it's in kilograms or pounds, but we found that a very significant proportion of the time the unit was actually missing in the HR record. And so unless you can actually get that back, that becomes useless. And so an approach was developed because we had data across 60 or more different sites, you have a large number of lab tests that do have the correct units and you can look at the data distributions and decide how likely is it that this missing unit is actually kilograms or pounds and save a huge portion of these labs. So that's just an example of something that has enabled research to happen that would not otherwise have been able >>just not to dig in and rat hole on that one point. But what time saving do you think that saves? I mean, I can imagine it's on the data cleaning side. That's just a massive time savings just in for Okay. Based on the data sampling, this is kilograms or pounds. >>Exactly. So we're talking there's more than 3.5 billion lab records in this data base now. So if you were trying to do this manually, I mean, it would take, it would take to thousands of years, you know, it just wouldn't be a black, it would >>be a black hole in the dataset, essentially because there's no way it would get done. Ok. Ok. Sam take me through like from a research standpoint, this normalization, harmonization the process. What does that enable for the, for the research and who decides what's the standard format? So, because again, I'm just in my mind thinking how hard this is. And then what was the, what was decided? Was it just on the base records what standards were happening? What's the impact of researchers >>now? It's a great quite well, a couple things I'll say. And Ben has touched on this is the other real core piece of N three C is the community, right? You know, And so I think there's a couple of things you mentioned with this, johN is the way we execute this is, it was very nimble, it was very agile and there's something to be said on that piece from a procurement perspective, the government had many covid authorities that were granted to make very fast decisions to get things procured quickly. And we were able to turn this around with our acquisition shop, which we would otherwise, you know, be dead in the water like you said, wait a year ago through a normal acquisition process, which can take time, but that's only one half the other half. And really, you're touching on this and Ben is touching on this is when he mentions the research as we have this entire courts entire, you know, research community numbering in the thousands from a volunteer perspective. I think it's really fascinating. This is a really a great example to me of this public private partnership between the companies we use, but also the academic participants that are actually make up the community. Um again, who the amount of time they have dedicated on this is just incredible. So, so really, what's also been established with this is core governance. And so, you know, you think from assistance perspective is, you know, the Palin tear this environment, the N three C environment belongs to the government, but the N 33 the entire actually, you know, program, I would say, belongs to the community. We have co governance on this. So who decides really is just a mixture between the folks on End Cats, but not just end cast as folks at End Cats, folks that, you know, and I proper, but also folks and other government agencies, but also the, the academic communities and entire these mixed governance teams that actually set the stage for all of this. And again, you know, who's gonna decide the standard, We decide we're gonna do this in Oman 5.3 point one um is the standard we're going to utilize. And then once the data is there, this is what gets exciting is then they have the different domain teams where they can ask different research questions depending upon what has interest scientifically to them. Um and so really, you know, we viewed this from the government's perspective is how do we build again the secure platform where we can enable the research, but we don't really want to dictate the research. I mean, the one criteria we did put your research has to be covid focused because very clearly in response to covid, so you have to have a Covid focus and then we have data use agreements, data use request. You know, we have entire governance committees that decide is this research in scope, but we don't want to dictate the research types that the domain teams are bringing to the table. >>And I think the National Institutes of Health, you think about just that their mission is to serve the public health. And I think this is a great example of when you enable data to be surfaced and available that you can really allow people to be empowered and not to use the cliche citizen analysts. But in a way this is what the community is doing. You're doing research and allowing people from volunteers to academics to students to just be part of it. That is citizen analysis that you got citizen journalism. You've got citizen and uh, research, you've got a lot of democratization happening here. Is that part of it was a result of >>this? Uh, it's both. It's a great question. I think it's both. And it's it's really by design because again, we want to enable and there's a couple of things that I really, you know, we we clamor with at end cats. I think NIH is going with this direction to is we believe firmly in open science, we believe firmly in open standards and how we can actually enable these standards to promote this open science because it's actually nontrivial. We've had, you know, the citizen scientists actually on the tricky problem from a governance perspective or we have the case where we actually had to have students that wanted access to the environment. Well, we actually had to have someone because, you know, they have to have an institution that they come in with, but we've actually across some of those bridges to actually get students and researchers into this environment very much by design, but also the spirit which was held enabled by the community, which, again, so I think they go they go hand in hand. I planned for >>open science as a huge wave, I'm a big fan, I think that's got a lot of headroom because open source, what that's done to software, the software industry, it's amazing. And I think your Federated idea comes in here and Ben if you guys can just talk through the Federated, because I think that might enable and remove some of the structural blockers that might be out there in terms of, oh, you gotta be affiliate with this or that our friends got to invite you, but then you got privacy access and this Federated ID not an easy thing, it's easy to say. But how do you tie that together? Because you want to enable frictionless ability to come in and contribute same time you want to have some policies around who's in and who's not. >>Yes, totally, I mean so Sam sort of already described the the UNa system which is the authentication system that encounters has developed. And obviously you know from our perspective, you know we integrate with that is using all of the standard kind of authentication protocols and it's very easy to integrate that into the family platform um and make it so that we can authenticate people correctly. But then if you go beyond authentication you also then to actually you need to have the access controls in place to say yes I know who this person is, but now what should they actually be able to see? Um And I think one of the really great things in Free C has done is to be very rigorous about that. They have their governance rules that says you should be using the data for a certain purpose. You must go through a procedure so that the access committee approves that purpose. And then we need to make sure that you're actually doing the work that you said you were going to. And so before you can get your data back out of the system where your results out, you actually have to prove that those results are in line with the original stated purpose and the infrastructure around that and having the access controls and the governance processes, all working together in a seamless way so that it doesn't, as you say, increase the friction on the researcher and they can get access to the data for that appropriate purpose. That was a big component of what we've been building out with them three C. Absolutely. >>And really in line john with what NIH is doing with the research, all service, they call this raz. And I think things that we believe in their standards that were starting to follow and work with them closely. Multifactor authentication because of the point Ben is making and you raised as well, you know, one you need to authenticate, okay. This you are who you say you are. And and we're recognizing that and you're, you know, the author and peace within the authors. E what do you authorized to see? What do you have authorization to? And they go hand in hand and again, non trivial problems. And especially, you know, when we basis typically a lot of what we're using is is we'll do direct integrations with our package. We using commons for Federated access were also even using login dot gov. Um, you know, again because we need to make sure that people had a means, you know, and login dot gov is essentially a runoff right? If they don't have, you know an organization which we have in common or a Federated access to generate a login dot gov account but they still are whole, you know beholden to the multi factor authentication step and then they still have to get the same authorizations because we really do believe access to these environment seamlessly is absolutely critical, you know, who are users are but again not make it restrictive and not make it this this friction filled process. That's very that's very >>different. I mean you think about nontrivial, totally agree with you and if you think about like if you were in a classic enterprise, I thought about an I. T. Problem like bring your own device to work and that's basically what the whole world does these days. So like you're thinking about access, you don't know who's coming in, you don't know where they're coming in from, um when the churn is so high, you don't know, I mean all this is happening, right? So you have to be prepared two Provisions and provide resource to a very lightweight access edge. >>That's right. And that's why it gets back to what we mentioned is we were taking a step back and thinking about this problem, you know, an M three C became the use case was this is an enterprise I. T. Problem. Right. You know, we have users from around the world that want to access this environment and again we try to hit a really difficult mark, which is secure but collaborative, Right? That's that's not easy, you know? But but again, the only place this environment could take place isn't a cloud based environment, right? Let's be real. You know, 10 years ago. Forget it. You know, Again, maybe it would have been difficult, but now it's just incredible how much they advanced that these real virtual research organizations can start to exist and they become the real partnerships. >>Well, I want to Well, that's a great point. I want to highlight and call out because I've done a lot of these interviews with awards programs over the years and certainly in public sector and open source over many, many years. One of the things open source allows us the code re use and also when you start getting in these situations where, okay, you have a crisis covid other things happen, nonprofits go, that's the same thing. They, they lose their funding and all the code disappears. Saying with these covid when it becomes over, you don't want to lose the momentum. So this whole idea of re use this platform is aged deplatforming of and re factoring if you will, these are two concepts with a cloud enables SAM, I'd love to get your thoughts on this because it doesn't go away when Covid's >>over, research still >>continues. So this whole idea of re platform NG and then re factoring is very much a new concept versus the old days of okay, projects over, move on to the next one. >>No, you're absolutely right. And I think what first drove us is we're taking a step back and and cats, you know, how do we ensure that sustainability? Right, Because my background is actually engineering. So I think about, you know, you want to build things to last and what you just described, johN is that, you know, that, that funding, it peaks, it goes up and then it wanes away and it goes and what you're left with essentially is nothing, you know, it's okay you did this investment in a body of work and it goes away. And really, I think what we're really building are these sustainable platforms that we will actually grow and evolve based upon the research needs over time. And I think that was really a huge investment that both, you know, again and and Cats is made. But NIH is going in a very similar direction. There's a substantial investment, um, you know, made in these, these these these really impressive environments. How do we make sure the sustainable for the long term? You know, again, we just went through this with Covid, but what's gonna come next? You know, one of the research questions that we need to answer, but also open source is an incredibly important piece of this. I think Ben can speak this in a second, all the harmonization work, all that effort, you know, essentially this massive, complex GTL process Is in the N three Seagate hub. So we believe, you know, completely and the open source model a little bit of a flavor on it too though, because, you know, again, back to the sustainability, john, I believe, you know, there's a room for this, this marriage between commercial platforms and open source software and we need both. You know, as we're strong proponents of N cats are both, but especially with sustainability, especially I think Enterprise I. T. You know, you have to have professional grade products that was part of, I would say an experiment we ran out and cast our thought was we can fund academic groups and we can have them do open source projects and you'll get some decent results. But I think the nature of it and the nature of these environments become so complex. The experiment we're taking is we're going to provide commercial grade tools For the academic community and the researchers and let them use them and see how they can be enabled and actually focus on research questions. And I think, you know, N3C, which we've been very successful with that model while still really adhering to the open source spirit and >>principles as an amazing story, congratulated, you know what? That's so awesome because that's the future. And I think you're onto something huge. Great point, Ben, you want to chime in on this whole sustainability because the public private partnership idea is the now the new model innovation formula is about open and collaborative. What's your thoughts? >>Absolutely. And I mean, we uh, volunteer have been huge proponents of reproducibility and openness, um in analyses and in science. And so everything done within the family platform is done in open source languages like python and R. And sequel, um and is exposed via open A. P. I. S and through get repository. So that as SaM says, we've we've pushed all of that E. T. L. Code that was developed within the platform out to the cats get hub. Um and the analysis code itself being written in those various different languages can also sort of easily be pulled out um and made available for other researchers in the future. And I think what we've also seen is that within the data enclave there's been an enormous amount of re use across the different research projects. And so actually having that security in place and making it secure so that people can actually start to share with each other securely as well. And and and be very clear that although I'm sharing this, it's still within the range of the government's requirements has meant that the, the research has really been accelerated because people have been able to build and stand on the shoulders of what earlier projects have done. >>Okay. Ben. Great stuff. 1000 researchers. Open source code and get a job. Where do I sign up? I want to get involved. This is amazing. Like it sounds like a great party. >>We'll send you a link if you do a search on on N three C, you know, do do a search on that and you'll actually will come up with a website hosted by the academic side and I'll show you all the information of how you can actually connect and john you're welcome to come in. Billion by all means >>billions of rows of data being solved. Great tech he's working on again. This is a great example of large scale the modern era of solving problems is here. It's out in the open, Open Science. Sam. Congratulations on your great success. Ben Award winners. You guys doing a great job. Great story. Thanks for sharing here with us in the queue. Appreciate it. >>Thank you, john. >>Thanks for having us. >>Okay. It is. Global public sector partner rewards best Covid solution palantir and and cats. Great solution. Great story. I'm john Kerry with the cube. Thanks for watching. Mm mm. >>Mhm

>> From Santa Clara, California, in the heart of Silicon Valley, it's theCUBE. Covering Technovation's World Pitch 2018. Now here's Sonia Tagare. >> Hi welcome back. I'm Sonia Tagare, here with theCUBE in Santa Clara, California, covering Technovation's World Pitch Summit 2018, a pitch competition in which girls develop apps in order to create positive change in the world. This week 12 finalists are competing for their chance to win the gold or silver scholarships. With us we have, all the way from Egypt, Team Thunderins, and with us is Yara Elkady and Rahma Medhat with their mentor Karim Abdallah. So congratulations and welcome to theCUBE. >> Thank you. >> So your app is called Stray Paws. Tell us more about it. >> So our app aims to solve the problem of street animals. It basically gives the user the ability to adopt animals through our app because in our hometown the adoption process is very difficult, and it also helps to rescue injured animals in the street. >> So what inspired you to create this app? >> Because in Egypt there are several campaigns that are launched every year to poison any street animals which leaves hundreds of cats and dogs dying. So we just want to help the animals because there are no specific rules to protect them, and they are growing in number, like in every street there will be stray animals, so we want to help them to have a better life. And we want stop the killing of them. >> Well that's a great cause to be a part of. So how would a user use the app? >> Okay first of all we have two features the adoption and the rescue. The user could open up our app and there will be three buttons. For the first button is the adopt button and the second is the rescue. He will just pick adopt if he wants to adopt and then he can pick to add a pet for adoption. If you have a pet to offer for adoption, he can add them and all its information in our app, and then other users who wish to adopt could enter another button in our app, and open the screen and just look through a gallery of pets that are available for adoption. And then pick the pet he wants, and then he can contact the owner of the pet directly. >> Wow. So Rahma, maybe you can tell us, how did you guys get involved in Technovation? >> We first of all we have known the competition at March and we only had a month and a half to finish our project. Yes, so we known Karim and he has helped us a lot. Yes and that's all. >> And Karim can you tell us more about how it was mentoring these two? >> Yeah I met them last March. Met them once in physical and after that we did all the job online by online meeting via Skype or messenger or something like that but they did a great job in very short time. >> And how excited are you for their pitch tomorrow? >> Very exciting, we hope to win tomorrow. >> And so how did you all find out about Technovation? >> We found that we were in a workshop for teen entrepreneurs and then they told us about the competition and we found out and we registered the next day. >> Okay. So how do you think Technovation is going to help you in your careers? >> It's going to help me greatly because I wish to be an entrepreneur in the future and make a business, and it inspired me by showing me how it's very possible to make your own business and create your own and fight for what you want, for what you believe in and it's not that hard. If you want it you can do it. And it's very inspirational to be able to make a whole project in a short time and that it works. And it's really great. >> And what advice would you give to young girls who want to join Technovation some day? >> I highly advise them to join because it will inspire them a lot, and show them that it's not impossible to create something that you are proud of and it will be an experience you won't forget. >> And last question, what are you most excited about this week for the competition? >> The pitch because we have been practicing for a long time and I want to just show our project to the world. And we're very excited to pitch in front of many people. >> Well that's great. Thank you so much for being on theCUBE. I am really excited by your app and I hope your pitch goes well. >> Thank you. >> We're here at the Technovation's World Pitch Summit 2018, stay tuned for more. (energetic music)

>> From Orlando, Florida, it's theCUBE, covering SAP Sapphire Now 2018. (upbeat electronic music) Brought to you by NetApp. >> Welcome to theCUBE, I'm Lisa Martin, in the NetApp booth, at Sapphire Now 2018. We are in Orlando, this is an enormous event, there's more than 20,000 people here, and there's about a million people that SAP is expecting to engage online, that's a lot. We're excited to welcome to theCUBE for the first time, Klara Young, the director of Strategic Alliances from AppBuddy and Steven Cox, the head of Global Sales Tools at NetApp, hi, guys. >> Howdy. >> Hello. >> Hi, Lisa. >> Thanks for having us. >> Absolutely, so Klara tell me about AppBuddy. Who are you guys and what do you do? >> So AppBuddy is a provider of a user experience layer that can sit on top of core systems like SAP Sales Cloud or SAP Service Cloud and that really allows the administrators to configure a dream workspace where you can get all the data that you need to work with in one place, and then, the users can interact with that very easily. And so, it's all very user friendly and it allows us to enable sales processes, I want to manage my pipelines, or my accounts, my contacts, all with a very easy to use interface right in the middle of the core system. >> So your target audience would be customers that are already using SAP or customers that are maybe in the transition from, say Oracle to SAP, or something like that? >> So any users that are planning to use SAP or are already using SAP and then want to enhance that user experience, want to give them a faster way to interact with the data, more intuitive, more functionality, right in the same core interface. So those would be good clients for us to enhance that experience, absolutely. >> And what about customers by industry know SAP really kind of being very, very strong in a lot of industries but manufacturing, digital supply chain, but if you look at their customers that are here at Sapphire and there's a million of them, they span so many industries. >> Yeah. >> I think yesterday they were saying HANA is installed in 23,000 customers across 60 industries. Does AppBuddy have a particular suite of industries where you really add even more value, or is it fairly horizontal? >> Oh, that's a real good question. Actually what's the beauty, I think, of AppBuddy's product, is that it is completely agnostic of which process or which industry that you're deploying it in. So you decide what objects, what information I want to put on that. It's not a purpose-built application specifically for one process or one industry. So we serve clients in all sorts of industries. We have a lot in high tech, or in the health care industry, manufacturing, as well but we're not specific to one industry. So really welcoming any use case and we'd love to hear from customers, hey, can I do this? With AppBuddy, could I put this object and that object together and build a process basically, almost in your own app. And we're very looking forward to those feedback from customers and wanting to build those use cases with them. >> And that's been such a huge theme or really an undertone at SAP Sapphire the last few days is how much SAP listens to their customers and really involves them and especially strategic accounts like in a collaborative way and yesterday, Steven, we spoke with your CIO Bill Miller. We talked to him about NetApp and SAP have been partners for 17 years. NetApp is 26 years young now and has undergone a big transformation. Bill talked about some of that yesterday, but you guys also did a big transformation that you were leading within your sales processes and your CRM move into SAP, talk to us about that. What were some of the reasons for that transformation? >> Yeah, it's working with Bill and his team I'm represent the business side and we're looking as NetApp is transforming from a traditional storage company to more a cloud. It's a change in the way we go to market. In the past we shipped boxes to people and they install them or we install them. And in the future, we're looking to more services and cloud-oriented things. And so the kind of infrastructure that we built up to support our large sales force doesn't work as well in the new world. And so we about two years ago, started a pretty big transformation journey to move from this more old-school hardware to more new cloud and through that process, we needed to change our systems. Changing out our CRM became an important component of that 'cause we need more flexibility and we needed to sort of be more contemporary and we worked with AppBuddy and our old system, we used to have Salesforce, and the field was pretty used to using that kind of interface. And when you build stuff like this, you don't always know how important it is to the field. You know, you have guesses at it, and as we looked at things that we had to do to prepare to move this was always something on our list that we felt like was important but we weren't able to do it immediately. It took us an extra release to get it out, so an extra few months. And through those few months, we learned the hard way that the field really wanted it. It was really impacting them. And we had guessed that we thought it was somewhere around 25% improvement in their overall productivity. And what we found was that it's at least that, if not more. >> Wow. >> Because they came back and said, "We can't do our jobs "without this, you guys gotta get it for us." >> So they said either AppBuddy or the highway? >> Yeah, pretty much. (laughs) Pretty much, AppBuddy or they're not happy. They're not happy all the time anyway but I feel like they-- >> Salespeople. >> That by getting that to 'em we were enabling them to go faster in a few things. And it's simple, it's hard to understand, I think, for everybody, it's a simple layer. Whenever you build a CRM or any kinda system, your job is to collect information and then display it back, make it easy to change. And the way CRMs typically work today is, you have a list for you of stuff, opportunities, or new registrations, quotes and you just have to look at that list and then pick one you wanna edit and then go to this details screen and look at it and then go to the edit screen and then edit it and then go back, back, back. And what AppBuddy provides, is it takes all that noise and makes it into one screen so that you can just simply make and change the data, the way you would expect to on a spreadsheet, in a simple experience. And once you give it to the reps, they sorta expect that as the tablestakes, and it's a gap if you look at most CRMs they don't have this kind of in-line edit capability out of the box. And so this is a great, SAP is really excited about this 'cause it gives them a way to solve this problem without having to build it themselves and that's the beauty of these kind of infrastructures where you can add capabilities by just plugging something in. >> Right. >> And it speaks using the APIs to the tool. And so all the rules that we build around the data about who should access it, what should happen when they change stuff, should we protect data. All that is followed, because AppBuddy works right through our APIs, through the SAP provides. And so it doesn't require a lot extra coding or anything. In fact. >> That's right. >> IT guys are standing over there somewhere. They don't like it 'cause I do it myself. I'll actually build experiences for the field really quickly 'cause that I can make a quick custom business process to support something that's needed. >> So, on the AppBuddy website, Klara, I saw, I love stats, and you guys said, we can save time and improve enterprise productivity by 5X to 10X. >> That's right. >> Those are big numbers. >> That's right. >> And you were saying there's been a massive improvement in employment productivity and I imagine in terms of the speed is essential. You know, we were talking, one of the underlying themes here at Sapphire, this year, is the intelligent enterprise, which demands the integration and the embedding of advanced emerging technologies, AI, for example, to make these enterprises truly intelligent, connecting supply chain and demand chain and it's essential, its table stakes these days. >> Yep. >> To be able to drive things faster, right? So that you guys can get what your customers need faster. >> Yep. >> So, you mentioned that huge productivity boost there but also that you were familiar with AppBuddy before your sales guys and gals were like, hey we need to have something that we're familiar with to be able to make our jobs better, so you're also doing, it sounds like a pretty good job of listening to your customers. >> Yeah, I try >> Who are probably very vocal. >> I try, I try, I mean, it's a hard job because you're sort of channeling the sales guys and in our world they're very different. In Europe, they sell very different than they sell in the US and APAC is different. And even within different sections of Europe or in the US, they act differently, and our goal is to try to streamline that so that they can act as much the same as they can across that and we can deploy sort of one experience without having to customize it totally. But tools like AppBuddy give us the ability to be much more targeted and flexible. A simple example I've been given pretty commonly is we have our sales kick-off this week also in Las Vegas and all of our sales guys are going there to learn about how to sell better, how to sell our new products and solutions and leverage some of our improved selling processes and before they go there, we wanted to have them identify a few key opportunities they're working on to say hey, these are the one's that I'm gonna use as my work case as I'm learning these new things, and in theory as we go through and finish our sales kick-off they go back and start the selling process those opportunities should sell at a higher rate then the other opportunities. And so to make that work, I configured a grid, or an AppBuddy list view, and all I put on it was the list of opportunities in one field that says, this is appropriate for our kick-off and so, instead of putting it in the middle of a very complex world, I sent 'em an email, they had a list and they just had to say this guy, this guy, and that guy, and that's all they had to do. And so our response rate on something, which if you sent a list of things to do for the field, they're not gonna respond. They're busy, they're makin' money. But in this case, because it was tied to the new learning and they felt value in it, 80% of 'em responded within 10 days. >> Yeah, wow. >> And you know, you just don't see that kind of response. But it works because it's a simple experience, right? The only thing they could do with that, they get an email that says, do this, they open it, they see the list, they click, yes, yes, yes, and it's done. And that's a whole business process that in the old days could take months to prepare for and create fields and deploy new code and do all the things you have to do. And in this case, I can create the fields in a day, create the grid in five minutes, and then I put it in an email, and done, you know? So this is where you take things to the next level and make it easier for the sales reps to do the things they need to do help us all be successful. >> Did it also sort of abstract, I can imagine, the fundamental challenges that go along with replacing an entire new CRM, going from Salesforce to SAP. >> Yeah. >> Has that been able to help kind of abstract some of the inner machinations of that so that the sales people can just focus on we know this same interface? >> It totally does, because the list views that we create are only the things they have to have. In any system like this you have a bunch of other fields that are specialized for, say, we have a professional services group and they really want to know blah blah but most sales reps, they don't deal with that at all. But you need it on the page, I need to build that. In these views, I can build it for a sales rep view that is perfect for them, right? Meaning there's no extra fields on that list. It's what you need to get your job done. And so it's like a laser focus, and then I can build a separate one for a different kind of role and give that one to them. So without changing the tool, I'm just creating a focused experience. It all uses the same things. You need sorting, you need filtering, you need a simple edit and that's all available and once they learn that core capability then the rest just kind of falls in. >> And then from your perspective it's probably business outcomes that, George, your CEO, is going to be really excited about, cost savings, employee productivity. >> Yep. >> I'm wondering though, we're talking about it in the context of what you're doing within your sales processes and your CRM. Klara, so obviously working with SAP, are there other businesses processes that AppBuddy can sit on top of and help to streamline the interface with? >> Yeah, great question, and actually thank you for asking 'cause I was gonna say, we talked a lot about sales but we could be enabling any other processes as well and services, for example, is a big one. I've got a list, a queue of cases, I want to make quick updates to that. I want to change things or I'm doing some forecasting, some account planning, but our vision, ultimately is to be able to bring from lead to cache all processes and again tailor it for each user, role specifically for them and we're not giving the solution, the customers are defining what do they need for each one of those processes and that's the power, I think, of this configurability and agility that you get. It's not built and hard coded. It's really you who puts it together. But again, we really have that vision of not only linking the CRM data but ultimately we would love to be able to get more use cases of, hey the CRM data together maybe with your ERP data, I want to see my opportunities but I also want to see the orders and I want to see the invoices so get really this 360 view of your customers that I think we've talked a lot about, even Bill McDermott was talking about it. It's so essential and critical to be customer focused is to have that visibility and with this application where you can basically pull data from wherever you need it for that specific view, you give your users that full visibility and therefore much faster answer questions, be in contexts, not lose critical information of a customer. >> Right, you're right, Bill McDermott did mention yesterday in the keynote about really what, SAP's been pretty vocal about for a while, they want to be one of the top 10 global brands. >> Mm-hmm. >> Right. >> Most valuable brands, and they want to be up there with Apple and Google. >> Right. >> And Coca-Cola, and that's for a software company that sells invisible technology, they're on their way. They're now ranked number 17, but he talked about this. >> Yeah. >> Kind of unique position that SAP's in to link and synchronize >> That's right. >> The demand chain with the supply chain >> That's right. >> Which is pretty revolutionary but ultimately, it's not about just having a 360 view of sales automation, it's of the entire customer process. >> Correct, yeah. >> So Steven, sounds like you are a rockstar in that app, with your sales guys going, hey, we need this AppBuddy technology to make our lives easier, our jobs easier. Do you foresee rolling the AppBuddy technology out to include other business processes? >> All the time, yeah, it's all about the data. And change management or getting the field to act in the same way is really hard and it doesn't sound like it should be but, (Lisa laughs) it's like having 1,000 cats on the table and getting them all to look one direction, it just doesn't happen, right? So my job is to make that and if I can have it with a single user experience, right, without having different flavors of screens and extra fields and narrow it down to what they need, bringing whatever data they need to flow from end to end it makes life easier and I've got 'em all trained. You know, we had very high usage in our previous platform and we're building now from that but they all know how to use it now so I don't have to train the cats to look in the same direction, they all know where to go. All I gotta do is add the data, right? And if you look at NetApp's transformation, from a storage company to a data company my job is really data, it's not about the tools as much. It's about how do we facilitate the salespeople to do more with what they have, right? How do I do a cross-sell, up-sell, how do I get them enabled so they can move faster so that's innate and built into what they do? >> Yeah. >> And in that you have to build, and we were just at another panel talking with SAP about, you have to give back to the sales reps and to the people doing the data 'cause CRM's not fun, I mean, it's not like, hey, I'm gonna go play my CRM tonight. (laughs) It's a different deal. CRM requires work and so you need to give them stuff back. Do machine learning, do things that provide scoring, show the probability of close, help them be more successful at their job and bring the data together in one spot. >> You know, I think yesterday one of the themes also was data and trust, the new currency, right? If you can't access it and extract valuable insights immediately and act on them then you risk being usurped by your competition. So being able to enable the data to be accessible, insights gleaned as quickly as possible, you must be the king. >> Well, I don't know about that. >> The data king. (laughs) >> Yeah, it's definitely our job. >> But as we wrap here in the last few seconds, digital transformation and every company has to go through it or you're not relevant but that requires a cultural transformation as well. >> It does. >> And it sounds like what you guys are doing together is helping that at least from the sales force's perspective of where change has to happen. >> Yep. >> Not only is it improving the efficiency of your SAP environment, your CRM environment, but it's also helping, sounds like, from a cultural perspective, as, hey, we've got to go through this transformation, let's make it where we can simplify, let's do that. >> Very much so. Just like I was talking about the cat problem. You've got the reps that are used to doing something the way and you're saying hey, we're gonna evolve and do something different and that change is rough and people don't feel like it's the right thing at times. The great news with this change and the timing of it is that when you're moving from one platform to the other, it's the one time in the life cycle of these products where you can make significant change, drop whole business process and they won't even notice it. I dropped three quarters of the stuff that we had before and just didn't build it. And I don't have people coming to me going, hey, I really miss doing that, and that's good news, we're helping drive the change. >> Yeah. >> Well, thank so much you guys for stopping by theCUBE and Klara telling us about AppBuddy, what you guys do, how you're working together with NetApp and SAP. We appreciate your time. >> Thank you so much. >> Thank you for the opportunity, Lisa, thank you. >> We want to thank you for watching theCUBE. I'm Lisa Martin at SAP Sapphire 2018. Thanks for watching. (upbeat electronic music)

>> Announcer: Live from San Francisco, it's theCube, covering Spark Summit 2017, brought to you by Databricks. >> Welcome back to theCube at Spark Summit 2017. I don't know about you, George, I'm having a great time learning from all of our attendees. >> We've been absorbing now for almost two days. >> Yeah, well, and we're about to absorb a little bit more here, too, because the next guest, I looking forward to, I saw his name on the schedule, all right, that's the guy who talks about herding cats, it's John Cavanaugh, Master Architect from HP. John, welcome to the show. >> Great, thanks for being here. >> Well, I did see, I don't know if it's about cats in the Internet, but either cats or self-driving cars, one of the two in analogies. But talk to us about your session. Why did you call it Herding Cats, and is that related to maybe the organization at HP? >> Yeah, there's a lot of organizational dynamics as part of our migration at Spark. HP is a very distributed organization, and it has had a lot of distributed autonomy, so, you know, trying to get centralized activity is often a little challenging. You guys have often heard, you know, I am from the government, I'm here to help. That's often the kind of shields-up response you will get from folks, so we got a lot of dynamics in terms of trying to bring these distributed organizations on board to a new common platform, and a allay many of the fears that they had with making any kind of a change. >> So, are you centered at a specific division? >> So, yes, I'm the print platforms and future technology group. You know, there's two large business segments with HP. There's our personal systems group that produces everything from phones to business PCs to high-end gaming. But I'm in the printing group, and while many people are very familiar with your standard desktop printer, you know, the printers we sell really vary from a very small product we call Sprocket, it fits in your hand, battery-operated, to literally a web press that's bigger than your house and prints at hundreds of feet per minute. So, it's a very wide product line, and it has a lot of data collection. >> David: Do you have 3D printing as well? >> We do have 3D printing as well. That's an emergent area for us. I'm not super familiar with that. I'm mostly on the 2D side, but that's a very exciting space as well. >> So tell me about what kind of projects that you're working on that do require that kind of cross-team or cross-departmental cooperation. >> So, you know, in my talk, I talked about the Wild West Era of Big Data, and that was prior to 2015, and we had a lot of groups that were standing up all kinds of different big data infrastructures. And part of this stems from the fact that we were part of HP at the time, and we could buy servers and racks of servers at cost. Storage was cheap, all these things, so they sprouted up everywhere. And, around 2015, everybody started realizing, oh my God, this is completely fragmented. How do we pull things back together? And that's when a lot of groups started trying to develop platformish types of activities, and that's where we knew we needed to go, but there was even some disagreement from different groups, how do we move forward. So, there's been a lot of good work within HP in terms of creating a virtual community, and Spark really kind of caught on pretty quickly. Many people were really tired of kind of Hadoop. There were a lot of very opinionated models in Hadoop, where Spark opens up a lot more into the data science community. So, that went really well, and we made a big push into AWS for much of our cloud activities, and we really ended up then pretty quickly with Databricks as an enterprise partner for us. >> And so, George, you've done a lot of research. I'm sure you talked to enterprise companies along the way. Is this a common issue with big enterprises? >> Well, for most big data projects they've started, the ones we hear a lot about is there's a mandate from the CIO, we need a big data strategy, and so some of those, in the past, stand up five or 10-node Hadoop cluster and run some sort of pilot and say, this is our strategy. But is sounds like you herded a lot of cats... >> We had dozens of those small Hadoop clusters all around the company. (laughter) >> So, how did you go about converting that energy, that excess energy towards something more harmonized around Databricks? >> Well, a lot of people started recognizing we had a problem, and this really wasn't going to scale, and we really needed to come up with a broader way to share things across the organization. So, the timing was really right, and a lot of people were beginning to understand that. And, you know, we said for us, probably about five different kind of key decisions we ended up making. And part of the whole strategy was to empower the businesses. As I have mentioned, we are a very distributed organization, so, you can't really dictate the businesses. The businesses really need the owners' success. And one of the decisions that was made, it might be kind of controversial for many CIOs, is that we've made a big push on cloud-hosted and business-owned, not IT-owned. And one of the real big reasons for that is we were no longer viewing data and big data as kind of a business-intelligence activity or a standardized reporting activity. We really knew that, to be successful moving forward, is needed to be built into our products and services, and those products and services are managed by the businesses. So, it can't be something that would be tossed off to an IT organization. >> So that the IT organization, then, evolved into being more of an innovative entity versus a reactive or supportive entity for all those different distributing groups. >> Well, in our regard, we've ended up with AWS as part of our activity, and, really, much of our big data activities are driven by the businesses. The connections we have with IT are more related to CRM and product data master sheets and selling in channels and all that information. >> But if you take a bunch of business-led projects and then try and centralize some aspect of them, wouldn't IT typically become the sort of shared infrastructure architecture advisor for that, and then the businesses now have a harmonized platform on which they can build shared data sets? >> Actually, in our case, that's what we did. We had a lot of our businesses that already had significant services hosted in AWS. And those were very much part of the high-data generators. So, it became a very natural evolution to continue with some of our AWS relationships and continue on to Databricks. So, as an organization today, we have three kind of main buckets for our Databricks, but, you know, any business, they can get their accounts. We try and encourage everything to get into a data link, and that's three, and Parquet formats, one of the decisions that was adapted. And then, from there, people can begin to move. You know, you can get notebooks, you can share notebooks, you can look at those things. You know, the beauty of Databricks and AWS is instant on. If I want to play around with something with a half a dozen nodes, it's great. If I need a thousand for a workload, boom, I've got it! I know, kind of others, then, with this cost and the value returned, there's really no need for permissions or coordination with other entities, and that's kind of what we wanted the businesses to have that autonomy to drive their business success. >> But, does there not to be some central value added in the way of, say, data curation through a catalog or something like that? >> Yes, so, this is not necessarily a model where all the businesses are doing all kinds of crazy things. One of the things that we shepherded by one of our CTOs and the other functions, we ended up creating a virtual community within HP. This kind of started off with a lot of "tribal elders" or "tribal leaders." With this virtual community, today we get together every two weeks, and we have presentations and discussions on all things from data science into machine learning, and that's where a lot of this activity around how do we get better at sharing. And this is fostered, kind of splinters off for additional activity. So we have one on data telemetry within our organization. We're trying to standardize more data formats and schemas for those so we can have more broader sharing. So, these things have been occurring more organically as part of a developer enablement kind of moving up rather than more of kind of dictates moving down. >> That's interesting. Potentially, really important, when you say, you're trying to standardize some of the telemetry, what are you instrumenting. Is it just all the infrastructure or is it some of the products that HP makes? >> It's definitely the products and the software. You know, like I said, we manage a huge spectrum of print products, and my apologies if I'm focusing on it, but that is what I know the best. You know, we've actually been doing telemetry and analysis since the late 90s. You know, we wanted to understand use of supplies and usage so we could do our own forecasting, and that's really, really grown over the years. You know, now, we have parts of our services organization management services, where they're offering big data analytics as part of the package, and we provide information about predictive failure of parts. And that's going to be really valuable for some of our business partners that allows them. We have all kinds fancy algorithms that we work on. The customers have specific routes that they go for servicing, and we may be able to tell them, hey, in a certain time period, we think these devices in your field so you can coordinate your route to hit those on an efficient route rather than having to make a single truck roll for one repair, and do that before a customer experiences a problem. So, it's been kind of a great example of different ways that big data can impact the business. >> You know, I think Ali mentioned in the keynote this morning about the example of a customer getting a notification that their ink's going to run out, and the chance that you get to touch that customer and get them to respond and buy, you could make millions of dollar difference, right? Let's talk about some of the business outcomes and the impact that some of your workers have done, and what it means, really, to the business. >> Right now, we're trying to migrate a lot of legacy stuff, and you know, that's kind of boring. (laughs) It's just a lot of work, but there are things that need to happen. But there's really the power of the big data platform has been really great with Databricks. I know, John Landry, one of our CTOs, he's in the personal systems group. He had a great example on some problems they had with batteries and laptops, and, you know, they have a whole bunch of analytics. They've been monitoring batteries, and they found a collection of batteries that experienced very early failure rates. I happen to be able to narrow it down to specific lots from a specific supplier, and they were able to reach out to customers to get those batteries replaced before they died. >> So, a mini-recall instead of a massive PR failure. (laughs) >> You know, it was really focused on, you know, customers didn't even know they were going to have a problem with these batteries, that they were going to die early. You know, you got to them ahead of time, told them we knew this was going to be a problem and try to help them. I mean, what a great experience for a customer. (laughs) That's just great. >> So, once you had this telemetry, and it sounds like a bunch of shared repositories, not one intergalactic one. What were some of the other use cases like, you know, like the battery predictive failure type scenarios. >> So, you know, we have some very large gaps, or not gaps, with different categories. We have clearly consumer products. You know, you sell millions and millions of those, and we have little bit of telemetry with those. I think we want to understand failures and ink levels and some of these other things. But, on our commercial web presses, these very large devices, these are very sensitive. These things are down, they have a big problem. So, these things are generating all kinds of data. All right, we have systems on a premise with customers that are alerting them to potential failures, and there's more and more activity going on there to understand predictive failure and predictive kind of tolerance slippages. I'm not super familiar with that business, but I know some guys that they've started introducing more sensors into products, specifically so they can get more data, to understand things. You know, slight variations in tensioning and paper, you know, these things that are running hundreds of feet per minute can have a large impact. So, I think that's really where we see more and more of the value coming from is being able to return that value back to the customer, not just help us make better decisions, but to get that back to the customer. You know, we're talking about expanding more customer-facing analytics in these cases, or we'll expose to customers some of the raw data, and they can build their own dashboards. Some of these industries have traditionally been very analog, so this move to digital web process and this mountain of data is a little new for them, but HP can bring a lot to the table in terms of our experience in computing and big data to help them with their businesses. >> All right, great stuff. And we just got a minute to go before we're done. I have two questions for you, the first is an easy yes/no question. >> John: Okay. >> Is Purdue going to repeat as Big 10 champ in basketball? >> Oh, you know, I don't know. (laughs) I hope so! >> We both went to Purdue. >> I'm more focused on the Warriors winning. (laughter) >> All right, go Warriors! And, the real question is, what surprised you the most? This is your first Spark Summit. What surprised you the most about the event? >> So, you know, you see a lot of Internet-born companies, and it's amazing how many people have just gone fully native with Spark all over the place, and it's a beautiful thing to see. You know, in larger enterprises, that transition doesn't happen like that. I'm kind of jealous. (laughter) We have a lot more things slug through, but the excitement here and all the things that people are working on, you know, you can only see so many tracks. I'm going to have to spend two days when I get back, just watching the videos on all of the tracks I couldn't attend. >> All right, Internet-born companies versus the big enterprise. Good luck herding those cats, and thank you for sharing your story with us today and talking a little bit about the culture there at HP. >> John: Thank you very much. >> And thank you all for watching this segment of theCube. Stay with us, we're still covering Spark Summit 2017. This is Day Two, and we're not done yet. We'll see you in a few minutes. (theCube jingle)