>> From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a Cube Conversation. >> Hi everyone, this is Dave Vellante and welcome back to the Cube's coverage of the MIT CDOIQ. God, we've been covering this show since probably 2013, really trying to understand the intersection of data and organizations and data quality and how that's evolved over time. And with me to discuss these issues is Krishna Cheriath, who's the Vice President and Chief Data Officer, Bristol-Myers Squibb. Krishna, great to see you, thanks so much for coming on. >> Thank you so much Dave for the invite, I'm looking forward to it. >> Yeah first of all, how are things in your part of the world? You're in New Jersey, I'm also on the East coast, how you guys making out? >> Yeah, I think these are unprecedented times all around the globe and whether it is from a company perspective or a personal standpoint, it is how do you manage your life, how do you manage your work in these unprecedented COVID-19 times has been a very interesting challenge. And to me, what is most amazing has been, I've seen humanity rise up and so to our company has sort of snap to be able to manage our work so that the important medicines that have to be delivered to our patients are delivered on time. So really proud about how we have done as a company and of course, personally, it has been an interesting journey with my kids from college, remote learning, wife working from home. So I'm very lucky and blessed to be safe and healthy at this time. So hopefully the people listening to this conversation are finding that they are able to manage through their lives as well. >> Obviously Bristol-Myers Squibb, very, very strong business. You guys just recently announced your quarter. There's a biologics facility near me in Devon's, Massachusetts, I drive by it all the time, it's a beautiful facility actually. But extremely broad portfolio, obviously some COVID impact, but you're managing through that very, very well, if I understand it correctly, you're taking a collaborative approach to a COVID vaccine, you're now bringing people physically back to work, you've been very planful about that. My question is from your standpoint, what role did you play in that whole COVID response and what role did data play? >> Yeah, I think it's a two part as you rightly pointed out, the Bristol-Myers Squibb, we have been an active partner on the the overall scientific ecosystem supporting many different targets that is, from many different companies I think. Across biopharmaceuticals, there's been a healthy convergence of scientific innovation to see how can we solve this together. And Bristol-Myers Squibb have been an active participant as our CEO, as well as our Chief Medical Officer and Head of Research have articulated publicly. Within the company itself, from a data and technology standpoint, data and digital is core to the response from a company standpoint to the COVID-19, how do we ensure that our work continues when the entire global workforce pivots to a kind of a remote setting. So that really calls on the digital infrastructure to rise to the challenge, to enable a complete global workforce. And I mean workforce, it is not just employees of the company but the all of the third-party partners and others that we work with, the whole ecosystem needs to work. And I think our digital infrastructure has proven to be extremely resilient than that. From a data perspective, I think it is twofold. One is how does the core book of business of data continue to drive forward to make sure that our companies key priorities are being advanced. Secondarily, we've been partnering with a research and development organization as well as medical organization to look at what kind of real world data insights can really help in answering the many questions around COVID-19. So I think it is twofold. Main summary; one is, how do we ensure that the data and digital infrastructure of the company continues to operate in a way that allows us to progress the company's mission even during a time when globally, we have been switched to a remote working force, except for some essential staff from lab and manufacturing standpoint. And secondarily is how do we look at the real-world evidence as well as the scientific data to be a good partner with other companies to look at progressing the societal innovations needed for this. >> I think it's a really prudent approach because let's face it, sometimes one shot all vaccine can be like playing roulette. So you guys are both managing your risk and just as I say, financially, a very, very successful company in a sound approach. I want to ask you about your organization. We've interviewed many, many Chief Data Officers over the years, and there seems to be some fuzziness as to the organizational structure. It's very clear with you, you report in to the CIO, you came out of a technical bag, you have a technical degree but you also of course have a business degree. So you're dangerous from that standpoint. You got both sides which is critical, I would think in your role, but let's start with the organizational reporting structure. How did that come about and what are the benefits of reporting into the CIO? >> I think the Genesis for that as Bristol-Myers Squibb and when I say Bristol-Myers Squibb, the new Bristol-Myers Squibb is a combination of Heritage Bristol-Myers Squibb and Heritage Celgene after the Celgene acquisition last November. So in the Heritage Bristol-Myers Squibb acquisition, we came to a conclusion that in order for BMS to be able to fully capitalize on our scientific innovation potential as well as to drive data-driven decisions across the company, having a robust data agenda is key. Now the question is, how do you progress that? Historically, we had approached a very decentralized mechanism that made a different data constituencies. We didn't have a formal role of a Chief Data Officer up until 2018 or so. So coming from that realization that we need to have an effective data agenda to drive forward the necessary data-driven innovations from an analytic standpoint. And equally importantly, from optimizing our execution, we came to conclusion that we need an enterprise-level data organization, we need to have a first among equals if you will, to be mandated by the CEO, his leadership team, to be the kind of an orchestrator of a data agenda for the company, because data agenda cannot be done individually by a singular CDO. It has to be done in partnership with many stakeholders, business, technology, analytics, et cetera. So from that came this notion that we need an enterprise-wide data organization. So we started there. So for awhile, I would joke around that I had all of the accountabilities of the CDO without the lofty title. So this journey started around 2016, where we create an enterprise-wide data organization. And we made a very conscious choice of separating the data organization from analytics. And the reason we did that is when we look at the bowl of Bristol-Myers Squibb, analytics for example, is core and part of our scientific discovery process, research, our clinical development, all of them have deep data science and analytic embedded in it. But we also have other analytics whether it is part of our sales and marketing, whether it is part of our finance and our enabling functions they catch all across global procurement et cetera. So the world of analytics is very broad. BMS did a separation between the world of analytics and from the world of data. Analytics at BMS is in two modes. There is a central analytics organization called Business Insights and Analytics that drive most of the enterprise-level analytics. But then we have embedded analytics in our business areas, which is research and development, manufacturing and supply chain, et cetera, to drive what needs to be closer to the business idea. And the reason for separating that out and having a separate data organization is that none of these analytic aspirations or the business aspirations from data will be met if the world of data is, you don't have the right level of data available, the velocity of data is not appropriate for the use cases, the quality of data is not great or the control of the data. So that we are using the data for the right intent, meeting the compliance and regulatory expectations around the data is met. So that's why we separated out that data world from the analytics world, which is a little bit of a unique construct for us compared to what we see generally in the world of CDOs. And from that standpoint, then the decision was taken to make that report for global CIO. At Bristol-Myers Squibb, they have a very strong CIO organization and IT organization. When I say strong, it is from this lens standpoint. A, it is centralized, we have centralized the budget as well as we have centralized the execution across the enterprise. And the CDO reporting to the CIO with that data-specific agenda, has a lot of value in being able to connect the world of data with the world of technology. So at BMS, their Chief Data Officer organization is a combination of traditional CDO-type accountabilities like data risk management, data governance, data stewardship, but also all of the related technologies around master data management, data lake, data and analytic engineering and a nascent AI data and technology lab. So that construct allows us to be a true enterprise horizontal, supporting analytics, whether it is done in a central analytics organization or embedded analytics teams in the business area, but also equally importantly, focus on the world of data from operational execution standpoint, how do we optimize data to drive operational effectiveness? So that's the construct that we have where CDO reports to the CIO, data organization separated from analytics to really focus around the availability but also the quality and control of data. And the last nuance that is that at BMS, the Chief Data Officer organization is also accountable to be the Data Protection Office. So we orchestrate and facilitate all privacy-related actions across because that allows us to make sure that all personal data that is collected, managed and consumed, meets all of the various privacy standards across the world, as well as our own commitments as a company from across from compliance principles standpoint. >> So that makes a lot of sense to me and thank you for that description. You're not getting in the way of R&D and the scientists, they know data science, they don't need really your help. I mean, they need to innovate at their own pace, but the balance of the business really does need your innovation, and that's really where it seems like you're focused. You mentioned master data management, data lakes, data engineering, et cetera. So your responsibility is for that enterprise data lifecycle to support the business side of things, and I wonder if you could talk a little bit about that and how that's evolved. I mean a lot has changed from the old days of data warehouse and cumbersome ETL and you mentioned, as you say data lakes, many of those have been challenging, expensive, slow, but now we're entering this era of cloud, real-time, a lot of machine intelligence, and I wonder if you could talk about the changes there and how you're looking at and thinking about the data lifecycle and accelerating the time to insights. >> Yeah, I think the way we think about it, we as an organization in our strategy and tactics, think of this as a data supply chain. The supply chain of data to drive business value whether it is through insights and analytics or through operation execution. When you think about it from that standpoint, then we need to get many elements of that into an effective stage. This could be the technologies that is part of that data supply chain, you reference some of them, the master data management platforms, data lake platforms, the analytics and reporting capabilities and business intelligence capabilities that plug into a data backbone, which is that I would say the technology, swim lane that needs to get right. Along with that, what we also need to get right for that effective data supply chain is that data layer. That is, how do you make sure that there is the right data navigation capability, probably you make sure that we have the right ontology mapping and the understanding around the data. How do we have data navigation? It is something that we have invested very heavily in. So imagine a new employee joining BMS, any organization our size has a pretty wide technology ecosystem and data ecosystem. How do you navigate that, how do we find the data? Data discovery has been a key focus for us. So for an effective data supply chain, then we knew that and we have instituted our roadmap to make sure that we have a robust technology orchestration of it, but equally important is an effective data operations orchestration. Both needs to go hand in hand for us to be able to make sure that that supply chain is effective from a business use case and analytic use standpoint. So that has led us on a journey from a cloud perspective, since you refer that in your question, is we have invested very heavily to move from very disparate set of data ecosystems to a more converse cloud-based data backbone. That has been a big focus at the BMS since 2016, whether it is from a research and development standpoint or from commercialization, it is our word for the sales and marketing or manufacturing and supply chain and HR, et cetera. How do we create a converged data backbone that allows us to use that data as a resource to drive many different consumption patterns? Because when you imagine an enterprise of our size, we have many different consumers of the data. So those consumers have different consumption needs. You have deep data science population who just needs access to the data and they have data science platforms but they are at once programmers as well, to the other end of the spectrum where executives need pre-packaged KPIs. So the effective orchestration of the data ecosystem at BMS through a data supply chain and the data backbone, there's a couple of things for us. One, it drives productivity of our data consumers, the scientific researchers, analytic community or other operational staff. And second, in a world where we need to make sure that the data consumption appalls ethical standards as well as privacy and other regulatory expectations, we are able to build it into our system and process the necessary controls to make sure that the consumption and the use of data meets our highest trust advancements standards. >> That makes a lot of sense. I mean, converging your data like that, people always talk about stove pipes. I know it's kind of a bromide but it's true, and allows you to sort of inject consistent policies. What about automation? How has that affected your data pipeline recently and on your journey with things like data classification and the like? >> I think in pursuing a broad data automation journey, one of the things that we did was to operate at two different speed points. In a historically, the data organizations have been bundled with long-running data infrastructure programs. By the time you complete them, their business context have moved on and the organization leaders are also exhausted from having to wait from these massive programs to reach its full potential. So what we did very intentionally from our data automation journey is to organize ourselves in two speed dimensions. First, a concept called Rapid Data Lab. The idea is that recognizing the reality that the data is not well automated and orchestrated today, we need a SWAT team of data engineers, data SMEs to partner with consumers of data to make sure that we can make effective data supply chain decisions here and now, and enable the business to answer questions of today. Simultaneously in a longer time horizon, we need to do the necessary work of moving the data automation to a better footprint. So enterprise data lake investments, where we built services based on, we had chosen AWS as the cloud backbone for data. So how do we use the AWS services? How do we wrap around it with the necessary capabilities so that we have a consistent reference and technical architecture to drive the many different function journeys? So we organized ourselves into speed dimensions; the Rapid Data Lab teams focus around partnering with the consumers of data to help them with data automation needs here and now, and then a secondary team focused around the convergence of data into a better cloud-based data backbone. So that allowed us to one, make an impact here and now and deliver value from data to the dismiss here and now. Secondly, we also learned a lot from actually partnering with consumers of data on what needs to get adjusted over a period of time in our automation journey. >> It makes sense, I mean again, that whole notion of converged data, putting data at the core of your business, you brought up AWS, I wonder if I could ask you a question. You don't have to comment on specific vendors, but there's a conversation we have in our community. You have AWS huge platform, tons of partners, a lot of innovation going on and you see innovation in areas like the cloud data warehouse or data science tooling, et cetera, all components of that data pipeline. As well, you have AWS with its own tooling around there. So a question we often have in the community is will technologists and technology buyers go for kind of best of breed and cobble together different services or would they prefer to have sort of the convenience of a bundled service from an AWS or a Microsoft or Google, or maybe they even go best of breeds for all cloud. Can you comment on that, what's your thinking? >> I think, especially for organizations, our size and breadth, having a converged to convenient, all of the above from a single provider does not seem practical and feasible, because a couple of reasons. One, the heterogeneity of the data, the heterogeneity of consumption of the data and we are yet to find a single stack provider who can meet all of the different needs. So I am more in the best of breed camp with a few caveats, a hybrid best of breed, if you will. It is important to have a converged the data backbone for the enterprise. And so whether you invest in a singular cloud or private cloud or a combination, you need to have a clear intention strategy around where are you going to host the data and how is the data is going to be organized. But you could have a lot more flexibility in the consumption of data. So once you have the data converged into, in our case, we converged on AWS-based backbone. We allow many different consumptions of the data, because I think the analytic and insights layer, data science community within R&D is different from a data science community in the supply chain context, we have business intelligence needs, we have a catered needs and then there are other data needs that needs to be funneled into software as service platforms like the sales forces of the world, to be able to drive operational execution as well. So when you look at it from that context, having a hybrid model of best of breed, whether you have a lot more convergence from a data backbone standpoint, but then allow for best of breed from an analytic and consumption of data is more where my heart and my brain is. >> I know a lot of companies would be excited to hear that answer, but I love it because it fosters competition and innovation. I wish I could talk for you forever, but you made me think of another question which is around self-serve. On your journey, are you at the point where you can deliver self-serve to the lines of business? Is that something that you're trying to get to? >> Yeah, I think it does. The self-serve is an absolutely important point because I think the traditional boundaries of what you consider the classical IT versus a classical business is great. I think there is an important gray area in the middle where you have a deep citizen data scientist in the business community who really needs to be able to have access to the data and I have advanced data science and programming skills. So self-serve is important but in that, companies need to be very intentional and very conscious of making sure that you're allowing that self-serve in a safe containment sock. Because at the end of the day, whether it is a cyber risk or data risk or technology risk, it's all real. So we need to have a balanced approach between promoting whether you call it data democratization or whether you call it self-serve, but you need to balance that with making sure that you're meeting the right risk mitigation strategy standpoint. So that's how then our focus is to say, how do we promote self-serve for the communities that they need self-serve, where they have deeper levels of access? How do we set up the right safe zones for those which may be the appropriate mitigation from a cyber risk or data risk or technology risk. >> Security pieces, again, you keep bringing up topics that I could talk to you forever on, but I heard on TV the other night, I heard somebody talking about how COVID has affected, because of remote access, affected security. And it's like hey, give everybody access. That was sort of the initial knee-jerk response, but the example they gave as well, if your parents go out of town and the kid has a party, you may have some people show up that you don't want to show up. And so, same issue with remote working, work from home. Clearly you guys have had to pivot to support that, but where does the security organization fit? Does that report separate alongside the CIO? Does it report into the CIO? Are they sort of peers of yours, how does that all work? >> Yeah, I think at Bristol-Myers Squibb, we have a Chief Information Security Officer who is a peer of mine, who also reports to the global CIO. The CDO and the CSO are effective partners and are two sides of the coin and trying to advance a total risk mitigation strategy, whether it is from a cyber risk standpoint, which is the focus of the Chief Information Security Officer and whether it is the general data consumption risk. And that is the focus from a Chief Data Officer in the capacities that I have. And together, those are two sides of a coin that the CIO needs to be accountable for. So I think that's how we have orchestrated it, because I think it is important in these worlds where you want to be able to drive data-driven innovation but you want to be able to do that in a way that doesn't open the company to unwanted risk exposures as well. And that is always a delicate balancing act, because if you index too much on risk and then high levels of security and control, then you could lose productivity. But if you index too much on productivity, collaboration and open access and data, it opens up the company for risks. So it is a delicate balance within the two. >> Increasingly, we're seeing that reporting structure evolve and coalesce, I think it makes a lot of sense. I felt like at some point you had too many seats at the executive leadership table, too many kind of competing agendas. And now your structure, the CIO is obviously a very important position. I'm sure has a seat at the leadership table, but also has the responsibility for managing that sort of data as an asset versus a liability which my view, has always been sort of the role of the Head of Information. I want to ask you, I want to hit the Escape key a little bit and ask you about data as a resource. You hear a lot of people talk about data is the new oil. We often say data is more valuable than oil because you can use it, it doesn't follow the laws of scarcity. You could use data in infinite number of places. You can only put oil in your car or your house. How do you think about data as a resource today and going forward? >> Yeah, I think the data as the new oil paradigm in my opinion, was an unhealthy, and it prompts different types of conversations around that. I think for certain companies, data is indeed an asset. If you're a company that is focused on information products and data products and that is core of your business, then of course there's monetization of data and then data as an asset, just like any other assets on the company's balance sheet. But for many enterprises to further their mission, I think considering data as a resource, I think is a better focus. So as a vital resource for the company, you need to make sure that there is an appropriate caring and feeding for it, there is an appropriate management of the resource and an appropriate evolution of the resource. So that's how I would like to consider it, it is a personal end of one perspective, that data as a resource that can power the mission of the company, the new products and services, I think that's a good, healthy way to look at it. At the center of it though, a lot of strategies, whether people talk about a digital strategy, whether the people talk about data strategy, what is important is a company to have a pool north star around what is the core mission of the company and what is the core strategy of the company. For Bristol-Myers Squibb, we are about transforming patients' lives through science. And we think about digital and data as key value levers and drivers of that strategy. So digital for the sake of digital or data strategy for the sake of data strategy is meaningless in my opinion. We are focused on making sure that how do we make sure that data and digital is an accelerant and has a value lever for the company's mission and company strategy. So that's why thinking about data as a resource, as a key resource for our scientific researchers or a key resource for our manufacturing team or a key resource for our sales and marketing, allows us to think about the actions and the strategies and tactics we need to deploy to make that effective. >> Yeah, that makes a lot of sense, you're constantly using that North star as your guideline and how data contributes to that mission. Krishna Cheriath, thanks so much for coming on the Cube and supporting the MIT Chief Data Officer community, it was a really pleasure having you. >> Thank you so much for Dave, hopefully you and the audience is safe and healthy during these times. >> Thank you for that and thank you for watching everybody. This is Vellante for the Cube's coverage of the MIT CDOIQ Conference 2020 gone virtual. Keep it right there, we'll right back right after this short break. (lively upbeat music)

>> Life from Las Vegas, it's theCube, covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back everyone to theCube's live coverage of the AWS Executive Summit. I'm your host, Rebecca Knight. And I'm joined by Kathleen Natriello. She is the vice president and the head of IT, digital design at Bristol Myers Squibb. And Shalu Chadha, senior technology services lead at Accenture. Thank you so much for coming on theCube. >> Sure. >> Thank you for having us. >> So we're going to talk about Bristol Myers Squibb's journey to the cloud today, but I want. Bristol Myers Squibb is a household name, but I would love you to just start out, Kathleen, by telling our viewers a little bit about Bristol Myers Squibb. Just how big a global pharma company you are. >> Sure. We're a global company, as you said. We have about 23,000 employees all over the world. And we're very focused on our immuno oncology therapies. And the way that they work is that they boost the immune system to fight cancer. So it's a really exciting development that we've had over the years. >> And so what was it, sort of, in the trajectory of Bristol Myers Squibb, that made you realize, as an organization, we need to do things differently? What challenges were you facing? >> So, we're very science focused in terms of developing treatments for our patients. And so our highest priority was our scientists' productivity. And so we started our cloud journey about 10 years ago. And our initial focus was on leveraging burst computing in AWS, which enabled us to spin up enough capacity for our scientists to do research with very large volumes of data. That's one of the things about biopharma. We use very large volumes for genomics research. >> And also, with this partnership, using AWS, you also partner with Accenture. So, can you describe a little bit, Shalu, how the partnership evolved? >> Right. And so that journey that Kathy mentioned, We've been part of that journey for the last two years now. And I think it's this nice partnership between AWS, BMS, and Accenture. And the teams have gone on with a lot of quick successes and early successes. And I think, going forward, the focus is really now businesses is going to look for a lot more demand and agility. Clouded adoption is going to be key in how we actually expand on that. And I know we're talking amongst us to say, how do we get there faster now? >> A little less conversation, a little more action please. >> Yes. (inaudible speech and laughter) >> Exactly. So, let's talk about this journey. So you're not only migrating existing applications, you're also building your own applications. >> Yes. >> What's the, sort of the wisdom behind that strategy? >> A couple of things. So I mentioned earlier that we started our journey with our scientists and we've continued because that's where AWS really delivers significant value for Bristol Myers Squibb. So, what we have done is implemented several AWS cloud services that enable our scientists to use machine learning, artificial intelligence, a lot of computational approaches and simulations that significantly reduce the amount of time it takes them to do an experiment, as well as the cost. Because they no longer have to use actual physical material, or patients, or investigators. They can do it all through simulation and modeling, which is exciting. >> So, I mean, we all know that the drug discovery process takes a long time, and it's tedious, um, cumbersome. So can you actually bring it back down to earth a little bit and say, what have you seen? What are your scientists? In terms of how the drug discovery process is going. >> Yeah. Our scientists are our biggest advocates of the cloud and the capabilities it delivers. And they will report back to us that they are doing things with machine learning and artificial intelligence with these simulations, that they're doing in a few hours, that used to take them weeks and months. And so that's how it's really shortening that cycle. >> And are the patients feeling the benefits yet, too? >> The patients will feel the benefits with our focus on clinical trials. And so, being able to speed up a clinical trial is very helpful. And both from the patient experience, as well as the investigators. >> Shalu, can you talk about some of the other innovation and automation capabilities? >> Yeah. So, BMS is really on this really exciting journey, and now that they've, like Kathy said, extended some of those capabilities and actually building and enabling for the scientists, of the commercial, the brand sites. It's now about, really, what do you do next and how you bring that next wave of innovation. And so, what's been nice at Bristol Myers Squibb and the partnership we have with Accenture here, is really looking at taking some of the learnings we had in the back office, in the finance and the procurement. Where we've actually brought a lot of process efficiency through our bots taking some of that learnings and bringing that across in many other different ways. And now we have bots across legal, compliance, and moving into the clinical area that adverse events. And we're looking at really that part which is how do you actually get quicker with how the patients are going to see both responses to the adverse events, as well as how do you actually accelerate the clinical trial process. And all of those innovations are really possible with what Kathy has set up in her organization. And actually having that digital acceleration competency and be able to take this span enterprise. >> One of the things that's so interesting about these partnerships is how you work together. >> (in unison) Yes. >> And is it that you're focusing on the science and Accenture is thinking about the technology? I mean, are you, sort of, two different groups? Or how are you coming together to collaborate and build a relationship? >> I really see it as three groups. So it's Bristol Myers Squibb that's focused on science as well as the technology. And if I take an example of how that partnership works, when we were doing our migration to the cloud, the more aggressive plan that we have in place right now, Amazon partnered with us on a migration readiness program. And that enabled us to move as much as 400 plus workloads into the cloud and to other locations. And then Accenture partnered with us, as well, to actually move the applications and migrate them to the cloud and the two other locations. So, I really see it as a three way partnership. And part of the way, one of the reasons it's so successful is it's not just BMS partnering with Accenture, and BMS partnering with Amazon, But it's Amazon and Accenture partnering together. And they would come up with ideas on here's what we think will make BMS even more successful. >> And how, and how is that? Is it because you were really grasping their business challenges? Or, I mean, how are you able to come up with? You're not a life science person. >> Right. >> It's, how are you doing that? >> It's a good question, and I think when I reflect on what I experience with other clients, I think what's so tremendously making us successful here is everything is about interest based. And it's about how we start the conversation. The patient in the center. And then it's about who's interests are we serving. Let's be clear. And let's try and try trigress into what's the solution that actually needs that. So, I think, whether, Kathy mentioned it in the cloud cumulus work, or even with the SAPS four journey right now. It's the combination of AWS, BMS, and Accenture in that journey of how we going to solve this together. Those critical and complex programs. >> Kathy, you said that scientists were some of your biggest advocates for going cloud native. I'm curious about the rest of the work force. I mean, has it been, sometimes introducing new technologies and new ways of doing things can cause consternation among your employees. >> Yeah., but in my organization, we bring a lot of change to the rest of the company. And your right. Sometimes it's well received. But I think when it is well received, is when across the company they can see the productivity gain with our robotics process automation. At a digital workforce, people are able to have, they are able to get a lot more done. And so there is acceptance of that. And very often, the business functions are the ones that introduce the new technologies because they're really interested in it and curious. So it works out well. >> So they're getting more done so >> Yes >> So then they're more satisfied with their work and life >> Yes >> And, exactly. So tell our viewers a little bit more about what's next for this partnership, for this relationship, in terms of new technologies. In terms of what you hope to be able to accomplish in the years to come. >> So, I can start. I really think that's what is next for us is to move a little faster. So, in our cloud journey, as I mentioned, we started 10 years ago and then, we've build on what we've learned. So, as an example, we put our commercial data warehouse into a Amazon Redshift. And then that laid the foundation for us to do, for example, rapid data labs. We started by building some data lakes in HR and R and D. And then, by the time we got to doing that for manufacturing, we did it serverless. And so we've had a nice progression based on learning and going the next step. But I think, we're to the point where the technology's evolving so quickly we can move a lot faster and get the benefits faster. So for me, that's what I view as what's next. >> Shalu, anything? >> Yeah. I would just add that I think analytics set the core. I think there is such a strong foundation set here that now it's about how are we going to extrapolate from there. And really look at bot machine learning and what that could do for us. And that, and we will take a lot from what we've learned here today about actually evolving that journey. And I think the best part is the foundation is set strong. And now it's about accelerating into those specific business areas as well. So I would say analytics and really extending our machine learning capabilities. >> So move faster, analytics machine learning. Great. So we're going to be talking about it next year's summit. Well, Kathy and Shalu, thank you so much for coming on theCube. This was a lot of fun. >> Yes. It was. >> (in unison) Thank you. >> I'm Rebecca Knight. We will have more of theCube's live coverage of the AWS Executive Summit coming up in just a little bit.

(upbeat music) >> Okay, we're back here in theCUBE, this is day three of our coverage right here in the middle of all the action of Cloud City at Mobile World Congress. This is the hit of the entire show in Barcelona, not only in person, but out on the interwebs virtually, this is a hybrid event. This is back to real life, and theCUBE is here. I'm John Furrier and Dave Vellante and DR is here, Danielle Royston. >> Totally. >> Welcome back to theCUBE for the fourth time now at the anchor desk, coming back, we love you. >> Well, it's been a busy day, it's been a busy week. It's been an awesome week. >> John: Feeling good? >> Oh my God. >> You made the call. >> I've made the call. >> You did on your podcast what, months ago. >> Yeah, right? >> You made the call. >> Made the call. >> You're on the right side of history. >> Right, and people were like, it's going to be canceled. COVID won't be handled, blahbity blah. >> She's crazy. >> Nope, I was just crazy, I'm okay with that, right? >> Crazy good. >> Right, I'm like I'm forward looking in a lot of ways. And we were looking towards June and we're like, I think this is going to be the first event back. >> You know, the crazy ones commercial that Apple ran is one of the best commercials of all time. You can't ignore the crazy ones in a good way. You can't ignore what you're doing. And I think to me, what I'm so excited about is cause we've been covering cloud we're cloud bigots, we love the cloud, public cloud. We've been on that train from day one. But when you hear the interviews we did here in theCUBE and interviews that we talked about with the top people, Google, Amazon Web Services. We're talking about the top people, both technology leaders like Bill Vass and the people who run the telecom verticals like Alfonzo, Adolfo, I mean, Hernandez. We had Google's top networking executive, we had their industry leader and the telecom, Microsoft and the Silicon all are validating, and it's like, surround sound to what you're saying here, and it cannot be ignored. >> I mean, we are coming to a big moment in Telco, right? And I mean, I've been saying it's coming. I called 2021, the year of Public Cloud and Telco. It helped that Erickson bailed. So thank you, Erickson people. >> It was a gift. >> It was a gift. >> It was. >> It really was a gift. And it was not just for me, but I think also for the vendors in the booth, I mean, we have a Cloud City army, right? Here we go, let's start marching, and it's awesome. >> He reminds me of that baseball player that took a break, cause he had a hangover and, Cal Ripkin. >> Cal Ripkin? >> Yeah, what was that guy's name? >> Did that really happen? >> Yeah, he took a break and uh- >> New guy stepped in. >> Yeah, and so well, not Cal Ripkin. >> No, no, so before, you want to know, who was it, Lou Gehrig? >> Lou Gehrig, yeah, Lou Gehrig. >> Right, so, Lou Gehrig was nobody, and we can't remember the guy's name, nobody knows the guy's name, what was that guy's name? Nobody knows, oh, there's Lou Gehrig, he got hurt. He sat out and Lou Gehrig replaced him and never hear of him again. >> Danielle: Love it, I'll take that. >> Never, never missed a game for his entire career. So again, this is what Erickson did, they just okay, take a break. >> Yeah, but I mean, it's been great again. I had a great day yesterday, my keynote was delivered. Things are going well with the booth, we had Jon Bon Jovi. I mean, that was just epic and it was acoustic and it was right after lockdown. I think everyone was really excited to be there. But I was talking to a vendor that said we'd been able to accomplish in three days, what normally it would take three years from a sales funnel perspective. I mean, that's big and that's not me. That's not my organization. That's other organizations that are benefiting from this energy. Oh, it's awesome. >> The post isolation economy has become a living metaphor for transformation, and I've been trying to sort of grok and put the pieces together as to how this thing progresses in my interview with Portal One in particular really brought it into focus for me, anyway, I'd love to get your thoughts. One of the things we haven't talked much about is public policy, and I think about all the time, all the discussion in the United States about infrastructure, this is critical infrastructure, right? And the spectrum is a country like South Africa saying, come on in, we want to open up. We want to innovate, to me, that's the model for these tier two and tier three Telcos that are just going to disrupt the big guys, whereas, maybe China's maybe on the other end of the spectrum, very controlling, but it's the former that is going to adopt the cloud sooner, and it's going to completely transform the next decade. >> Yeah, I think this is a great technology for a smaller challenge or CSP that still is a large successful company to challenge the incumbents that are, they are dinosaurs too, they move a little bit slow, and maybe if you're a little bit faster, quicker dinosaur you'll survive longer, maybe you'll be able to transform and, and a public cloud enables that. And I think, you know I'm playing the long game here, right? Is public cloud already for every Telco in every corner of the world, no. And there's a couple of things that are barriers to that. We don't really talk about the downsides, and so maybe we sort of wrap up with- there are challenges and acknowledge there are challenges, you know, in some cases their data regulations and issues, right? And you can't right? There's not a hyperscaler in your country, right? And so you're having a little bit of challenges, but you trend this out over 10 years and then pace it with the hyperscalers that are building new data centers. They're each at 25 plus each, you know, plus or minus a few, right? They're marching along, and you trend this out over 10 years, I think one of two things happened, your data regulations are eased or a hyperscaler appears in a place you can use it, and those points converge and hopefully the software's there, and that's my effort and (claps) yeah. >> Dave: You know what's an interesting trend, DR and John, that is maybe a harbinger to this, is you just mentioned something. If the hyperscalers might not have a presence in, in a country, you know what they're doing? And our data shows this, I do that weekly series breaking analysis and the data Openstack was popping up. Like where does OpenStack come from, well, guess what, when you cut the data, it was Telcos using open source to build clouds in regions where there was no hyperscalers. >> It's a gap filler. >> Yeah, it's a gap filler, it's a bandaid. >> But I think this is where, like. outpost is such a great idea, right? Like getting outposts, and I think Microsoft has the ability to do this as well, Google less so, right? They're not providing the staff, they're doing Anthos. So you're still managing this, the rack, but they're giving you the ability to tap into their services. But I was talking to a CTO in Bolivia. He was like, we have data privacy issues in our country. There's no hyperscaler, not sure Bolivia is like next on the list for AWS, right? But he's like, I'm going to build my own public cloud. And I'm like why would you do that when you can just use outposts? And then when your data regulations release, where they get to Bolivia, you can switch and you're on the stack, and you're ready to go. I think that's what you should do. You should totally do that. >> John: Yeah, one of the things that's come up on here in the interviews, in theCUBE and here, the show is that there are risk takers and innovators and there's operators. And this has been the consistent theme around, yeah, the on-premises world you mentioned this regulation reasons, and or some workflows just have to be on premise for security reasons, whatever, that's the corner case. But the operating model of the technology architecture is shifted. And that reality, I don't think is debatable, so I find it, I got to ask you this because I'm really curious. I know you get a lot of people staring at ya, oh the public cloud's just a hosting, but why aren't people getting this architectural shift? I mean, you mentioned outpost and wavelength, which Amazon has, is a game changer. It's Amazon cloud at the hub. >> Yeah, at the edge. >> Okay, that's a low latency, again, low-hanging fruit applications, real buys, whatnot. I mean, that's an architectural dot that's been connected. Why are people getting it. >> In our industry, I think it is a lot of not invented here syndrome, right? And that's a very sort of nineties thought and I have been advocating stand on the shoulders of the greatest technologists in the world, right, and you know, there's, there is a geopolitical US thing, I think we lived through a presidency that had a sort of nationalistic approach and a lot of those conversations pop up, but I've also looked to these guys and I'm like, you're still, you still have your Huawei kit installed. And there's concerns with that too. So, and you picked it because of cost, and it's really hard to switch off of, so give me a break with your public cloud USA stuff, right? You can use it, you're just making excuses, you're just afraid. What are you afraid of, the HR implications? Let's talk about that, right? And the minute I take it there, conversation changes. >> Yeah, I talked to Teresa Carlson when she was running the public sector at AWS, she's now president of Splunk. I call her a Renaissance woman. She's been a great leader and public sector for this weird little pocket of AWS where it's a guess a sales division, but it's still its own company. >> Danielle: Yeah. >> And she's, did the CIA deal, the DOD, and the public sector partnerships are now private, a lot more private relationships, So it's not like just governments, you mentioned government and national security, and these things, you started to see the ecosystem not, not just be about companies, >> Danielle: Yeah. >> Government and private sector. So this whole vibe of the telecom being regulated, unregulated, unbundled is an interesting kind of theory. What's your thoughts and reactions to this, kind of this, melting pot of ecosystem change and evolution? >> Danielle: Yeah, I mean. I think there's a very nationalistic approach by the Telcos, right? They sort of think about the countries that they operate in. There's a couple of groups that go across multiple countries, but can there be a global Telco? Can that happen, right? Just like we say, you were saying it earlier, Netflix, right? You can say Netflix, UK. Right, and so can we have a global Telco, right. That is challenging on a lot of different levels. But think about that in a public cloud start to enable that idea, right? Elon Musk is going to get to Mars. You need a planetary level Telco. And I can, I think that day is, I mean, I don't think it's tomorrow, but I think that's like 10, 20 years away. >> Dave: You're done, we're going to see it start this decade, it's already starting. We're going to see the fruits of that dividend. >> Danielle: Yeah, it's crazy. >> I've got to ask you, you're a student of the industry and you get so much experience, it's great to have you on theCUBE and chat about, riff about these things, but, the classic who's ready for disruption question comes up, and I think there's no doubt that the Telcos as an industry has been slow moving and the role and the importance has changed. People need the need to have the internet access they need to access. >> Yeah. >> So, and you've got the edge, now applications are now running on it, since the iPhone 14 years ago, as you pointed out, people now are interested in how packets move. That's fast whether it's a doctor or an emergency worker or someone. >> Danielle: What we have done in 2020 without the internet and broadband and our mobile phones, I mean? >> You know, I think about 1920 when the Spanish flu pandemic hit a hundred years ago, those guys did not have mobile phones and they must have been bored, right? I mean, what are you going to do, right? And so, yeah I think last year really moved a lot of thinking forward in this respect, so. >> Yeah, it's always like that, that animal out in the Serengeti that gets taken down, you know, by the cheetah or the lion. How do know when someone is going to be disrupted What's the, what's the tell sign in your mind, you look at the Telco landscape. What is someone waiting to be disrupted or replaced like? >> You know what they're ostriches, how do you say that word, right? They stick their head in the sand. Like I don't want to talk about it, la la la, I don't want to, I don't want to think about it. You know, they bring up all these like roadblocks, and I'm like, okay, I'm going to come visit you in another six months to a year, and let's see what happens when the guys that are moving fast that are open-minded to this, and it's, I mean, when you start to use the public cloud, you don't, like, turn it on overnight. You start experimenting, right? You start, you take an application that is non-threatening. You have, I mean, these guys are running thousands of apps inside their data centers. Pick some boring ones, pick some old ones that no one likes, and move that to the public cloud, play with it. Right, I'm not talking about moving a whole network overnight tomorrow. You got to learn, you have no, I mean, very little talent in the Telco that know how to program against the AWS stack. Start hiring, start doing it, and you're going to start to learn about the compensation, and I used to do compensation, right? I spent a lot of time in HR, right? The compensation points and structures, they compare AWS and Google, versus a Telco. Do you want Telco stock? Do you want Google stock? >> Dave: Right, where do you want to go? >> Right, right? like that's going to challenge the HR organization in terms of compensate. How do we compensate our people when they're learning these new valuable skills? >> When you think about disruption, you know, the master or the professor of disruption, Clay Christensen, one of the best lectures he ever gave was who at Cambridge, and he gave a lecture on the steel industry, and he was describing it, it was like four layers of value in the steel industry, the value chain, it started with rebar, like the lowest end, right? >> Danielle: Yeah yeah. >> And the Telco's actually the opposite, so that, you know, when, when the international companies came in, they went after rebar, and the higher end steel companies said, nah, let them have it, that's the low margin stuff. And then eventually, uh, when they got up to the high end. >> Danielle: It was over, yeah. >> The Telcos are the opposite. They're like, the, you know, in the, in the conductivity and they're hanging on to that because it's so big, but all the high value stuff, it's already gone to the, over the top players, right. >> It's being eaten away, and I'm like, what is going to wake you guys up to realize those are your competitors, that's where the battle is, right? >> John: That's really where the value is. >> The battle of the bastards, you're there by yourself, like "Game of Thrones" and they're coming at you. >> John: You need a dragon. >> What are you doing about it? >> John: I need a dragon to compete in this market. Riding a dragon would be a good strategy. >> I know, I was just watching. Cause I have a podcast, I have a podcast called "Telco In 20" and we always put like little nuggets in the show notes, I personally reviewed them, I was just reviewing the one for the keynote that we're putting out, and I had a dragon in my keynote, right? It was a really great moment, it was really fun to do, but there's, I don't know if you guys are "Game of Thrones" fans. >> Yeah. >> Sure. >> Right, but there's a great moment when Daenerys gets her dragons, the baby dragons, and she takes over the Unsullied Army, right? And it's just this, right? Like all of a sudden the tables turn in an instant where she has nothing, and she's like on her quest, right. I'm on a quest. >> Dave: Comes out of the fire. >> Right, comes out of the fire, the unburnt, right? She has her dragons, right? She has them hatch. She takes over the Unsullied Army, right? Slaves, it starts her march, right? And I'm like, we're putting that clip into the show notes because I think that's where we are. I think I've hatched some dragons, right? The Cloud City army, let's go, let's go take on Telco. >> John: Well, I mean, this to me. >> Easy. >> It definitely have made, made it happen because I heard many people talking about cloud, this is turning into a cloud show. The question is, when does this going to be a cloud show? That's just Cloud City, it's a big section of the show. I mean, all the big players are behind it. >> Danielle: Yeah, yeah. >> Amazon Web Services, Google Azure, Ecosystem, startups, thinking differently, but everyone's agreeing why aren't we doing this? >> I think, like I said, I mean, people are like, you're such a visionary, and how did, why do you think this will work, I'm like, it's worked in every other industry. Am I really that visionary, and like, these are the three best tech companies in the world, like, are, are you kidding me? And so I think we've shown the momentum here. I think we're looking forward to 2022, you know? And that we see 2022, you got to start planning this the minute we get back, right? Like I wouldn't recommend doing this in a hundred days again, that was a very painful, but you know, February, I was, there's a sign inside NWC, February 28th. Right, we're talking seven months. You got to get going now. >> John: Let's get on the phone. >> With Telco, I mean, I think you're right on. I mean, you know, remember Skype, in the early days, right? >> Danielle: Yeah, yeah. >> It wasn't regional. It was just, plug into the internet. >> Danielle: It was just Skype, it was just WhatsApp. >> Well this is a great location, if you can get a shot guys of the people behind us, I don't know if you can, if you're watching check out the scene here, It's winding down, a lot of people having happy hour. Now this is a social construct here at Cloud City, not only is it chock full of information, reporting that we're doing and getting all the data and with the presentations on the main stage, with Adam and the studio and the team, this is a place where people are meeting and there's deals being done face to face, intimate relationships, the best of the best are here, they make the trek. So there's been a successful formula. Of course theCUBE is in the middle of all the action, which we love, we're psyched to be back. I want to thank you personally, while we have you on stage here. >> I want to thank you guys, and the crew, the crew has been amazing, turning out videos on short order. We have all these crews in different cities, it's, our own show has been virtual. You know, Adam's in Bristol, right? We're here, this was an experiment, we talked about this a hundred days ago, 90 days ago. Could we get theCUBE there, do the show but also theCUBE. >> You are a visionary, you said made for TV hybrid event with your team, produce television shows, theCUBE, we're digital, we love you guys, great alignment, but it's magical because the content doesn't end here, the show might end, they might break down the beautiful plants and the exhibits, but the community is going to continue, the content and the conversations. >> Yeah. >> So, we were looking forward to it and- >> I'm super glad, super glad we did this. >> Awesome, well, any final moments that you would like to share in the last two minutes we have, favorite moments, observations, funny things that have happened to you, weird things that have happened to you, share something that people might not know, or a favorite moment? >> I think, I don't know that people know, we have a 3D printer in the coffee shops, and so you can upload any picture and they're 3d printing, coffee art, right? So I've been seeing lots of social posts around people uploading their, their logos and things like that. I think Jon Bon Jovi, he was super thankful to be back. He thanked me personally two different times of like, I'm just glad to be out in front of people. And I think just even just the people walking around, thank you for being brave, thank you for coming back. You've helped Barcelona and we're happy to be together. Even if it is with masks, it's hard to do business with masks on, everyone's happy and psyched. >> John: Well the one thing that people cannot do relative to you is they cannot ignore you. You are making a great big wave. >> Danielle: I shout pretty loud, It's kind of hard to ignore me. >> You're making a great big wave, you're on the right side, we believe, of history, public cloud is driving the bus down main street of Cloud City, and if people don't get out of the way, they will be under the bus. >> I'm, like I said, in my keynote, it's go time let's do it. >> Okay. Thank you so much for all your attention and mission behind the cloud and the success. >> Danielle: We'll do it again. We're going to do it again soon. >> After Togi's a hundred million dollar investment, you're the CEO of Togi that, let's follow that progress, and of course, Telco DR, Danielle Royston, the digital revolution. Thanks for coming on with you. >> Thank you guys, it was super fun. >> This is theCUBE I'm John Furrier with Dave Vallante, we're going to send it back to Adam in the studio. Thanks, the team here. >> Woo! (audience applauding) >> I want to thank the team, everyone here, Adam is great, Chloe. >> Great working with you guys. >> Awesome, and what a great crew. >> So great. >> Thank you everybody. That's it for theCUBE, here on the last day, Wednesday of theCUBE, stay tuned for tomorrow more action on the main stage, here in Cloud City. Thanks for watching.

(upbeat music) >> Hey, we're back here in theCube. This is day three of our coverage right here in the middle of all the action of Cloud City at Mobile World Congress. This is the hit of the entire show in Barcelona, not only in person, but out on the interwebs virtually. This is a hybrid event. This is back to real life, and theCube is here. I'm John Furrier with Dave Vellante and D. R. is here, Danielle Royston. >> Totally. >> Welcome back to theCube for fourth time. now at the anchor desk, coming back. >> I don't know. It's been a busy day. It's been a busy week. It's been an awesome week. >> Dave: Feeling good? >> Oh, my god. >> You made the call. >> I made the call. You finished your podcast, what months ago? >> Yeah. >> Made the call. >> Made the call. You're on the right side of history. >> Right? And people were like, "It's going to be canceled. COVID won't be handled." Blahbity blah. >> She's crazy. >> And I'm like, nope. She's crazy. I'm okay with that. Right? But I'm like... >> Crazy good. >> Right, I'm like, I'm forward-looking in a lot of ways. And we were looking towards June, and we're like, "I think this is going to be the first event back. We're going to be able to do it." >> You know, the crazy one's commercial that Apple ran, probably one of the best commercials of all time. You can't ignore the crazy ones in a good way. You can't ignore what you're doing. And I think to me, what I'm so excited about is, 'cause we've been covering cloud. We're cloud bigots. We love the cloud, public cloud. We've been on that train from day one. But when you hear the interviews we did here on theCube and interviews that we talked about with the top people, Google, Amazon Web Services. We're talking about the top people, both technology leaders like Bill Vass and the people who run the Telecom Verticals like Alf, Alfonzo. >> Danielle: Yeah. >> Adolfo, I mean, Hernandez. >> Danielle: Yeah. >> We had Google's top networking executive. We had their industry leader in the telecom, Microsoft, and the Silicon. All are validating, and it's like surround sound to what you're saying here. And it cannot be ignored. >> I mean, we are coming to a big moment in Telco, right? And I mean, I've been saying that it's coming. I called 2021, the year of public cloud and Telco. It helped that Ericcson bailed. So thank you, Ericcson people. >> Dave: It was a gift. >> It was a gift. >> John: It really was. >> It really was a gift. And it was not just for me, but I think also for the vendors in the booth. I mean, we have a Cloud City army, right? Here we go. Let's start marching. And it's awesome. >> He reminds me of that baseball player that took a break 'cause he had a hangover and Cal Ripken. >> Cal Ripken, right, yeah, yeah. What was that guy's name? >> Did it really happen? >> Yeah, he took a break and... >> The new guy stepped in? >> Yeah, and so we'll go to Cal Ripken. >> No, no, so before it was it? Lou Gehrig. >> Lou Gehrig, yeah. >> Right, so Lou Gehrig was nobody. And we can't remember the guy's name. Nobody knows the guy's name. >> Danielle: Yeah, yeah. >> What was that guy's name? Nobody knows. Oh, 'cause Lou Garrett, he got hurt. >> Danielle: And Lou Gehrig stepped in. >> He sat out, and Lou Gehrig replaced him. >> Danielle: Love it. >> And never heard of him again. >> Danielle: I'll take that. >> Never missed a game. Never missed a game for his entire career. So again, this is what Ericcson did. They just okay, take a break and... >> But I mean, it's been great. Again, I had a great day yesterday. My keynote was delivered. Things are going well with the booth. We had Jon Bon Jovi. I mean, that was just epic, and it was acoustic, and it was right after lockdown. I think everyone was really excited to be there. But I was talking to a vendor that said we'd been able to accomplish in three days what normally it would take three years from a sales funnel perspective. I mean, that is, that's big, and that's not me. That's not my organization. That's other organizations that are benefiting from this energy. Oh, that's awesome. >> The post-isolation economy has become a living metaphor for transformation. And I've been trying to sort of grok and put the pieces together as to how this thing progresses. And my interview with Portaone, in particular, >> Danielle: Yeah. >> really brought it into focus for me, anyway. I'd love to get your thoughts. One of the things we haven't talked much about is public policy. And I think about all the time, all the discussion in the United States about infrastructure, this is critical infrastructure, right? >> Danielle: Yeah. >> And the spectrum is a country like South Africa saying, "Come on in. We want to open up." >> Danielle: Yeah. >> "We want to innovate." And to me that's to me, that's the model for these tier two and tier three telcos that are just going to disrupt the big guys. Whereas, you know, China, may be using the other end of the spectrum, very controlling, but it's the former that is going to adopt the cloud sooner. It's going to completely transform the next decade. >> Yeah, I think this is a great technology for a smaller challenger CSP that still is a large successful company to challenge the incumbents that are, they are dinosaurs too. They move a little bit slow. And maybe if you're a little bit faster, quicker dinosaur you'll survive longer. Maybe it will be able to transform and a public cloud enables that. And I think, you know, I'm playing the long game here, right? >> Dave: Yeah. >> Is public cloud ready for every telco in every corner of the world? No. And there's a couple of things that are barriers to that. We don't really talk about the downsides, and so maybe we sort of wrap up with, there are challenges, and I acknowledge there are challenges. You know, in some cases there are data regulations and issues, right? And you can't, right? There's not a hyperscaler in your country, right? And so you're having a little bit of challenges, but you trend this out over 10 years and then pace it with the hyperscalers are building new data centers. They're each at 25 plus each, plus or minus a few, right? They're marching along, and you trend this out over 10 years, I think one of two things happens. Your data regulations are eased or you a hyperscaler appears in a place you can use it. And those points converge, and hopefully the software's there, and that's my effort. And, yeah. >> You know what's an interesting trend, D. R., John? That is maybe a harbinger to this. You just mentioned something. If the hyperscalers might not have a presence in a country, you know what they're doing? And our data shows this, I do that weekly series "Breaking Analysis," and the data, OpenStack was popping up. >> Danielle: Yeah. >> Like where does OpenStack come from? Well, guess what. When you cut the data, it was telcos using open source to build clouds in regions where there was no hyperscaler. >> Where it didn't exist, yeah. >> So it's a-- >> Gap-filler. >> Yeah, it's a gap-filler. It's a Band-aid. >> But I think this is where like Outpost is such a great idea, right? Like getting Outposts, and I think Microsoft has the ability to do this as well, Google less so, right. They're not providing the staff. They're doing Anthos, so you're still managing this, the rack, but they're giving you the ability to tap into those services. But I was talking to a CE, a CTO in Bolivia. He was like, "We have data privacy issues in our country. There's no hyperscaler." Not sure Bolivia is like next on the list for AWS, right? But he's like, "I'm going to build my own public cloud." And I'm like, "Why would you do that when you can just use Outposts?" And then when your data regulations release or there's a, they get to Bolivia, you can switch and you're on the stack and you're ready to go. I think that's what you should do. You should totally do that. >> Yeah, and one of the things that's come up here on the interviews and theCube and here, the show, is that there are risk takers and innovators and there's operators. And this has been the consistent theme around, yeah, the on-premises world. You mentioned this regulation reasons and/or some workflows just have to be on premise for security reasons, whatever. That's the corner case. >> Danielle: Yeah. >> But the operating model of the technology architecture is shifted. >> Danielle: Yep. >> And that reality, I don't think, is debatable. So I find it. I've got to ask you this because I'm really curious. I know you get a lot of people steering 'ya, oh the public cloud's just a hosting, but why aren't people getting this architectural shift? I mean, you mentioned Outpost, and Wavelength, which Amazon has, is a game changer. It's Amazon Cloud at the hub. >> Yeah, at the edge, yeah. >> Okay, that's a low latency again, low-hanging fruit applications, robotics, whatnot. I mean, that's an architectural dot that's been connected. >> Yeah. >> Why aren't people getting it? >> In our industry, I think it is a lot of not invented here syndrome, right? And that's a very sort of nineties thought, and I have been advocating stand on the shoulders of the greatest technologists in the world. Right? And you know, there is a geopolitical US thing. I think we lived through a presidency that had a sort of nationalistic approach and a lot of those conversations pop up, but I've also looked to these guys and I'm like, you still have your Huawei kit installed, and there's concerns with that, too. So, and you picked it because of cost. And it's really hard to switch off of. >> John: Yeah. >> So give me a break with your public cloud USA stuff, right? You can use it. You're just making excuses. You're just afraid. What are you afraid of? The HR implications? Let's talk about that, right? And the minute I take it there, conversation changes. >> I talked to Teresa Carlson when she was running the public sector at AWS. She's now president of Splunk. I call her a Renaissance woman. She's been a great leader. In public sector there's been this weird little pocket of AWS where it's, I guess, a sales division, but it's still its own company. >> Danielle: Yeah. >> And she just did the CIA deal. The DOD and the public sector partnerships are now private, a lot more private relationships. So it's not like just governments. You mentioned government and national security and these things. You start to see the ecosystem, not, not just be about companies, government and private sector. So this whole vibe of the telecomm being regulated, unregulated, unbundled is an interesting kind of theory. What's your thoughts and reactions to this kind melting pot of ecosystem change and evolution? >> Yeah, I mean, I think there's a very nationalistic approach by the telcos, right? They sort of think about the countries that they operate in. There's a couple of groups that go across multiple countries, but can there be a global telco? Can that happen, right? Just like we say, you were saying it earlier, Netflix. Right? You didn't say Netflix, UK, right? And so can we have a global telco, right? That is challenging on a lot of different levels. But think about that in a public cloud starts to enable that idea. Right? Elon Musk is going to get Mars. >> Dave: Yep. >> John: Yeah. >> You need a planetary level telco, and I think that day is, I mean, I don't think it's tomorrow, but I think that's like 10, 20 years away. >> You're done. We're going to see it start this decade. It's already starting. >> Danielle: Yeah. >> But we're going to see the fruits of that dividend. >> Danielle: Right, yeah. >> I got to ask you. You're a student of the industry and you got so much experience. It's great to have you on theCube and chat about, riff about, these things, but the the classic "Who's ready for disruption?" question comes up. And I think there's no doubt that the telcos, as an industry, has been slow moving, and the role and the importance has changed. People need the need to have the internet access. They need to access. >> Danielle: Yeah. >> So and you've got the Edge. Now applications are now running on a, since the iPhone 14 years ago, as you pointed out, people now are interested in how packets move. >> Danielle: Yeah. >> That's fast, whether it's a doctor or an emergency worker or someone. >> What would we have done in 2020 without the internet and broadband and our mobile phones? I mean. >> Dave: We would have been miserable. >> You know, I think about 1920 when the Spanish flu pandemic hit a hundred years ago. Those guys did not have mobile phones, and they must have been bored, right? I mean, what are you going to do? Right? And so, yeah, I think, I think last year really moved a lot of thinking forward in this respect, so. >> Yeah, it's always like that animal out in the Serengeti that gets taken down, you know, by the cheetah or the lion. How do you know when someone is going to be disrupted? What's the, what's the tell sign in your mind? You look at the telco landscape, what is someone waiting to be disrupted or replaced look like? >> Know what? They're ostriches. Ostriches, how do you say that word right? They stick their head in the sand. Like they don't want to talk about it. La, la, la, I don't want to. I don't want to think about it. You know, they bring up all these like roadblocks, and I'm like, okay, I'm going to come visit you in another six months to a year, and let's see what happens when the guys that are moving fast that are open-minded to this. And it's, I mean, when you start to use the public cloud, you don't like turn it on overnight. You start experimenting, right? You start. You take an application that is non-threatening. You have, I mean, these guys are running thousands of apps inside their data centers. Pick some boring ones. Pick some old ones that no one likes. Move that to the public cloud. Play with it, right? I'm not talking about moving your whole network overnight tomorrow. You got to learn. You have no, I mean, very little talent in the telco that know how to program against the AWS stack. Start hiring. Start doing it. And you're going to start to learn about the compensation. And I used to do compensation, right? I spent a lot of time in HR, right? The compensation points and structures, and they can bear AWS and Google versus a telco. You want Telco stock? Do you want Google stock? >> John: Right, where do you want to go? >> Right? Right? And so you need to start. Like that's going to challenge the HR organization in terms of compensate. How do we compensate our people when they're learning these new, valuable skills? >> When you think about disruption, you know, the master or the professor of disruption, Clay Christensen, one of the best lectures he ever gave is we were at Cambridge, and he gave a lecture on the steel industry and he was describing it. It was like four layers of value in the steel industry, the value chain. It started with rebar, like the lowest end. Right? >> Danielle: Yeah, yeah. >> And the telco's actually the opposite. So, you know, when the international companies came in, they went after rebar, and the higher end steel companies said, "Nah, let them have it." >> Danielle: Let it go. >> "That's the low margin stuff." And then eventually when they got up to the high end, they all got killed. >> Danielle: It was over, yeah. >> The telcos are the opposite. They're like, you know, in the connectivity, and they're hanging on to that because it's so big, but all the high value stuff, it's already gone to the over-the-top players, right? >> It's being eaten away. And I'm like, "What is going to wake you guys up to realize those are your competitors?" That's where the battle is, right? >> Dave: That's really where the value is. >> The battle of the bastards. You're there by yourself, the Game of Thrones, and they're coming at you. >> John: You need a dragon. >> What are you doing about it? >> I need a dragon. I need a dragon to compete in this market. Riding on the dragon would be a good strategy. >> I know. I was just watching. 'Cause I have a podcast. I have a podcast called "Telco in 20," and we always put like little nuggets in the show notes. I personally review them. I was just reviewing the one for the keynote that we're putting out. And I had a dragon in my keynote, right? It was a really great moment. It was really fun to do. But there's, I don't know if you guys are Game of Thrones fans. >> Dave: Oh, yeah. >> John: For sure. >> Right? But there's a great moment when Daenerys guts her dragons, the baby dragons, and she takes over the Unsullied Army. Right? And it's just this, right? Like all of a sudden, the tables turn in an instant where she has nothing, and she's like on her quest, right? I'm on a quest. >> John: Comes out of the fire. >> Right, comes out of the fire. The unburnt, right? She has her dragons, right? She has them hatch. She takes over the Unsullied Army, right? Slays and starts her march, right? And I'm like, we're putting that clip into the show notes because I think that's where we are. I think I've hatched some dragons, right? The Cloud City Army, let's go, let's go take on Telco. >> John: Well, I mean to me... >> Easy. >> I definitely have made it happen because I heard many people talking about cloud. This is turning into a cloud show. The question is, when does this be, going to be a cloud show? You know it's just Cloud City is a big section of the show. I mean, all the big players are behind it. >> Danielle: Yeah, yeah. >> Amazon Web Services, Google, Azure, Ecosystem, startups thinking differently, but everyone's agreeing, "Why aren't we doing this?" >> I think, like I said, I mean, people are like, you're such a visionary. And how did, why do you think this will work? I'm like, it's worked in every other industry. Am I really that visionary? And like, these are the three best tech companies in the world. Like, are you kidding me? And so I think we've shown the momentum here. I think we're looking forward to 2022, you know? And do we see 2022, you get to start planning this the minute we get back. Right? >> John: Yeah. >> Like I wouldn't recommend doing this in a hundred days again. That was a very painful, but you know, February, I was, there's a sign inside NWC, February 28th, right? We're talking seven months. You got to get going now. >> John: Let's get on the phone. (John and Dave talking at the same time) >> I mean, I think you're right on. I mean, you know, remember Skype in the early days? >> Danielle: Yeah, yeah, yeah, yeah. >> It wasn't regional. >> Danielle: Yeah. >> It was just plug into the internet, right? >> Danielle: It was just Skype. It was just WhatsApp. >> Well, this great location, and if you can get a shot, guys, of the people behind us. I don't know if you can. If you're watching, check out the scene here. It's winding down. A lot of people having happy hour now. This is a social construct here at Cloud City. Not only is it chock full of information, reporting that we're doing and getting all the data and with the presentations on the main stage with Adam and the studio and the team. This is a place where people are meeting and there's deals being done face to face, intimate relationships. The best of the best are here. They make the trek, so there's been a successful formula. Of course theCube is in the middle of all the action, which we love. We're excited to be back. I want to thank you personally while we have you on stage here. >> I want to thank you guys and the crew. The crew has been amazing turning out videos on short order. We have all these crews in different cities. It's our own show has been virtual. You know, Adam's at Bristol, right? We're here. This was an experiment. We talked about this a hundred days ago, 90 days ago. Could we get theCube there and do the show, but also theCube. >> You are a visionary. And you said, made for TV hybrid event with your team, reduced television shows, theCube. We're digital. We love you guys. Great alignment, but it's magical because the content doesn't end here. The show might end. They might break down the beautiful plants and the exhibits, but the community is going to continue. The content and the conversations. >> Yeah. >> So. >> We are looking forward to it and. >> Yeah, super-glad, super-glad we did this. >> Awesome. Well, any final moments that you would like to share? And the last two minutes we have, favorite moments, observations, funny things that have happened to you, weird things that have happened to you. Share something that people might not know or a favorite moment. >> I think, I mean I don't know that people know we have a 3D printer in the coffee shops, and so you can upload any picture, and there are three 3D printing coffee art, right? So I've been seeing lots of social posts around people uploading their, their logos and things like that. I think Jon Bon Jovi, he was super-thankful to be back. He thanked me personally two different times of like, I'm just glad to be out in front of people. And I think just even just the people walking around, thank you for being brave, thank you for coming back. You've helped Barcelona, and we're happy to be together even if it is with masks. It's hard to do business with masks on. Everyone's happy and psyched. >> The one thing that people cannot do relative to you is they cannot ignore you. You are making a great big waves. >> Danielle: I shout pretty loud. It's kind of hard to ignore me. >> Okay, you're making a great big wave. You're on the right side, we believe, of history. Public cloud is driving the bus down main street of Cloud City, and if people don't get out of the way, they will be under the bus. >> And like I said, in my keynote, it's go time. Let's do it. >> Okay, thank you so much for all your tension and mission behind the cloud and the success of... >> Danielle: We'll do it again. We're going to do it again soon. >> Ketogi's hundred million dollar investment. Be the CEO of Togi as we follow that progress. And of course, Telco D. R. Danielle Royston, the digital revolution. Thanks for coming on theCube. >> Thank you, guys. It was super-fun. Thank you so much. >> This is theCube. I'm John Furrier with Dave Vellante. We're going to send it back to Adam in the studio. Thanks the team here. (Danielle clapping and cheering) I want to thank the team, everyone here. Adam is great. Chloe, great working with you guys. Awesome. And what a great crew. >> So great. >> Thank you everybody. That's it for theCube here on the last day, Wednesday, of theCube. Stay tuned for tomorrow, more action on the main stage here in Cloud City. Thanks for watching.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Global Partner Network. Hello, everyone. This is Dave Balanta. And welcome to the cubes Virtual coverage of AWS reinvent 2020 with a special focus on the A p N partner experience. I'm excited to have two great guests on the program. Fernando Castillo is the head s a p on AWS Partner Network and s A P Alliance and AWS and Stephen Jones is the general manager s a p E c to enterprise that aws Gentlemen, welcome to the Cube. Great to see you. >>I'm here. >>So guys ASAP on AWS. It's a core workload for customers. I call it the poster child for mission Critical workloads and applications. Now a lot has happened since we last talked to you guys. So So tell us it. Maybe start with Stephen. What's going on with Sapna Ws? Give us the update. >>I appreciate the question Day. Look, a lot of customers continue to migrate. These mission critical workloads State of us on a good example is the U. S. Navy right? Who moved their entire recipe landscape European workload AWS. This is a very large system of support. Over 72,000 users across 66 different navy commands. They estimate that 70 billion worth of parts and goods actually transact through the system every year. Just just massive. Right? And this this type of adoptions continued to accelerate a very rapid clip. And today, over 5000 customers now are running SFP workloads. I need to be us on there really trusting us, uh, to to manage and run these workloads. And another interesting stat here is that more than half of these customers are actually running asap, Hana, which is a safe He's flagship in memory database. >>Right, Fernando, can you add to that? >>Sure. So definitely about, you know, the customs are also SCP themselves continue to lose a dollar less to run their own offerings. Right? So think about conquer SCP platform. SCP analytics were when new offers like Hannah Cloud. In addition to that, we continue to see the P and L despondent network to grow at an accelerated pace. Today we have over 60 SNP company partners all over the world helping SFP customers s O that customers are my green. There s appeal asking CW's. They only look for reduced costs, improved performance but also toe again access to new capabilities. So innovate around their core business systems and transform their businesses. >>So for now, I wonder if I could stay with you for a minute. I mean, the numbers that Steve was putting out there, it's just massive scale. So you obviously have a lot of data. So I'm wondering when you talk to these customers, Are you discerning any common patterns that are emerging? What are some of the things that you're hearing or seeing when you analyze the data? >>Sure. So just to give a couple example right. Our biggest customers are doing complete ASAP. Transformations on Toe s four Hana. Their chance they're going to these new S a p r p code nine All customers have immediate needs, and they're taking their existing assets to AWS, so looking to reduce costs and improve performance, but also to sell them apart for innovation. This innovation is something that operation or something that they can wait. They need it right now. It's they This time to innovate is now right on some of these customers saying that while s and P has nice apart. So that is a multi year process on most organizations and have a look from waiting for this just before they start innovating. So instead of that, they focus on bringing what they have on start innovating right away on Steve has some great stories around here, so maybe Steve can share with that. Goes with that? >>Yeah, that'd be great, Steve. >>Yeah. Look, I think a good example here on and Fernando touched it, touched on it. Well, right. So customers coming from all kind of different places in their journey aws as it relates to this this critical workload and some are looking to really reap the benefits of the investments they made over the last couple decades sometimes. And Vista is a really good example Here, um there a subsidiary of Cook Industries, they migrated and moved their existing S a P r P solution called E c C. To AWS. They estimate that this migration alone from an infrastructure cost savings perspective, has netted them about two million per year. Additionally, you know, they started to bring some of the other issues they were trying to solve from a business perspective, together now that they were on the on the on the business on the AWS platform. And one thing that recognizes they had different data silos, that they had been operating in an on premises world. Right? So massive factories solution and bringing all of that data together on a single platform on AWS and enriching that with the SCP data has allowed them to actually improve their forecasting supply chain processes across multiple data sources and the estimate that that is saving them additional millions per year. So again, customers are not necessarily waiting to innovate. Um, but actually moving forward now. >>All right, so I gotta ask, you don't hate me for asking this question, but but everybody talks about how great they are. Supporting s a P is It's one of the top, of course, because s a p, you know, huge player in the in the application space. So I want you guys to address how aws specifically compares Thio some of your competitors that are, you know, the hyper scaler specifically as it relates to supporting S a P workloads. What's the rial differential value that you guys bring? Maybe Steve, you could start >>Sure, you're probably getting to know us a little bit. Way don't focus a lot on competition, Aziz mentioned week We continue to see customers adopt AWS for S a p a really rapid clip. And that alone actually brings a lot of feedback back into how we consider our own service offerings as it relates to this particular workload on that, that's it. That's important signal right for what we're building. But customers do tell us the security performance availability matters, especially for this workload, which, you know, to be honest, is the backbone of many, many organizations. Right? And we understand why. And there was a study that was done recently about a. D. C. Where they found that even a single hour of unplanned downtime as a released this particular workload could cost millions. And so it's it's super important. And if you look at, um, you know, publicly available data from an average perspective, um, it has considerably less downtime than the other hyper scale is out there way. Take the performance and availability of oh, our entire global footprint and in this workload in particular, super important. >>Well, you know, that's a great point, Steve. I mean, if you got critical mission critical applications like ASAP supporting the business, that's driving revenue. It's driving productivity. The higher the value of the application, the greater the impact when it's down, I wonder, Fernando, you know, Steve said, You guys don't focus on the competition. Well, is an analyst. You know, I always focused on the competition, So I wonder if you're gonna add anything to that. >>Sure. So again, as you can imagine, multiple analyst called Space right. And, uh, everybody shares information. And analysts have agreed that Italy's clean infrastructure services, including the three quite a for CP across the globe. So we feel very humble and honor about this recognition on this encourages to continue to improve ourselves to give you a couple examples for a 10 year in a row. Italy's US evaluated as a leader in the century Gardner Magic Quadrant, right for cloud infrastructure from services. And, as you know, the measure to access right they measure very execute on complete, insufficient were the highest, both of them. Another third party, just not keep with one is icy, right? You know, technology research dreamers, you already you might know advice for famous Well, the reason they publisher s a p on infrastructure service provider lands reports long name which, basically, the analyzers providers were best suited to host s a. P s four hana workloads on more broadly s a p Hannah landscapes, you know, very large scape ASAP 100 landscapes. So they recognize it, at least for the third year in a row. And conservative right, the best class enterprise. Great infrastructure towards security performances, Steve mentioned, but also making the panic community secure. Differentiation. Andi, they posted. They mentioned it all us as a little position in quadrant for the U. S. U K France, Germany, the Nordics in Brazil. So again, really honor and humble on discontinued in court just to continue to improve. >>You know, Steve, I just wrote a piece on Cloud 2030 trying to project what the next 10 years is gonna look like in one of the I listed a lot of things, but one of the things I talked about was some of the technical factors like alternative processors, specialized networks, and you guys have have have really, always done a good job of sort of looking at purpose built, you know, stuff that that can run workloads faster. How relevant is that in the the S A P community? >>Oh, that's a great question, David. It's It's absolutely relevant. You take a look at what? What we've done over the years with nitro and how we've actually brought the ability for customers to run on environmental infrastructure but still have that integrated, uh, native cloud experience. Uh, that is absolutely applicable to Unless if you workload and we're actually able toe with that technology, bring the capability to customers to run thes mission critical workloads on instances with up to 24 terabytes of brand, albeit bare metal, but fully integrated into the AWS network fabric, >>right? I mean, a lot of people, you know, need that bare metal raw performance on, and that makes sense that you've been, you know, prioritize such an important class of workload. I'm not surprised that that I mean, the numbers that you threw out a pretty impressive eso. It's clear you're leading the charge here. Maybe you could share a little glimpse of what's coming in the future. Show us a little leg, Steve. >>Yeah, well, look, uh, we know that infrastructure is super important. Thio. Our customers and in particular the customers are running these mission critical workloads. But there's a lot of heavy lifting, uh, that that we also want to simplify. And so you've seen some indications of what we've done here over the years, uh, ice G that Fernando mentioned actually called out. AWS is differentiating here, right? So for for many years, we've actually been leading in releasing tools for customers to actually orchestrate and automate the deployment of these types of worthless so ASAP in particular. I mean, if you think about it a customer who is coming to a to a hyper scale platforms like AWS and having to learn what that means, Plus understand all the best practices from S, A, P and AWS to make that thing really shine from a performance and availability perspective, that's a heavy asked. Right? So we put a lot of work from a tooling perspective into into automating this and making this super simple not just for customers, but also partners. >>Anything you wanna chime in on that particular the partner side, Fernando. >>Sure. So this is super important for public community, right? As you can imagine, the tooling that we're bringing together toe. The market is helping the Spanish to move quicker, right? So they don't have to reinvent. They will all the time. They will just take this and move and take it and move forward. Give an example. One of our parents in New York, three hosts. Thanks for lunch. We start with Steve just reference right. They want to create work clothes in an automated way. Speeding up the delivery time. 75% corporation is every environments. So it just imagine the the impact of these eso a thing here that is important is our goal is to help customers and partners move quicker, removing any undifferentiated heavy lifting, right, Andi, that's kind of the mantra of this group. >>You know, when you think about what Doug Young was saying is in the keynote, um, the importance of partners and I've been on this kick about we've moved in this industry from products to platforms, and the next 10 years is gonna be about leveraging ecosystems. The power of many versus the resource is of a few or even one is large is a W s so so partners air critical on I wonder if you could talk toe the role that that the network partners air playing in affecting S a p customer outcomes and strategies. Maybe Steve, you could take that first. >>Yeah, but look, we recognize that the migration on the management of these systems it's complex, right? And for years, we've invested in a global community of partners many partners who have been fundamental to s a p customer success over over a couple decades, Right? And so, um, that there are some nuances that that need to be realized when it comes to running ASAP on on a hyper scale platforms like AWS. And so we put a lot of work into making sure these partners are equipped to ensure customers have have a really good experience. And I mean, in a recent conversation I had with a CEO of a large, uh, CPG company, he told me he reflected that the partners really are the glue. That kind of brings it all together for them. And, uh, you know, just to share something with you today, our partners, our partner community network for S. If he is actually helping over 90% of net new customers who are coming toe migrate as if you were close to AWS, so they're just absolutely critical. >>So, Fernando, there's the m word, the migration, you know, it's you don't want to unless you have to, but people have to move to the cloud. So So what can you add to this conversation? >>Sure, they So again, just to echo what Steve mentioned, right? Uh, migration. Super important. We have ah group of partners that are right now specializing in migration projects. And they have built migration factories. You may have seen some of them. They have been doing press releases through the whole year saying that they're part of these and their special cells they're bringing to the helping customers adopt AWS. So they go through the next, you know, very detailed process. We call them map for ASAP partners. So they have these incremental value on top of being SCP competent funds, which I referred earlier on. This group has, as mentioned, you know, show additional capability to safeguard these migrations on. Of course, we appreciate and respect and we have put investment programs for them to help them support their own customers right in those in these migrations. But because the SNP ecosystem on it. But it's not about only migrations, right? One important topic that we need technologies as you as Steve mentioned, we have these great set of partner of customers have trusted us or 5000 through a year on these, uh, these customers asking for innovation right there, asking us how come the ecosystem help us innovate faster? So these partners are using a dollars a plan off innovation, creating new solutions that are relevant for SCP. So basically helping customers modernize their business processes so you can take an example like Accenture Data Accelerator writers taking SCP information and data legs Really harm is the power of data there or the Lloyd you know, kinetic finances helping, you know, deploy Central finance, which is a key component of SCP, or customer like partners like syntax that has created our industrial i o. T. Offering that connects with the SNP core. So more and more you will see thes ecosystem partners innovating on AWS to support SNP customers. >>You know, I think that's such an important point because for for decades have been around for a while. It's the migrations air like this. Oftentimes there's forced March because maybe a vendor is not going to support it anymore. Or you're just trying to, you know, squeeze Mawr costs out of the lemon. What you guys are talking about is leveraging an ecosystem for innovation and again that ties into the themes that we're talking about about Cloud 2030 in the next decade of innovation. Let's close, guys. What can customers ASAP customers AWS customers expect from reinvent this year? Um, you know, maybe more broadly, what can they expect from A W S in the coming 12 months? Maybe, Steve, you could give us a sense, and then Fernando could bring us home. >>You bet. Look, um, this year we've really tried to focus on customer stories, right? So we've we've optimized. There's a number of sessions here agreement this year. We want customers and partners to learn from other from other customer experiences, so customers will be able to listen to Bristol Myers Squibb talk about their performance, their their experiences, Alando Newmont's and Volkswagen. And I'll be talking about kind of different places where they are on this, this journey to cloud and this innovation life cycle, right, because it really is about choice and what's right for their business. So we're pretty excited about that. >>Yeah. Nice mix of representative Industries there. I Fernando bring us home, please. >>Sure. So, again, we think about 21 in the future. Rest assured, we'll continue to invest heavily to make sure it values remains the platform innovation. Right on choice for recipe customers where a customer wants to move their existing investments on continue to add value. So what they have already done for years or goto export transformation. We're here to support their choice. Right? And we're committed to that as part of our customers Asian culture. So we're super excited about the future. And we're thankful for you to spend time with us today. >>Great, guys, Look, these are the most demanding workloads we're seeing that that rapid movement to the cloud is just gonna accelerate over the coming years. Thanks so much for coming on The Cube. Really appreciate it. >>Our pleasure. Thank >>you. All >>right. Thank you for watching everyone keep it right there from or great content. You're watching the cube aws reinvent 2020

>>welcome. My name is Ben Bennett. I am the director of HPC Strategic programs here at Hewlett Packard Enterprise. It is my great pleasure and honor to be talking to Professor Mark Parsons from the Edinburgh Parallel Computing Center. And we're gonna talk a little about exa scale. What? It means we're gonna talk less about the technology on Maura about the science, the requirements on the need for exa scale. Uh, rather than a deep dive into the enabling technologies. Mark. Welcome. >>I then thanks very much for inviting me to tell me >>complete pleasure. Um, so I'd like to kick off with, I suppose. Quite an interesting look back. You and I are both of a certain age 25 plus, Onda. We've seen these milestones. Uh, I suppose that the S I milestones of high performance computing's come and go, you know, from a gig a flop back in 1987 teraflop in 97 a petaflop in 2000 and eight. But we seem to be taking longer in getting to an ex a flop. Um, so I'd like your thoughts. Why is why is an extra flop taking so long? >>So I think that's a very interesting question because I started my career in parallel computing in 1989. I'm gonna join in. IPCC was set up then. You know, we're 30 years old this year in 1990 on Do you know the fastest computer we have them is 800 mega flops just under a getting flogged. So in my career, we've gone already. When we reached the better scale, we'd already gone pretty much a million times faster on, you know, the step from a tariff block to a block scale system really didn't feel particularly difficult. Um, on yet the step from A from a petaflop PETA scale system. To an extent, block is a really, really big challenge. And I think it's really actually related to what's happened with computer processes over the last decade, where, individually, you know, approached the core, Like on your laptop. Whoever hasn't got much faster, we've just got more often So the perception of more speed, but actually just being delivered by more course. And as you go down that approach, you know what happens in the supercomputing world as well. We've gone, uh, in 2010 I think we had systems that were, you know, a few 1000 cores. Our main national service in the UK for the last eight years has had 118,000 cores. But looking at the X scale we're looking at, you know, four or five million cores on taming that level of parallelism is the real challenge. And that's why it's taking an enormous and time to, uh, deliver these systems. That is not just on the hardware front. You know, vendors like HP have to deliver world beating technology and it's hard, hard. But then there's also the challenge to the users. How do they get the codes to work in the face of that much parallelism? >>If you look at what the the complexity is delivering an annex a flop. Andi, you could have bought an extra flop three or four years ago. You couldn't have housed it. You couldn't have powered it. You couldn't have afforded it on, do you? Couldn't program it. But you still you could have You could have bought one. We should have been so lucky to be unable to supply it. Um, the software, um I think from our standpoint, is is looking like where we're doing mawr enabling with our customers. You sell them a machine on, then the the need then to do collaboration specifically seems mawr and Maura around the software. Um, so it's It's gonna be relatively easy to get one x a flop using limb pack, but but that's not extra scale. So what do you think? On exa scale machine versus an X? A flop machine means to the people like yourself to your users, the scientists and industry. What is an ex? A flop versus >>an exa scale? So I think, you know, supercomputing moves forward by setting itself challenges. And when you when you look at all of the excess scale programs worldwide that are trying to deliver systems that can do an X a lot form or it's actually very arbitrary challenge. You know, we set ourselves a PETA scale challenge delivering a petaflop somebody manage that, Andi. But you know, the world moves forward by setting itself challenges e think you know, we use quite arbitrary definition of what we mean is well by an exit block. So, you know, in your in my world, um, we either way, first of all, see ah flop is a computation, so multiply or it's an ad or whatever on we tend. Thio, look at that is using very high precision numbers or 64 bit numbers on Do you know, we then say, Well, you've got to do the next block. You've got to do a billion billion of those calculations every second. No, a some of the last arbitrary target Now you know today from HPD Aiken by my assistant and will do a billion billion calculations per second. And they will either do that as a theoretical peak, which would be almost unattainable, or using benchmarks that stressed the system on demonstrate a relaxing law. But again, those benchmarks themselves attuned Thio. Just do those calculations and deliver and explore been a steady I'll way if you like. So, you know, way kind of set ourselves this this this big challenge You know, the big fence on the race course, which were clambering over. But the challenge in itself actually should be. I'm much more interesting. The water we're going to use these devices for having built um, eso. Getting into the extra scale era is not so much about doing an extra block. It's a new generation off capability that allows us to do better scientific and industrial research. And that's the interesting bit in this whole story. >>I would tend to agree with you. I think the the focus around exa scale is to look at, you know, new technologies, new ways of doing things, new ways of looking at data and to get new results. So eventually you will get yourself a nexus scale machine. Um, one hopes, sooner rather >>than later. Well, I'm sure you don't tell me one, Ben. >>It's got nothing to do with may. I can't sell you anything, Mark. But there are people outside the door over there who would love to sell you one. Yes. However, if we if you look at your you know your your exa scale machine, Um, how do you believe the workloads are going to be different on an extra scale machine versus your current PETA scale machine? >>So I think there's always a slight conceit when you buy a new national supercomputer. On that conceit is that you're buying a capability that you know on. But many people will run on the whole system. Known truth. We do have people that run on the whole of our archer system. Today's A 118,000 cores, but I would say, and I'm looking at the system. People that run over say, half of that can be counted on Europe on a single hand in a year, and they're doing very specific things. It's very costly simulation they're running on. So, you know, if you look at these systems today, two things show no one is. It's very difficult to get time on them. The Baroque application procedures All of the requirements have to be assessed by your peers and your given quite limited amount of time that you have to eke out to do science. Andi people tend to run their applications in the sweet spot where their application delivers the best performance on You know, we try to push our users over time. Thio use reasonably sized jobs. I think our average job says about 20,000 course, she's not bad, but that does mean that as we move to the exits, kill two things have to happen. One is actually I think we've got to be more relaxed about giving people access to the system, So let's give more people access, let people play, let people try out ideas they've never tried out before. And I think that will lead to a lot more innovation and computational science. But at the same time, I think we also need to be less precious. You know, we to accept these systems will have a variety of sizes of job on them. You know, we're still gonna have people that want to run four million cores or two million cores. That's absolutely fine. Absolutely. Salute those people for trying really, really difficult. But then we're gonna have a huge spectrum of views all the way down to people that want to run on 500 cores or whatever. So I think we need Thio broaden the user base in Alexa Skill system. And I know this is what's happening, for example, in Japan with the new Japanese system. >>So, Mark, if you cast your mind back to almost exactly a year ago after the HPC user forum, you were interviewed for Premier Magazine on Do you alluded in that article to the needs off scientific industrial users requiring, you know, uh on X a flop or an exa scale machine it's clear in your in your previous answer regarding, you know, the workloads. Some would say that the majority of people would be happier with, say, 10 100 petaflop machines. You know, democratization. More people access. But can you provide us examples at the type of science? The needs of industrial users that actually do require those resources to be put >>together as an exa scale machine? So I think you know, it's a very interesting area. At the end of the day, these systems air bought because they are capability systems on. I absolutely take the argument. Why shouldn't we buy 10 100 pattern block systems? But there are a number of scientific areas even today that would benefit from a nexus school system and on these the sort of scientific areas that will use as much access onto a system as much time and as much scale of the system as they can, as you can give them eso on immediate example. People doing chroma dynamics calculations in particle physics, theoretical calculations, they would just use whatever you give them. But you know, I think one of the areas that is very interesting is actually the engineering space where, you know, many people worry the engineering applications over the last decade haven't really kept up with this sort of supercomputers that we have. I'm leading a project called Asimov, funded by M. P S O. C in the UK, which is jointly with Rolls Royce, jointly funded by Rolls Royce and also working with the University of Cambridge, Oxford, Bristol, Warrick. We're trying to do the whole engine gas turbine simulation for the first time. So that's looking at the structure of the gas turbine, the airplane engine, the structure of it, how it's all built it together, looking at the fluid dynamics off the air and the hot gasses, the flu threat, looking at the combustion of the engine looking how fuel is spread into the combustion chamber. Looking at the electrics around, looking at the way the engine two forms is, it heats up and cools down all of that. Now Rolls Royce wants to do that for 20 years. Andi, Uh, whenever they certify, a new engine has to go through a number of physical tests, and every time they do on those tests, it could cost them as much as 25 to $30 million. These are very expensive tests, particularly when they do what's called a blade off test, which would be, you know, blade failure. They could prove that the engine contains the fragments of the blade. Sort of think, continue face really important test and all engines and pass it. What we want to do is do is use an exa scale computer to properly model a blade off test for the first time, so that in future, some simulations can become virtual rather than having thio expend all of the money that Rolls Royce would normally spend on. You know, it's a fascinating project is a really hard project to do. One of the things that I do is I am deaf to share this year. Gordon Bell Price on bond I've really enjoyed to do. That's one of the major prizes in our area, you know, gets announced supercomputing every year. So I have the pleasure of reading all the submissions each year. I what's been really interesting thing? This is my third year doing being on the committee on what's really interesting is the way that big systems like Summit, for example, in the US have pushed the user communities to try and do simulations Nowhere. Nobody's done before, you know. And we've seen this as well, with papers coming after the first use of the for Goku system in Japan, for example, people you know, these are very, very broad. So, you know, earthquake simulation, a large Eddie simulations of boats. You know, a number of things around Genome Wide Association studies, for example. So the use of these computers spans of last area off computational science. I think the really really important thing about these systems is their challenging people that do calculations they've never done before. That's what's important. >>Okay, Thank you. You talked about challenges when I nearly said when you and I had lots of hair, but that's probably much more true of May. Um, we used to talk about grand challenges we talked about, especially around the teraflop era, the ski red program driving, you know, the grand challenges of science, possibly to hide the fact that it was a bomb designing computer eso they talked about the grand challenges. Um, we don't seem to talk about that much. We talk about excess girl. We talk about data. Um Where are the grand challenges that you see that an exa scale computer can you know it can help us. Okay, >>so I think grand challenges didn't go away. Just the phrase went out of fashion. Um, that's like my hair. I think it's interesting. The I do feel the science moves forward by setting itself grand challenges and always had has done, you know, my original backgrounds in particle physics. I was very lucky to spend four years at CERN working in the early stage of the left accelerator when it first came online on. Do you know the scientists there? I think they worked on left 15 years before I came in and did my little ph d on it. Andi, I think that way of organizing science hasn't changed. We just talked less about grand challenges. I think you know what I've seen over the last few years is a renaissance in computational science, looking at things that have previously, you know, people have said have been impossible. So a couple of years ago, for example, one of the key Gordon Bell price papers was on Genome Wide Association studies on some of it. If I may be one of the winner of its, if I remember right on. But that was really, really interesting because first of all, you know, the sort of the Genome Wide Association Studies had gone out of favor in the bioinformatics by a scientist community because people thought they weren't possible to compute. But that particular paper should Yes, you could do these really, really big Continental little problems in a reasonable amount of time if you had a big enough computer. And one thing I felt all the way through my career actually is we've probably discarded Mawr simulations because they were impossible at the time that we've actually decided to do. And I sometimes think we to challenge ourselves by looking at the things we've discovered in the past and say, Oh, look, you know, we could actually do that now, Andi, I think part of the the challenge of bringing an extra service toe life is to get people to think about what they would use it for. That's a key thing. Otherwise, I always say, a computer that is unused to just be turned off. There's no point in having underutilized supercomputer. Everybody loses from that. >>So Let's let's bring ourselves slightly more up to date. We're in the middle of a global pandemic. Uh, on board one of the things in our industry has bean that I've been particularly proud about is I've seen the vendors, all the vendors, you know, offering up machine's onboard, uh, making resources available for people to fight things current disease. Um, how do you see supercomputers now and in the future? Speeding up things like vaccine discovery on help when helping doctors generally. >>So I think you're quite right that, you know, the supercomputer community around the world actually did a really good job of responding to over 19. Inasmuch as you know, speaking for the UK, we put in place a rapid access program. So anybody wanted to do covert research on the various national services we have done to the to two services Could get really quick access. Um, on that, that has worked really well in the UK You know, we didn't have an archer is an old system, Aziz. You know, we didn't have the world's largest supercomputer, but it is happily bean running lots off covert 19 simulations largely for the biomedical community. Looking at Druk modeling and molecular modeling. Largely that's just been going the US They've been doing really large uh, combinatorial parameter search problems on on Summit, for example, looking to see whether or not old drugs could be reused to solve a new problem on DSO, I think, I think actually, in some respects Kobe, 19 is being the sounds wrong. But it's actually been good for supercomputing. Inasmuch is pointed out to governments that supercomputers are important parts off any scientific, the active countries research infrastructure. >>So, um, I'll finish up and tap into your inner geek. Um, there's a lot of technologies that are being banded around to currently enable, you know, the first exa scale machine, wherever that's going to be from whomever, what are the current technologies or emerging technologies that you are interested in excited about looking forward to getting your hands on. >>So in the business case I've written for the U. K's exa scale computer, I actually characterized this is a choice between the American model in the Japanese model. Okay, both of frozen, both of condoms. Eso in America, they're very much gone down the chorus plus GPU or GPU fruit. Um, so you might have, you know, an Intel Xeon or an M D process er center or unarmed process or, for that matter on you might have, you know, 24 g. P. U s. I think the most interesting thing that I've seen is definitely this move to a single address space. So the data that you have will be accessible, but the G p u on the CPU, I think you know, that's really bean. One of the key things that stopped the uptake of GPS today and that that that one single change is going Thio, I think, uh, make things very, very interesting. But I'm not entirely convinced that the CPU GPU model because I think that it's very difficult to get all the all the performance set of the GPU. You know, it will do well in H p l, for example, high performance impact benchmark we're discussing at the beginning of this interview. But in riel scientific workloads, you know, you still find it difficult to find all the performance that has promised. So, you know, the Japanese approach, which is the core, is only approach. E think it's very attractive, inasmuch as you know They're using very high bandwidth memory, very interesting process of which they are going to have to, you know, which they could develop together over 10 year period. And this is one thing that people don't realize the Japanese program and the American Mexico program has been working for 10 years on these systems. I think the Japanese process really interesting because, um, it when you look at the performance, it really does work for their scientific work clothes, and that's that does interest me a lot. This this combination of a A process are designed to do good science, high bandwidth memory and a real understanding of how data flows around the supercomputer. I think those are the things are exciting me at the moment. Obviously, you know, there's new networking technologies, I think, in the fullness of time, not necessarily for the first systems. You know, over the next decade we're going to see much, much more activity on silicon photonics. I think that's really, really fascinating all of these things. I think in some respects the last decade has just bean quite incremental improvements. But I think we're supercomputing is going in the moment. We're a very very disruptive moment again. That goes back to start this discussion. Why is extra skill been difficult to get? Thio? Actually, because the disruptive moment in technology. >>Professor Parsons, thank you very much for your time and your insights. Thank you. Pleasure and folks. Thank you for watching. I hope you've learned something, or at least enjoyed it. With that, I would ask you to stay safe and goodbye.

>> Narrator: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in San Mateo, California right at the crossroads. The building's called The Crossroads but it's right at the crossroads of 92 and 101. It's a really interesting intersection over the years as you watch these buildings that are on the corner continue to change names. I always think of the Seibel, his first building came up on this corner and we're here to see a good friend of SnapLogic and their brand new building. Gaurav Dhillon, Chairman and CEO, great to see you. >> Pleasure to be here. >> So how long you been in this space? >> Gosh, it's been about a year. >> Okay. >> Although it feels longer. It's a high-growth company so these are dog years. (laughs) >> That's right. and usually, you outgrow it before you all have moved in. >> The years are short but the days are long. >> And it's right next Rakuten, I have to mention it. We all see it on the Warriors' jerseys So now we know who they are and where they are exactly. >> No they're a good outfit. We had an interesting time putting a sign up and then the people who made their sign told us all kinds of back stories. >> Oh, good, good Alright. So give us an update on SnapLogic. You guys are in a great space at a really, really good time. >> You know, things been on a roll. As you know, the mission we set out to... engage with was to bring together applications and data in the enterprise. We have some of the largest customers in high technology. Folks like Qualcomm, Workday. Some of the largest customers in pharmaceuticals. Folks like Astrazeneca, Bristol-Meyers Squibb. In retail, Denny's, Wendy's, etc. And these folks are basically bringing in new cloud applications and moving data into the cloud. And it's really fun to wire that all up for them. And there's more of it every day and now that we have this very strong install-base of customers, we're able to get more customers faster. >> Right. >> In good time. >> It's a great time and the data is moving into the cloud, and the public cloud guys are really making bigger plays into the enterprise, Microsoft and, Amazon and Google. And of course, there's IBM and lots of other clouds. But integration's always been such a pain and I finally figured out what the snap in SnapLogic means after interviewing you >> (laughs) a couple of times, right. But this whole idea of, non-developer development and you're taking that into integration which is a really interesting concept, enabled by cloud, where you can now think of snapping things together, versus coding, coding, coding. >> Yeah Cloud and A.I, right We feel that this problem has grown because of the change in the platform. The compute platform's gone to the cloud. Data's going to the cloud. There was bunch of news the other day about more and more companies moving the analytics into the cloud. And as that's happening, we feel that this approach and the question we ask ourselves when we started this company, we got into building the born in the cloud platform was, what would Apple do if they were to build an integration product? And the answer was, they would make it like the iPhone, which is easy to use, but very powerful at the same time. And if you can do that, you can bring in a massive population of users who wouldn't have been able to do things like video chat. My mom was not able to do video chat, and believe me, we tried this and every other thing possible 'till facetime came along. And now she can talk to my daughter and she can do it without help, any assistance from teenage grandchildren on that side, Right? >> Right, Right >> So what we've done with SnapLogic, is by bringing in a beautiful, powerful, sleek interface, with a lot of capability in how it connects, snaps together apps and data, we've brought in a whole genre of people who need data in the enterprise so they can serve themselves data. So if your title has analyst in it, you don't have to be programmer analyst. You could be any analyst. >> Right >> You could be a compensation analyst, a commissions analyst, a finance analyst, an HR analyst. All those people can self-serve information, knock down silos, and integrate things themselves. >> It's so interesting because we talk a lot about innovation and digital transformation, and in doing thousands of these interviews, I think the answer to innovation is actually pretty simple. You give more people access to the data. You give them more access to the tools to work with the data and then you give them the power to actually do something once they figure something out. And you guys are really right in the middle of that. So before, it was kind of >> (laughs) Yeah >> democratization of the data, democratization of the tools to work with the data, but in the API economy, you got to be able to stitch this stuff together because it's not just one application, it's not just one data source. >> Correct >> You're bringing from lots and lots of different things and that's really what you guys are taking advantage of this cloud infrastructure which has everything available, so it's there to connect, >> (laughs) Versus, silo in company one and silo in company two. So are you seeing it though, in terms of, of people enabling, kind of citizen integrators if you will, versus citizen developers. >> Yeah. Heck Yeah. So I'll give you an example. One of our large customers... Adobe Systems, right here in San Jose has been amazingly successful flagship account for us. About 800 people at Adobe come to www.snaplogic.com, every week to self-serve data. We replaced legacy products like TIBCO, informatica web methods about four years ago. They first became a customer in 2014 and usage of those products was limited to Java programmers and Sequel programmers, and that was less than 50 people. And imagine that you have about 800 people doing self-service getting information do their jobs. Now, Adobe is unique in that, it's moved the cloud in a fantastic way, or it was unique in 2014. Now everybody is emulating them and the great success that they've had. With the cloud economic model, with the cloud ID model. This is working in spades. We have customers who've come on board in Q4. We're just rounding out Q1 and in less than 60, 90 days, every time I look, 50, 100, 200 people, from each large company, whether it's a cosmetics company, pharmaceuticals company, retailer, food merchandise, are coming in and using data. >> Right >> And it's proliferating, because the more successful they are, the better they are able to do in their jobs, tell their friends about it sort-of-thing, or next cubicle over, somebody wants to use that too. It's so interesting. Adobe is such a great example, cause they did transform their business. Used to be a really expensive license. You would try to find your one friend that worked there around Christmas >> (laughs) Cause you think they got two licenses a year they can buy for a grand. Like, I need an extra one I can get from you. But they moved to a subscription model. They made a big bet. >> Yes. Yes >> And they bet on the cloud, so now if you're a subscriber, which I am, I can work on my home machine, my work machine, go to machine, machine. So, it's a really great transformation story. The other piece of it though, is just this cloud application space. There's so many cloud applications that we all work with every day whether it's Basecamp, Salesforce, Hootsuite. There's a proliferation of these things and so they're there. They've got data. So the integration opportunity is unlike anything that was ever there before. Cause there isn't just one cloud. There isn't just one cloud app. There's a lot of them. >> Yes. >> How do I bring those together to be more productive? >> So here's a stat. The average enterprise has most cloud services or SAS applications, in marketing. On the average, they have 91 marketing applications or SAS applications. >> 91. That's the average. >> 96% of them are not connected together. >> Right. >> Okay. That's just one example. Now you go to HR, stock administration. You go into sales, CRM, and all the ancillary systems around CRM. And there is this sort of massive, to us, opportunity of knocking down these silos and making things work together. You mention the API economy and whilst that's true that all these SAS applications of APIs. The problem is, most companies don't have programmers to hook up those API's. >> Right. To connect them. >> Yes, in Silicon Valley we do and maybe in Manhattan they do, but in everywhere else in the world, the self-service model, the model of being able to do it to something that is simple, yet powerful. Enterprise great >> Right. Right >> and simple, beautiful is absolutely the winning formula in our perspective. So the answer is to let these 100 applications bloom, but to keep them well behaved and orchestrated, in kind of a federated model, where security, having one view of the world, etc., is managed by SnapLogic and then various people and departments can bring in a blessed, SAS applications and then snap them in and the input and the way they connect, is done through snaps. And we've found that to be a real winning model for our customers. >> So you don't have to have like 18 screens open all with different browsers and different apps. >> Swivel chair integration is gone. Swivel chair integration is gone. >> Step above sneakernet but still not-- >> Step above but still not. And again, it may make sense in very, very specific super high-speed, like Wall Street, high frequency trading and hedge funds, but it's a minuscule minority of the overall problems that there needs to be solved. >> Right. So, it's just a huge opportunity, you just are cleaning up behind the momentum in the SAS applications, the momentum of the cloud. >> Cloud data. Cloud apps. Cloud data. And in general, if a customer's not going to the cloud, they're probably not the best for us. >> Right. >> Right. Our customers' almost always going towards the cloud, have lots of data and applications on premise. And in that hybrid spot, we have the capability to straddle that kind of architecture in a way that nobody else does. Because we have a born in the cloud platform that was designed to work in the real world, which is hybrid. >> So another interesting thing, a lot of talk about big data over the years. Now it's just kind of there. But AI and machine learning. Artificial intelligence which should be automated intelligence and machine learning. There's kind of the generic, find an old, dead guy and give it a name. But we're really seeing the values that's starting to bubble up in applications. It's not, AI generically, >> Correct. >> It's how are you enabling a more efficient application, a more efficient workflow, a more efficient, get your job done, using AI. And you guys are starting to incorporate that in your integration framework. >> Yes. Yes. So we took the approach, 'doctor heal thyself.' And we're going to help our customers do better job of having AI be a game changer for them. How do we apply that to ourselves? We heard one our CIOs, CI of AstraZeneca, Dave Smoley, was handing out the Amazon Alexa Echo boxes one Christmas. About three years ago and I'm like, my gosh that's right. That was what Walt Mossberg said in his farewell column. IT is going to be everywhere and invisible at the same time. Right. >> Right. >> It'll be in the walls, so to speak. So we applied AI, starting about two years ago, actually now three, because we shipped Iris a year ago. The artificial intelligence capability inside SnapLogic has been shipping for over 12 months. Fantastic usage. But we applied to ourselves the challenge about three years ago, to use AI based on our born in the cloud platform. On the metadata that we have about people are doing. And in the sense, apply Google Autocomplete into enterprise connectivity problems. And it's been amazing. The AI as you start to snap things together, as you put one or two snaps, and you start to look for the third, it starts to get 98.7% accurate, in predicting how to connect SAS applications together. >> Right. Right. >> It's not quite autonomous integration yet but you can see where we're going with it. So it's starting to do so much value add that most of our customers, leave it on. Even the seasoned professionals who are proficient and running a center of excellence using SnapLogic, even those people choose to have sort-of this AI, on all the time helping them. And that engagement comes from the value that they're getting, as they do these things, they make less mistakes. All the choices are readily at hand and that's happening. So that's one piece of it >> Right. >> Sorry. Let me... >> It's Okay. Keep going. >> Illustrate one other thing. Napoleon famously said, "An army marches on its stomach" AI marches on data. So, what we found is the more data we've had and more customers that we've had, we move about a trillion documents for our customers worldwide, in the past 30 days. That is up from 10 million documents in 30 days, two years ago. >> Right. Right >> That more customers and more usage. In other words, they're succeeding. What we've found as we've enriched our AI with data, it's gotten better and better. And now, we're getting involved with customers' projects where they need to support data scientists, data engineering work for machine learning and that self-service intricate model is letting someone who was trying to solve a problem of, When is my Uber going to show up? So to speak. In industry X >> Right. Right. >> These kinds of hard AI problems that are predictive. That are forward changing in a sense. Those kind of problems are being solved by richer data and many of them, the projects that we're now involved in, are moving data into the cloud for data lake to then support AI machine learning efforts for our customers. >> So you jumped a little bit, I want to talk on your first point. >> Okay. Sorry >> That's okay. Which is that you're in the very fortunate position because you have all that data flow. You have the trillion documents that are changing hands every month. >> Born in the cloud platform. >> So you've got it, right? >> Got it. >> You've got the data. >> It's a virtual cycle. It's a virtual cycle. Some people call it data capitalism. I quibble with that. We're not sort-of, mining and selling people's personal data to anybody. >> Right. Right. >> But this is where, our enterprise customers' are so pleased to work with us because if we can increase productivity. If we can take the time to solution, the time to integration, forward by 10 times, we can improve the speed that by SAS application and it gets into production 10 times faster. That is such a good trade for them and for everyone else. >> Right. Right. >> And it feeds on itself. It's a virtual cycle. >> You know in the Marketo to the Salesforce integration, it's nothing. You need from company A to company B. >> I bet you somebody in this building is doing it on a different floor right now. >> Exactly. >> (laughs) >> So I think that's such an interesting thing. In the other piece that I like is how again, I like your kind of Apple analogy, is the snap packs, right. Because we live in a world, with even though there 91 on-averages, there's a number of really dominant SAS application that most people use, you can really build a group of snaps. Is snap the right noun? >> That's the right word. >> Of snaps. In a snap pack around the specific applications, then to have your AI powered by these trillion transactions that you have going through the machines, really puts you in a unique position right now. >> It does, you know. And we're very fortunate to have the kind of customer support we've had and, sort of... Customer advisory board. Big usages of our products. In which we've added so much value to our customers, that they've started collaborating with us in a sense. And are passing to us wonderful ideas about how to apply this including AI. >> Right. >> And we're not done yet. We have a vision in the future towards an autonomous integration. You should be able to say "SnapLogic, Iris, "connect my company." And it should. >> Right. Right. >> It knows what the SAS apps are by looking at your firewall, and if you're people are doing things, building pipelines, connecting your on-premise legacy applications kind of knows what they are. That day when you should be able to, in a sense, have a bot of some type powered by all this technology in a thoughtful manner. It's not that far. It's closer at hand than people might realize. >> Which is crazy science fiction compared to-- I mean, integration was always the nightmare right back in the day. >> It is. >> Integration, integration. >> But on the other hand, it is starting to have contours that are well defined. To your point, there are certain snaps that are used more. There are certain problems that are solved quite often, the quote-to-cash problem is as old as enterprise software. You do a quote in the CRM system. Your cash is in a financial system. How does that work together? These sort of problems, in a sense, are what McKinsey and others are starting to call robotic process automations. >> Right. >> In the industrial age, people... Stopped, with the industrial age, any handcrafted widget. Nuts, and bolts, and fasteners started being made on machines. You could stamp them out. You could have power driven beams, etc., etc. To make things in industrial manner. And our feeling is, some of the knowledge tasks that feel like widget manufactures. You're doing them over and over again. Or robotic, so to speak, should be automated. And integration I think, is ripe as one of those things and using the value of integration, our customers can automate a bunch of other repeatable tasks like quote-to-cash. >> Right. Right. It's interesting just when you say autonomous, I can't help but think of autonomous vehicles right, which are all the rage and also in the news. And people will say "well I like to drive "or of course we all like to drive "on Sunday down at the beach" >> Sure. Yeah. >> But we don't like to sit in traffic on the way to work. That's not driving, that's sitting in traffic on the way to work. Getting down the 101 to your exit and off again is really not that complicated, in terms of what you're trying to accomplish. >> Indeed. Indeed. >> Sets itself up. >> And there are times you don't want to. I mean one of the most pleasant headlines, most of the news is just full of bad stuff right. So and so and such and such. But one of the very pleasing headlines I saw the other day in a newspaper was, You know what's down a lot? Not bay area housing prices. >> (laughs) >> But you know what's down a lot? DUI arrests, have plummeted. Because of the benefits of Lyft and Uber. More and more people are saying, "You know, I don't have to call a black cab. "I don't need to spend a couple hundred bucks to get home. "I'm just getting a Lyft or an Uber." So the benefits of some of these are starting to appear as in plummeting DUIs. >> Right. Right >> Plummeting fatalities. From people driving while inebriated. Plunging into another car or sidewalk. >> Right. Right. >> So Yes. >> Amara's Law. He never gets enough credit. >> (laughs) >> I say it in every interview right. We overestimate in the short term and we underestimate in the long term the effects of these technologies cause we get involved-- The Gartner store. It's the hype cycle. >> Yeah, Yeah >> But I really I think Amara nailed it and over time, really significant changes start to take place. >> Indeed and we're seeing them now. >> Alright well Gaurav, great to get an update from you and a beautiful facility here. Thanks for having us on. >> Thank you, thank you. A pleasure to be here. Great to see you as well. >> Alright He's Gaurav, I'm Jeff. And you're watching theCUBE from SnapLogic's headquarters Thanks for watching. (techno music)

>> Narrator: From San Mateo, California, it's theCUBE covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in San Mateo, California right at the crossroads. The building's called The Crossroads but it's right at the crossroads of 92 and 101. It's a really interesting intersection over the years as you watch these buildings that are on the corner continue to change names. I always think of the Seville, his first building came up on this corner and we're here to see a good friend of SnapLogic and their brand new building. Gaurav Dhillon, Chairman and CEO, great to see you. >> Pleasure to be here. >> So how long you been in this space? >> Gosh, it's been about a year. >> Okay. >> Although it feels longer. It's a high-growth company so these are dog years. (laughs) >> That's right. and usually, you outgrow it before you all have moved in. >> The years are short but the days are long. >> And it's right next Rakuten, I have to mention it. We all see it on the Warriors' jerseys So now we know who they are and where they are exactly. >> No they're a good outfit. We had an interesting time putting a sign up and then the people who made their sign told us all kinds of back stories. >> Oh, good, good Alright. So give us an update on SnapLogic. You guys are in a great space at a really, really good time. >> You know, things been on a roll. As you know, the mission we set out to... engage with was to bring together applications and data in the enterprise. We have some of the largest customers in high technology. Folks like Qualcomm, Workday. Some of the largest customers in pharmaceuticals. Folks like Astrazeneca, Bristol-Meyers Squibb. In retail, Denny's, Wendy's, etc. And these folks are basically bringing in new cloud applications and moving data into the cloud. And it's really fun to wire that all up for them. And there's more of it every day and now that we have this very strong install-base of customers, we're able to get more customers faster. >> Right. >> In good time. >> It's a great time and the data is moving into the cloud, and the public cloud guys are really making bigger plays into the enterprise, Microsoft and, Amazon and Google. And of course, there's IBM and lots of other clouds. But integration's always been such a pain and I finally figured out what the snap in SnapLogic means after interviewing you >> (laughs) a couple of times, right. But this whole idea of, non-developer development and you're taking that into integration which is a really interesting concept, enabled by cloud, where you can now think of snapping things together, versus coding, coding, coding. >> Yeah Cloud and A.I, right We feel that this problem has grown because of the change in the platform. The compute platform's gone to the cloud. Data's going to the cloud. There was bunch of news the other day about more and more companies moving the analytics into the cloud. And as that's happening, we feel that this approach and the question we ask ourselves when we started this company, we got into building the born in the cloud platform was, what would Apple do if they were to build an integration product? And the answer was, they would make it like the iPhone, which is easy to use, but very powerful at the same time. And if you can do that, you can bring in a massive population of users who wouldn't have been able to do things like video chat. My mom was not able to do video chat, and believe me, we tried this and every other thing possible 'till facetime came along. And now she can talk to my daughter and she can do it without help, any assistance from teenage grandchildren on that side, Right? >> Right, Right >> So what we've done with SnapLogic, is by bringing in a beautiful, powerful, sleek interface, with a lot of capability in how it connects, snaps together apps and data, we've brought in a whole genre of people who need data in the enterprise so they can serve themselves data. So if your title has analyst in it, you don't have to be programmer analyst. You could be any analyst. >> Right >> You could be a compensation analyst, a commissions analyst, a finance analyst, an HR analyst. All those people can self-serve information, knock down silos, and integrate things themselves. >> It's so interesting because we talk a lot about innovation and digital transformation, and in doing thousands of these interviews, I think the answer to innovation is actually pretty simple. You give more people access to the data. You give them more access to the tools to work with the data and then you give them the power to actually do something once they figure something out. And you guys are really right in the middle of that. So before, it was kind of >> (laughs) Yeah >> democratization of the data, democratization of the tools to work with the data, but in the API economy, you got to be able to stitch this stuff together because it's not just one application, it's not just one data source. >> Correct >> You're bringing from lots and lots of different things and that's really what you guys are taking advantage of this cloud infrastructure which has everything available, so it's there to connect, >> (laughs) Versus, silo in company one and silo in company two. So are you seeing it though, in terms of, of people enabling, kind of citizen integrators if you will, versus citizen developers. >> Yeah. Heck Yeah. So I'll give you an example. One of our large customers... Adobe Systems, right here in San Jose has been amazingly successful flagship account for us. About 800 people at Adobe come to www.snaplogic.com, every week to self-serve data. We replaced legacy products like DIBCO, informatica web methods about four years ago. They first became a customer in 2014 and usage of those products was limited to Java programmers and Sequel programmers, and that was less than 50 people. And imagine that you have about 800 people doing self-service getting information do their jobs. Now, Adobe is unique in that, it's moved the cloud in a fantastic way, or it was unique in 2014. Now everybody is emulating them and the great success that they've had. With the cloud economic model, with the cloud ID model. This is working in spades. We have customers who've come on board in Q4. We're just rounding out Q1 and in less than 60, 90 days, every time I look, 50, 100, 200 people, from each large company, whether it's a cosmetics company, pharmaceuticals company, retailer, food merchandise, are coming in and using data. >> Right >> And it's proliferating, because the more successful they are, the better they are able to do in their jobs, tell their friends about it sort-of-thing, or next cubicle over, somebody wants to use that too. It's so interesting. Adobe is such a great example, cause they did transform their business. Used to be a really expensive license. You would try to find your one friend that worked there around Christmas >> (laughs) Cause you think they got two licenses a year they can buy for a grand. Like, I need an extra one I can get from you. But they moved to a subscription model. They made a big bet. >> Yes. Yes >> And they bet on the cloud, so now if you're a subscriber, which I am, I can work on my home machine, my work machine, go to machine, machine. So, it's a really great transformation story. The other piece of it though, is just this cloud application space. There's so many cloud applications that we all work with every day whether it's Basecamp, Salesforce, Hootsuite. There's a proliferation of these things and so they're there. They've got data. So the integration opportunity is unlike anything that was ever there before. Cause there isn't just one cloud. There isn't just one cloud app. There's a lot of them. >> Yes. >> How do I bring those together to be more productive? >> So here's a stat. The average enterprise has most cloud services or SAS applications, in marketing. On the average, they have 91 marketing applications or SAS applications. >> 91. That's the average. >> 96% of them are not connected together. >> Right. >> Okay. That's just one example. Now you go to HR, stock administration. You go into sales, CRM, and all the ancillary systems around CRM. And there is this sort of massive, to us, opportunity of knocking down these silos and making things work together. You mention the API economy and whilst that's true that all these SAS applications of APIs. The problem is, most companies don't have programmers to hook up those API's. >> Right. To connect them. >> Yes, in Silicon Valley we do and maybe in Manhattan they do, but in everywhere else in the world, the self-service model, the model of being able to do it to something that is simple, yet powerful. Enterprise great >> Right. Right >> and simple, beautiful is absolutely the winning formula in our perspective. So the answer is to let these 100 applications bloom, but to keep them well behaved and orchestrated, in kind of a federated model, where security, having one view of the world, etc., is managed by SnapLogic and then various people and departments can bring in a blessed, SAS applications and then snap them in and the input and the way they connect, is done through snaps. And we've found that to be a real winning model for our customers. >> So you don't have to have like 18 screens open all with different browsers and different apps. >> Swivel chair integration is gone. Swivel chair integration is gone. >> Step above sneakernet but still not-- >> Step above but still not. And again, it may make sense in very, very specific super high-speed, like Wall Street, high frequency trading and hedge funds, but it's a minuscule minority of the overall problems that there needs to be solved. >> Right. So, it's just a huge opportunity, you just are cleaning up behind the momentum in the SAS applications, the momentum of the cloud. >> Cloud data. Cloud apps. Cloud data. And in general, if a customer's not going to the cloud, they're probably not the best for us. >> Right. >> Right. Our customers' almost always going towards the cloud, have lots of data and applications on premise. And in that hybrid spot, we have the capability to straddle that kind of architecture in a way that nobody else does. Because we have a born in the cloud platform that was designed to work in the real world, which is hybrid. So another interesting thing, a lot of talk about big data over the years. Now it's just kind of there. But AI and machine learning. Artificial intelligence which should be automated intelligence and machine learning. There's kind of the generic, find an old, dead guy and give it a name. But we're really seeing the values that's starting to bubble up in applications. It's not, AI generically, >> Correct. >> It's how are you enabling a more efficient application, a more efficient workflow, a more efficient, get your job done, using AI. And you guys are starting to incorporate that in your integration framework. >> Yes. Yes. So we took the approach, 'doctor heal thyself.' And we're going to help our customers do better job of having AI be a game changer for them. How do we apply that to ourselves? We heard one our CIOs, CI of AstraZeneca, Dave Smoley, was handing out the Amazon Alexa Echo boxes one Christmas. About three years ago and I'm like, my gosh that's right. That was what Walt Mossberg said in his farewell column. IT is going to be everywhere and invisible at the same time. Right. >> Right. >> It'll be in the walls, so to speak. So we applied AI, starting about two years ago, actually now three, because we shipped iris a year ago. The artificial intelligence capability inside SnapLogic has been shipping for over 12 months. Fantastic usage. But we applied to ourselves the challenge about three years ago, to use AI based on our born in the cloud platform. On the metadata that we have about people are doing. And in the sense, apply Google Autocomplete into enterprise connectivity problems. And it's been amazing. The AI as you start to snap things together, as you put one or two snaps, and you start to look for the third, it starts to get 98.7% accurate, in predicting how to connect SAS applications together. >> Right. Right. >> It's not quite autonomous integration yet but you can see where we're going with it. So it's starting to do so much value add that most of our customers, leave it on. Even the seasoned professionals who are proficient and running a center of excellence using SnapLogic, even those people choose to have sort-of this AI, on all the time helping them. And that engagement comes from the value that they're getting, as they do these things, they make less mistakes. All the choices are readily at hand and that's happening. So that's one piece of it >> Right. >> Sorry. Let me... >> It's Okay. Keep going. >> Illustrate one other thing. Napoleon famously said, "An army marches on it's stomach" AI marches on data. So, what we found is the more data we've had and more customers that we've had, we move about a trillion documents for our customers worldwide, in the past 30 days. That is up from 10 million documents in 30 days, two years ago. >> Right. Right >> That more customers and more usage. In other words, they're succeeding. What we've found as we've enriched our AI with data, it's gotten better and better. And now, we're getting involved with customers' projects where they need to support data scientists, data engineering work for machine learning and that self-service intricate model is letting someone who was trying to solve a problem of, When is my Uber going to show up? So to speak. In industry X >> Right. Right. >> These kinds of hard AI problems that are predictive. That are forward changing in a sense. Those kind of problems are being solved by richer data and many of them, the projects that we're now involved in, are moving data into the cloud for data lake to then support AI machine learning efforts for our customers. >> So you jumped a little bit, I want to talk on your first point. >> Okay. Sorry >> That's okay. Which is that you're in the very fortunate position because you have all that data flow. You have the trillion documents that are changing hands every month. >> Born in the cloud platform. >> So you've got it, right? >> Got it. >> You've got the data. >> It's a virtual cycle. It's a virtual cycle. Some people call it data capitalism. I quibble with that. We're not sort-of, mining and selling people's personal data to anybody. >> Right. Right. >> But this is where, our enterprise customers' are so pleased to work with us because if we can increase productivity. If we can take the time to solution, the time to integration, forward by 10 times, we can improve the speed that by SAS application and it gets into production 10 times faster. That is such a good trade for them and for everyone else. >> Right. Right. >> And it feeds on itself. It's a virtual cycle. >> You know in the Marketo to the Salesforce integration, it's nothing. You need from company A to company B. >> I bet you somebody in this building is doing it on a different floor right now. >> Exactly. >> (laughs) >> So I think that's such an interesting thing. In the other piece that I like is how again, I like your kind of Apple analogy, is the snap packs, right. Because we live in a world, with even though there 91 on-averages, there's a number of really dominant SAS application that most people use, you can really build a group of snaps. Is snap the right noun? >> That's the right word. >> Of snaps. In a snap pack around the specific applications, then to have your AI powered by these trillion transactions that you have going through the machines, really puts you in a unique position right now. >> It does, you know. And we're very fortunate to have the kind of customer support we've had and, sort of... Customer advisory board. Big usages of our products. In which we've added so much value to our customers, that they've started collaborating with us in a sense. And are passing to us wonderful ideas about how to apply this including AI. >> Right. >> And we're not done yet. We have a vision in the future towards an autonomous integration. You should be able to say "SnapLogic, Iris, "connect my company." And it should. >> Right. Right. >> It knows what the SAS apps are by looking at your firewall, and if you're people are doing things, building pipelines, connecting your on-premise legacy applications kind of knows what they are. That day when you should be able to, in a sense, have a bot of some type powered by all this technology in a thoughtful manner. It's not that far. It's closer at hand than people might realize. >> Which is crazy science fiction compared to-- I mean, integration was always the nightmare right back in the day. >> It is. >> Integration, integration. >> But on the other hand, it is starting to have contours that are well defined. To your point, there are certain snaps that are used more. There are certain problems that are solved quite often, the quote-to-cash problem is as old as enterprise software. You do a quote in the CRM system. Your cash is in a financial system. How does that work together? These sort of problems, in a sense, are what McKinsey and others are starting to call robotic process automations. >> Right. >> In the industrial age, people... Stopped, with the industrial age, any handcrafted widget. Nuts, and bolts, and fasteners started being made on machines. You could stamp them out. You could have power driven beams, etc., etc. To make things in industrial manner. And our feeling is, some of the knowledge tasks that feel like widget manufactures. You're doing them over and over again. Or robotic, so to speak, should be automated. And integration I think, is ripe as one of those things and using the value of integration, our customers can automate a bunch of other repeatable tasks like quote-to-cash. >> Right. Right. It's interesting just when you say autonomous, I can't help but think of autonomous vehicles right, which are all the rage and also in the news. And people will say "well I like to drive "or of course we all like to drive "on Sunday down at the beach" >> Sure. Yeah. >> But we don't like to sit in traffic on the way to work. That's not driving, that's sitting in traffic on the way to work. Getting down the 101 to your exit and off again is really not that complicated, in terms of what you're trying to accomplish. >> Indeed. Indeed. >> Sets itself up. >> And there are times you don't want to. I mean one of the most pleasant headlines, most of the news is just full of bad stuff right. So and so and such and such. But one of the very pleasing headlines I saw the other day in a newspaper was, You know what's down a lot? Not bay area housing prices. >> (laughs) >> But you know what's down a lot? DUI arrests, have plummeted. Because of the benefits of Lyft and Uber. More and more people are saying, "You know, I don't have to call a black cab. "I don't need to spend a couple hundred bucks to get home. "I'm just getting a Lyft or an Uber." So the benefits of some of these are starting to appear as in plummeting DUIs. >> Right. Right >> Plummeting fatalities. From people driving while inebriated. Plunging into another car or sidewalk. >> Right. Right. >> So Yes. >> Amara's Law. He never gets enough credit. >> (laughs) >> I say it in every interview right. We overestimate in the short term and we underestimate in the long term the effects of these technologies cause we get involved-- The Gartner store. It's the hype cycle. >> Yeah, Yeah >> But I really I think Amara nailed it and over time, really significant changes start to take place. >> Indeed and we're seeing them now. >> Alright well Gaurav, great to get an update from you and a beautiful facility here. Thanks for having us on. >> Thank you, thank you. A pleasure to be here. Great to see you as well. >> Alright He's Gaurav, I'm Jeff. And you're watching theCUBE from SnapLogic's headquarters Thanks for watching. (techno music)

>> Announcer: It's theCUBE, covering VeeamOn 2018, brought to you by Veeam. >> Welcome back to VeeamOn 2018 everybody, you're watching theCUBE, the leader in live tech coverage. We go out to the events and extract the signal from the noise. My name is Dave Vellante, and I'm with my cohost, Stu Miniman. Mike Conjoice is here, he's a Solutions Architect at Bupa Dental. Mike, over from the pond? >> Yeah absolutely. >> Over the pond rather, to America, welcome, from Bristol, England, great to have you on theCUBE, thank you. >> Thanks very much. >> Bupa Dental. Tell us about this 90,000 person organization. >> Yeah, so, Bupa's a global organization. They're primarily known for their health care insurance. Bupa Dental is a market unit that provides dental, NHS and private. So we're one of the largest private providers in the UK. We've got around 460 practices at the moment across the UK and Ireland. Bupa itself, 90,000 staff, 8,000 of that is dental. So that's clinicians and support staff. Were acquiring new practices, about three practices a week. >> Massive scale. >> Mike: Absolutely, it's huge. >> I've got to ask you, before we get into it. So health care, in England, NHS, you mentioned NHS and private. A lot of us in the United States, you know, have I think misconceptions, but what's your take on the quality of healthcare in England and the UK? A lot of people I talk to love it, they say it's really high quality. What's your take? >> It's certainly a different way of doing things, but then, it's a good model I feel. 'cause we all pay in, everyone can get that healthcare they need, they don't have to worry about being ill. You know, being ill shouldn't bankrupt you. So we do the NHS and private side of things. It's usually a lot of the same clinicians that run those models, but private we tend to cut the line a lot quicker, things like that. You're paying for the speed of the access to the clinicians, things like that. >> Okay, so but it's a hybrid model, so if you can afford it, then you can complement it, and it allows you to accelerate things. >> Mike: Absolutely. >> Okay, so there's still that level of quality that you can pay for, >> Yes, it's tiered >> But everybody's got healthcare, a hundred percent of the citizens are covered. >> Mike: Yeah. >> Mike, what's the kind of the stresses and the changes happening in healthcare, regulation like that impact from the technology sector? >> So at the moment, GDPR is obviously the big buzzword, I'm sure it's not the first time you've heard that this week. >> It's May 2018 >> We've got a countdown going. So a lot of our data is patient data, so it's critical healthcare data. So we're very lucky in Bupa to have a large information governance team that can manage a lot of the compliance and regulatory factors for us. So we need to be very aware of what we're doing with that data. We have the GDPR compliance side of things, where you've got the right to forget in an organization, but also the healthcare side of things can overrule that, that we are obliged to keep records for you know, certain amounts of time, depending on ages and things like that. >> And what kind of solutions are you architecting? >> So we, as I said, we acquire heavily, we acquire about two to three practices a week. So we are growing, so everything we look at is scale, not where we are now, but where we're going to be. You know, we've got plans to be at a thousand practices in no time at all. So a lot of the legacy frameworks that we follow, a lot of the legacy operational models we went with, they worked, but they don't scale well. So we need to put things so automation and intelligence, like Danny's been talking about in the keynote. It's things we really need to look at. We've started leveraging our data a lot more. So we pull back a lot of this data, we've got so much data, but we weren't really doing a lot with it. We've started running a lot of business intelligence, you know MIS data across that, to kind of learn how our patients use, I mean nobody likes going to the dentist, it's not a luxury treat that people go for. So trying to make that journey easier for the patients is kind of our end goal. We want to make it as painless as possible, apart from the dental bit. From making an appointment to kind of feeding back afterwards, and keeping that loop going, it's not just a one time end to end project. >> Yeah, so that whole experience. Take us inside the pieces that your patients don't see. Paint a picture of your infrastructure, I mean, what's there, what does it look like, and ultimately what applications are you supporting, you know, the top ones. >> Yeah, so dental practice management software isn't as advanced as probably as most people would think. Each practice has got a virtualization host in each. So we've got 500 service, remote branches on an MPLS link, so they're all coming back to a central data center where we keep all our offsite backups. >> Those are 500 physical servers? >> Yes, they're running Hyper-V, so they've got... They're quite low capacity, so there might be one or two VMs on each one. So although the scale is huge, the kind of the density is quite minimal. So we're bringing all that back across MPLS links that we're still not in an amazing place with network links in the UK, so some of our practices, they're not the best links, they're slow. Bringing back a lot of that data every night can be, you know, a massive issue, especially with the legacy software we were using previously. We need an offsite copy, we can't just cope with a local copy. We've had issues where practices have failed, practices have flooded, and without an offsite copy, you know, that backup drive floating in the water (mumbles) >> How does that local copy get made? That's done in an automated way from your remote location >> Yeah, so... >> It's not some gal at the desk doing the backup >> No, no, no >> like it used to be. >> Each practice has got like a USB or a NAS, depending on the size of the practice, and so we centrally manage that through the Veeam console in our data center. So each practice has a local backup job, to that storage every night, and then a backup copy job to our offsite data center to keep two copies of the data. >> And the office is closed, right, so it's not like you're dealing with high volume transactions that you're having to capture. I mean you've got a long enough window to get the stuff offsite, is that true? >> Yeah, so our bottleneck is always network, it's never source or target, it's always network. You know, some of our links we might get 200K uploads, so, if you're transferring a few gig of data it's never good. A lot of our data is digital imaging as well, which is really taking off. So you know you used to go and get an x-ray, now it's all 3D models of a scan of your mouth. So those files are... >> A lot of data. >> Yeah, absolutely. >> Well we've done Cube gigs in the UK, so we know, sometimes those pipes are pretty small. >> Absolutely. >> Okay, so in the primary applications that you're supporting is this dental, this what you folks offer >> Yeah, so we've got, there's a couple of big players in the practice management software space, so we're kind of a split across those. They are moving towards private cloud software, but it's a slow process. These are the same softwares that you find in a single-person dental practice to these massive scales that we've got, so there's... They're very well known across the industry. So change is quite hard for them. >> So you're a Microsoft shop. Who's your server vendor? >> Dell. >> So you've got Dell servers, and Dell storage as well? >> Yes, so we've got Dell storage in the core. Just equal, equal logic. >> But Veeam is your primary data protection right? >> Yeah, absolutely. >> And how long have you had Veeam in there? >> Probably two and a half years now. >> Okay, great, so let's go back to three years ago. >> The good times. >> What was life like then, and why did you bring in Veeam, and what change, take us through that whole case. >> So, like I said, we're highly acquisitive. So that came with a certain cadence and expectation. So we basically got what was given to us when we bought the practice. There was a lot of legacy backup providers, you know, all the classic ones. All over the place, no standardization of what was set up, what was backing up, the reporting. There was no central pane of glass to manage that. So it was taking a lot of engineer time to check those backups. So the infrastructure team that look after that, they were having to dedicate possibly two engineers a day just to check backups, which was an absolute nightmare. It's expensive as well, you know, they're not cheap guys to hire, so you just, you're getting them to do manual admin work. So we needed a change obviously, especially with the expectations of growth. I'd worked with Veeam previously as an MSV, so I knew the product, I knew how it worked. I kind of put it forward, I think it would be the best idea for us to go with it. So we kind of went through a partner, to kick off the initiation, and straightaway they said this is a big project, you want to get Veeam directly involved. So we had a lot of help from Veeam, the SEs, the sales guys. Everyone we wanted, we had access to, just because of the size of it. And it was something Veeam hadn't really done before, the whole remote office, the whole remote office scheme, because of the licensing, it can work out expensive per socket. So they were quite interested in it as well. That was our primary driver was kind of centralizing all that management and the reporting, and just freeing up time, just was the main... >> So did you, was it sort of a wholesale, we're doing Veeam, we're going all in? Across 500 server platforms. >> It was a big blast of it at the start, so we had a lot of physical 2003 servers, so they needed to be replaced anyway, so that was perfect timing for that. >> Dave: How convenient. >> Yeah it was good timing. 2008 >> Sorry CFO, we got to do it. >> We were very lucky actually. Our finance team are very trusting of us. If we say this is the right solution, they kind of, well, if that's what it takes. >> They bite the bullet. >> Yeah, yeah. So we had probably about 200 in one go, well, in one go, over a period of a couple of months. >> Dave: In (mumbles) kind of >> It wasn't the slickest process, because we were learning at the time. The network bandwidth was a big issue. But now moving forward we're still replacing servers. Any kind of BAU replacements, we'll always go out with this Hyper-V Veeam model. Any new practice we bring on, Hyper-V Veeam. It's just, we've done a lot of power shell scripting on the background as well to... 'Cause if you think, we've got 500 hosts, that's a thousand jobs running. It's 500 local, 500 copy. It's a lot to keep track of, so... >> So Mike, the next acquisition, do you have to change the infrastructure, or can you drop Veeam in as a first before you rip out some of the gear? >> We do tend to rip and replace, just to kind of standardize it. So we keep a... We don't want to go to 350 practices and they're one model, and there's 10 at a different one. So we tend to rip and replace with our MPLS and the server, switching, just trying to keep it standard as possible for management. >> Hard work. I mean what was your result? >> Pretty good actually, yeah. >> What changed? How did you measure the success? Was it sort you saw it and... >> So, reporting before was done by an MSP that looked after us. Reporting was creative, shall we say. So were getting 98-100% successes of what they reported on. So they may have been backing up 20 files, that was working. >> They had their thumb on the scale. >> Absolutely. So we've got a lot more confidence in what we're backing up now, even if we, you know, get, which we never do, but even if 30% failures, I'd rather know about 30% actual failures than just be blissfully ignorant. It's saved a lot of the infrastructure team's time, you know, with the scripting and the reporting, we're pulling a lot into Power BI as well, so management can see those stats realtime. It's just, you know buzzword, it just works. >> That was an ad, it just works. So you save time, your staff save time. What happened, they got their weekends and nights back? You were able to not hire as many people, I presume you didn't fire anybody? >> Not that I know of, no. It's allowed them to concentrate on the work they should be doing, the project work, the forward thinking work. With that kind of block it was not allowing these guys to innovate and to see where to change. They were doing a lot of reactive work, whereas now they're fully proactive, they're kind of looking about, what's the next thing, how can we get ahead of the curve. >> Why Veeam, I know we've got to go, and you might want to jump in. But why Veeam relative to the other choices that you had? >> Well first of all it was my experience with Veeam. I've never had a bad experience dealing with them. Their support is absolutely flawless. Anyone I speak to, I always say, hopefully you never need them, but, their support guys are just out of this world. The help they'll give and what they'll, they'll go above and beyond, they'll help with things that aren't necessarily Veeam, just to get you up and running. >> Mike, the last question I had for you is, you've been expanding beyond just virtualization, you're using Hyper-V, it was big news when Veeam supported that. You're doing a lot with SAS these days, you're probably not too much in public cloud, but what do you see, what interests you, what might bring you beyond kind of the one product you're using today? >> So 365 is big for us, we're going to be pushing to 365 next year. So the Veeam backup for Office 365 is something we're definitely going to look at. We do leverage Azure very heavily for our development. So things like direct restore to Azure are good for us. We can spin up a practice straight in Azure if their physical area fails, things like that are a big boost to us. >> All right we got to go. Mike, are you going to the party tonight? >> Mike: Absolutely. >> Dave: You're fired up? >> Theme party, yeah. >> Right, thanks so much for coming on theCUBE. >> Thank you from me. >> Actually, sorry, one last question. >> Okay. >> If you had 'em all again, what would you do over, differently? >> Probably nothing, really. >> Oh, that was easy. All right, well, thanks again for coming on theCUBE. >> Thank you. >> Keep right there, we're going to be back with our next guest right after this short break.

>> Announcer: Live, from Stanford University in Palo Alto, California, it's theCUBE covering Women in Data Science Conference 2018, brought to you by Stanford. (light techno music) >> Welcome back to theCUBE's continuing coverage of the Women in Data Science event, WiDS 2018. We are live at Stanford University. You can hear some great buzz around us. A lot of these exciting ladies in data science are here around us. I'm pleased to be joined by my next guest, Bhavani Thuraisingham, who is one of the speakers this afternoon, as well as a distinguished professor of computer science and the executive director of Cyber Security Institute at the University of Texas at Dallas. Bhavani, thank you so much for joining us. >> Thank you very much for having me in your program. >> You have an incredible career, but before we get into that I'd love to understand your thoughts on WiDS. In it's third year alone, they're expecting to reach over 100,000 people today, both here at Stanford, as well as more than 150 regional events in over 50 countries. When you were early in your career you didn't have a mentor. What does an event like WiDS mean to you? What are some of the things that excite you about giving your time to this exciting event? >> This is such an amazing event and just in three years it has just grown and I'm just so motivated myself and it's just, words cannot express to see so many women working in data science or wanting to work in data science, and not just in U.S. and in Stanford, it's around the world. I was reading some information about WiDS and I'm finding that there are WiDS ambassadors in Africa, South America, Asia, Australia, Europe, of course U.S., Central America, all over the world. And data science is exploding so rapidly because data is everywhere, right? And so you really need to collect the data, stow the data, analyze the data, disseminate the data, and for that you need data scientists. And what I'm so encouraged is that when I started getting into this field back in 1985, and that was 32 plus years ago in the fall, I worked 50% in cyber security, what used to be called computer security, and 50% in data science, what used to be called data management at the time. And there were so few women and we did not have, as I said, women role models, and so I had to sort of work really hard, the commercial industry and then the MITRE Corporation and the U.S. Government, but slowly I started building a network and my strongest supporters have been women. And so that was sort of in the early 90's when I really got started to build this network and today I have a strong support group of women and we support each other and we also mentor so many of the junior women and so that, you know, they don't go through, have to learn the hard way like I have and so I'm very encouraged to see the enthusiasm, the motivation, both the part of the mentors as well as the mentees, so that's very encouraging but we really have to do so much more. >> We do, you're right. It's really kind of the tip of the iceberg, but I think this scale at which WiDS has grown so quickly shines a massive spotlight on there's clearly such a demand for it. I'd love to get a feel now for the female undergrads in the courses that you teach at UT Dallas. What are some of the things that you are seeing in terms of their beliefs in themselves, their interests in data science, computer science, cyber security. Tell me about that dynamic. >> Right, so I have been teaching for 13 plus years full-time now, after a career in industry and federal research lab and government and I find that we have women, but still not enough. But just over the last 13 years I'm seeing so much more women getting so involved and wanting to further their careers, coming and talking to me. When I first joined in 2004 fall, there weren't many women, but now with programs like WiDS and I also belong to another conference and actually I shared that in 2016, called WiCyS, Women in Cyber Security. So, through these programs, we've been able to recruit more women, but I would still have to say that most of the women, especially in our graduate programs are from South Asia and East Asia. We hardly find women from the U.S., right, U.S. born women pursuing careers in areas like cyber security and to some extent I would also say data science. And so we really need to do a lot more and events like WiDS and WiCys, and we've also started a Grace Lecture Series. >> Grace Hopper. >> We call it Grace Lecture at our university. Of course there's Grace Hopper, we go to Grace Hopper as well. So through these events I think that, you know women are getting more encouraged and taking leadership roles so that's very encouraging. But I still think that we are really behind, right, when you compare men and women. >> Yes and if you look at the statistics. So you have a speaking session this afternoon. Share with our audience some of the things that you're going to be sharing with the audience and some of the things that you think you'll be able to impart, in terms of wisdom, on the women here today. >> Okay, so, what I'm going to do is that, first start off with some general background, how I got here so I've already mentioned some of it to you, because it's not just going to be a U.S. event, you know, it's going to be in Forbes reports that around 100,000 people are going to watch this event from all over the world so I'm going to sort of speak to this global audience as to how I got here, to motivate these women from India, from Nigeria, from New Zealand, right? And then I'm going to talk about the work I've done. So over the last 32 years I've said about 50% of my time has been in cyber security, 50% in data science, roughly. Sometimes it's more in cyber, sometimes more in data. So my work has been integrating the two areas, okay? So my talk, first I'm going to wear my data science hat, and as a data scientist I'm developing data science techniques, which is integration of statistical reasoning, machine learning, and data management. So applying data science techniques for cyber security applications. What are these applications? Intrusion detection, insider threat detection, email spam filtering, website fingerprinting, malware analysis, so that's going to be my first part of the talk, a couple of charts. But then I'm going to wear my cyber security hat. What does that mean? These data science techniques could be hacked. That's happening now, there are some attacks that have been published where the data science, the models are being thwarted by the attackers. So you can do all the wonderful data science in the world but if your models are thwarted and they go and do something completely different, it's going to be of no use. So I'm going to wear my cyber security hat and I'm going to talk about how we are taking the attackers into consideration in designing our data science models. It's not easy, it's extremely challenging. We are getting some encouraging results but it doesn't mean that we have solved the problem. Maybe we will never solve the problem but we want to get close to it. So this area called Adversarial Machine Learning, it started probably around five years ago, in fact our team has been doing some really good work for the Army, Army research office, on Adversarial Machine Learning. And when we started, I believe it was in 2012, almost six years ago, there weren't many people doing this work, but now, there are more and more. So practically every cyber security conference has got tracks in data science machine learning. And so their point of view, I mean, their focus is not, sort of, designing machine learning techniques. That's the area of data scientists. Their focus is going to be coming up with appropriate models that are going to take the attackers into consideration. Because remember, attackers are always trying to thwart your learning process. >> Right, we were just at Fortinet Accelerate last week, theCUBE was, and cyber security and data science are such interesting and pervasive topics, right, cyber security things when Equifax happened, right, it suddenly translates to everyone, male, female, et cetera. And the same thing with data science in terms of the social impact. I'd love your thoughts on how cyber security and data science, how you can educate the next generation and maybe even reinvigorate the women that are currently in STEM fields to go look at how much more open and many more opportunities there are for women to make massive impact socially. >> There are, I would say at this time, unlimited opportunities in both areas. Now, in data science it's really exploding because every company wants to do data science because data gives them the edge. But what's the point in having raw data when you cannot analyze? That's why data science is just exploding. And in fact, most of our graduate students, especially international students, want to focus in data science. So that's one thing. Cyber security is also exploding because every technology that is being developed, anything that has a microprocessor could be hacked. So, we can do all the great data science in the world but an attacker can thwart everything, right? And so cyber security is really crucial because you have to try and stop the attacker, or at least detect what the attacker is doing. So every step that you move forward you're going to be attacked. That doesn't mean you want to give up technology. One could say, okay, let's just forget about Facebook, and Google, and Amazon, and the whole lot and let's just focus on cyber security but we cannot. I mean we have to make progress in technology. Whenever we make for progress in technology, driver-less cars or pacemakers, these technologies could be attacked. And with cyber security there is such a shortage with the U.S. Government. And so we have substantial funding from the National Science Foundation to educate U.S. citizen students in cyber security. And especially recruit more women in cyber security. So that's why we're also focusing, we are a permanent coach here for the women in cyber security event. >> What have some of the things along that front, and I love that, that you think are key to successfully recruiting U.S. females into cyber security? What do you think speaks to them? >> So, I think what speaks to them, and we have been successful in recent years, this program started in 2010 for us, so it's about eight years. The first phase we did not have women, so 2000 to 2014, because we were trying to get this education program going, giving out the scholarships, then we got our second round of funding, but our program director said, look, you guys have done a phenomenal job in having students, educating them, and placing them with U.S. Government, but you have not recruited female students. So what we did then is to get some of our senior lecturers, a superb lady called Dr. Janelle Stratch, she can really speak to these women, so we started the Grace Lecture. And so with those events, and we started the women in cyber security center as part of my cyber security institute. Through these events we were able to recruit more women. We are, women are still under-represented in our cyber security program but still, instead of zero women, I believe now we have about five women, and that's, five, by the time we will have finished a second phase we will have total graduated about 50 plus students, 52 to 55 students, out of which, I would say about eight would be female. So from zero to go to eight is a good thing, but it's not great. >> We want to keep going, keep growing that. >> We want out of 50 we should get at least 25. But at least it's a start for us. But data science we don't have as much of a problem because we have lots of international students, remember you don't need U.S. citizenship to get jobs at Facebook or, but you need U.S. citizenships to get jobs as NSA or CIA. So we get many international students and we have more women and I would say we have, I don't have the exact numbers, but in my classes I would say about 30%, maybe just under 30%, female, which is encouraging but still it's not good. >> 30% now, right, you're right, it's encouraging. What was that 13 years ago when you started? >> When I started, before data science and everything it was more men, very few women. I would say maybe about 10%. >> So even getting to 30% now is a pretty big accomplishment. >> Exactly, in data science, but we need to get our cyber security numbers up. >> So last question for you as we have about a minute left, what are some of the things that excite you about having the opportunity, to not just mentor your students, but to reach such a massive audience as you're going to be able to reach through WiDS? >> I, it's as I said, words cannot express my honor and how pleased and touched, these are the words, touched I am to be able to talk to so many women, and I want to say why, because I'm of, I'm a tamil of Sri Lanka origin and so I had to make a journey, I got married and I'm going to talk about, at 20, in 1975 and my husband was finishing, I was just finishing my undergraduate in mathematics and physics, my husband was finishing his Ph.D. at University of Cambridge, England, and so soon after marriage, at 20 I moved to England, did my master's and Ph.D., so I joined University of Bristol and then we came here in 1980, and my husband got a position at New Mexico Petroleum Recovery Center and so New Mexico Tech offered me a tenure-track position but my son was a baby and so I turned it down. Once you do that, it's sort of hard to, so I took visiting faculty positions for three years in New Mexico then in Minneapolis, then I was a senior software developer at Control Data Corporation it was one of the big companies. Then I had a lucky break in 1985. So I wanted to get back into research because I liked development but I wanted to get back into research. '85 I became, I was becoming in the fall, a U.S. citizen. Honeywell got a contract to design and develop a research contract from United States Air Force, one of the early secure database systems and Honeywell had to interview me and they had to like me, hire me. All three things came together. That was a lucky break and since then my career has been just so thankful, so grateful. >> And you've turned that lucky break by a lot of hard work into what you're doing now. We thank you so much for stopping. >> Thank you so much for having me, yes. >> And sharing your story and we're excited to hear some of the things you're going to speak about later on. So have a wonderful rest of the conference. >> Thank you very much. >> We wanted to thank you for watching theCUBE. Again, we are live at Stanford University at the third annual Women in Data Science Conference, #WiDs2018, I am Lisa Martin. After this short break I'll be back with my next guest. Stick around. (light techno music)

>> Hey, welcome back everybody. Jeff Rick here with the Cube. We are live in downtown San Jose at the historic Pagoda Lounge, part of Big Data SV, which is part of Strata + Hadoop Conference, which is part of Big Data Week because everything big data is pretty much in San Jose this week. So we're excited to be here. We're here with George Gilbert, our big data analyst from Wikibon, and a great guest, Gaurav Dhillon, Chairman and CEO of SnapLogic. Gaurav, great to see you. >> Pleasure to be here, Jeff. Thank you for having me. George, good to see you. >> You guys have been very busy since we last saw you about a year ago. >> We have. We had a pretty epic year. >> Yeah, give us an update, funding, and customers, and you guys have a little momentum. >> It's a good thing. It's a good thing, you know. A friend and a real mentor to us, Dan Wormenhoven, the Founder and CEO of NetApp for a very long time, longtime CEO of NetApp, he always likes to joke that growth cures all startup problems. And you know what, that's the truth. >> Jeff: Yes. >> So we had a scorching year, you know. 2016 was a year of continuing to strengthen our products, getting a bunch more customers. We got about 300 new customers. >> Jeff: 300 new customers? >> Yes, and as you know, we don't sell to small business. We sell to the enterprise. >> Right, right. >> So, this is the who's who of pharmaceuticals, continued strength in high-tech, continued strength in retail. You know, all the way from Subway Sandwich to folks like AstraZeneca and Amgen and Bristol-Myers Squibb. >> Right. >> So, some phenomenal growth for the company. But, you know, we look at it very simply. We want to double our company every year. We want to do it in a responsible way. In other words, we are growing our business in such a way that we can sail over to cash flow break-even at anytime. So responsibly doubling your business is a wonderful thing. >> So when you look at it, obviously, you guys are executing, you've got good products, people are buying. But what are some of the macro-trends that you're seeing talking to all these customers that are really helping push you guys along? >> Right, right. So what we see is, and it used to be the majority of our business. It's now getting to be 50/50. But still I would say, historically, the primary driver for 2016 of our business was a digital transformation at a boardroom level causing a rethinking of the appscape and people bringing in cloud applications like Workday. So, one of the big drivers of our growth is helping fit Workday into the new fabric in many enterprises: Vassar College, into Capital One, into finance and various other sectors. Where people bring in Workday, they want to make that work with what they have and what they're going to buy in the future, whether it's more applications or new types of data strategies. And that is the primary driver for growth. In the past, it was probably a secondary driver, this new world of data warehousing. We like to think of it as a post-modern era in the use of data and the use of analytics. But this year, it's trending to be probably 50/50 between apps and data. And that is a shift towards people deploying in the same way that they moved from on-premise apps to SAS apps, a move towards looking at data platforms in the cloud for all the benefits of racking and stacking and having the capability rather than being in the air-conditioning, HVAC, and power consumption business. And that has been phenomenal. We've seen great growth with some of the work from Microsoft Azure with the Insights products, AWS's Redshift is a fantastic growth area for us. And these sorts of technologies, we think are going to be of significant impact to the everyday, the work clothing types of analytics. Maybe the more exotic stuff will stay on prem, but a lot of the regular business-like stuff, you know, stuff in suits and ties is moving into the cloud at a rapid pace. >> And we just came off the Google Next show last week. And Google really is helping continue to push kind of ML and AI out front. And so, maybe it's not the blue suit analytics. >> Gaurav: Indeed, yes. >> But it does drive expectations. And you know, the expectations of what we can get, what we should get, what we should be moving towards is rapidly changing. >> Rapidly changing, for example, we saw at The New York Times, which as many of Google's flagship enterprise customers are media-related. >> Jeff: Right. >> No accident, they're so proficient themselves being in the consumer internet space. So as we encountered in places like The New York Times, is there's a shift away from a legacy data warehouse, which people like me and others in the last century, back in my time in Informatica, might have sold them towards a cloud-first strategy of using, in their case, Google products, Bigtable, et cetera. And also, they're doing that because they aspirationally want to get at consumer prices without having to have a campus and the expense of Google's big brain. They want to benefit from some of those things like TensorFlow, et cetera, through the machine learning and other developer capabilities that are now coming along with that in the cloud. And by the way, Microsoft has amazing machine learning capability in its Azure for Microsoft Research as well. >> So Gaurav, it's interesting to hear sort of the two drivers. We know PeopleSoft took off starting with HR first and then would add on financials and stumble a little bit with manufacturing. So, when someone wants to bring in Workday, is it purely an efficiency value prop? And then, how are you helping them tie into the existing fabric of applications? >> Look, I think you have to ask Dave or Aneel or ask them together more about that dynamic. What I know, as a friend of the firm and as somebody we collaborate with, and, you know, this is an interesting statistic, 20 percent of Workday's financial customers are using SnapLogic, 20 percent. Now, it's a nascent business for them and you and I were around in the last century of ERP. We saw the evolution of functional winners. Some made it into suites and some didn't. Siebel never did. PeopleSoft at least made a significant impact on a variety of other things. Yes, there was Bonn and other things that prevented their domination of manufacturing and, of course, the small company in Walldorf did a very good job on it too. But that said, what we find is it's very typical, in a sense, how people using TIBCO and Informatica in the last century are looking at SnapLogic. And it's no accident because we saw Workdays go to market motion, and in a sense, are following, trying to do the same thing Dave and Aneel have done, but we're trying to do the same thing, being a bunch of ex-Informatica guys. So here's what it is. When you look at your legacy installation, and you want to modernize it, what are your choices? You can do a big old upgrade because it's on-premise software. Or you can say, "You know what? "For 20% more, I could just get the new thing." And guess what? A lot of people want to get the new thing. And that's what you're going to see all the time. And that's what's happening with companies like SnapLogic and Workday is, you know, someone. Right here locally, Adobe, it's an icon in technology and certainly in San Jose that logo is very big. A few years ago, they decided to make the jump from legacy middleware, TIBCO, Informatica, WebMethods, and they've replaced everything globally with SnapLogic. So in that same way, instead of trying to upgrade this version and that version and what about what we do in Japan, what do we do in Sweden, why don't you just find a platform as a service that lets you elevate your success and go towards a better product, more of a self-service better UX, millennial-friendly type of product? So that's what's happening out there. >> But even that three-letter company from Walldorf was on-stage last week. You can now get SAP on the Google Cloud Platform which I thought was pretty amazing. And the other piece I just love but there's still a few doubters out there on the SAS platform is now there's a really visual representation. >> Gaurav: There is. >> Of the dominance of that style going up in downtown San Francisco. It's 60 stories high, and it's taken over the landscape. So if there's ever any a doubt of enterprise adaptation of SAS, and if anything, I would wonder if kind of the proliferation of apps now within the SAS environment inside the enterprise starts to become a problem in and of its own self. Because now you have so many different apps that you're working on and working. God help if the internet goes down, right? >> It's true, and you know, and how do you make e pluribus unim, out of many one, right? So it's hilarious. It is almost at proliferation at this point. You know, our CFO tapped me the other day. He said, "Hey, you've got to check this out." "They're using a SAS application which they got "from a law firm to track stock options "inside the company." I'm like, "Wow, that is a job title and a vertical." So only high growth private venture backed companies need this, and typically it's high tech. And you have very capable SAS, even in the small grid squares in the enterprise. >> Jeff: Right, right. >> So, a sign, and I think that's probably another way to think about the work that we do at SnapLogic and others. >> Jeff: Right, right. >> Other people in the marketplace like us. What we do essentially is we give you the ERP of one. Because if you could choose things that make sense for you and they could work together in a very good way to give you very good fabric for your purposes, you've essentially bought a bespoke suit at rack prices. Right? Without that nine times multiplier of the last century of having to have just consultants without end, darkened the sky with consultants to make that happen. You know? So that, yes, SAS proliferation is happening. That is the opportunity, also the problem. For us, it's an opportunity where that glass is half-full we come in with SnapLogic and knit it together for you to give you fabric back. And people love that because the businesses can buy what they want, and the enterprise gets a comprehensive solution. >> Jeff: Right, right. >> Well, at the risk of taking a very short tangent, that comment about darkening the skies, if I recall, was the battle of the Persians threatening the 300 Greeks at the battle of Thermopylae. >> Gaurav: Yes. >> And they said, "We'll darken the skies with our arrows." And so the Greek. >> Gaurav: Come and get 'em. >> No, no. >> The famous line was, he said, "Give us your weapons." And the guy says, "Come and get 'em." (laughs) >> We got to that point, the Greek general says, "Well, we'll fight in the shade." (all laughing) But I wanted to ask you. >> This is the movie 300 as well, right? >> Yes. >> The famous line is, "Give us your weapons." He said, "Come and get 'em." (all laughing) >> But I'm thinking also of the use case where a customer brings in Workday and you help essentially instrument it so it can be a good citizen. So what does that make, or connect it so it can be a good citizen. How much easier does that mean or does that make fitting in other SAS apps or any other app into the fabric, application fabric? >> Right, right. Look, George. As you and I know, we both had some wonderful runs in the last century, and here we are doing version 2.0 in many ways, again, very similar to the Workday management. The enterprise is hip to the fact that there is a Switzerland nature to making things work together. So they want amazing products like Workday. They want amazing products like the SAP Cloud Suite, now with Concur, SuccessFactors in there. Some very cool things happening in the analytics world which you'll see at Sapphire and so on. So some very, very capable products coming from, I mean, Oracle's bought 80 SAS companies or 87 SAS companies. And so, what you're seeing is the enterprise understands that there's going to be red versus blue and a couple other stripes and colors and that they want their businesspeople to buy whatever works for them. But they want to make them work together. All right? So there is a natural sort of geographic or structural nature to this business where there is a need for Switzerland and there is a need for amazing technology, some of which can only come from large companies with big balance sheets and vertical understanding and a legacy of success. But if a customer like an AstraZeneca where you have a CIO like Dave Smoley who transformed Flextronics, is now doing the same thing at AstraZeneca bringing cloud apps, is able to use companies like SnapLogic and then deploy Workday appropriately, SAP appropriately, have his own custom development, some domestic, some overseas, all over the world, then you've got the ability again to get something very custom, and you can do that at a fraction of the cost of overconsulting or darkening the skies in the way that things were done in the last century. >> So, then tell us about maybe the convergence of the new age data warehousing, the data science pipeline, and then this bespoke collection of applications, not bespoke the way Oracle tried it 20 years ago where you had to upgrade every app tied into every other app on prem, but perhaps the integration, more from many to one because they're in the cloud. There's only one version of each. How do you tie those two worlds together? >> You know, it's like that old bromide, "Know when to hold 'em. "Know when to fold them." There is a tendency when programming becomes more approachable, you have more millennials who are able to pick up technology in a way. I mean, it's astounding what my children can do. So what you want to do is as a enterprise, you want to very carefully build those things that you want to build, make sure you don't overbuild. Or, say, if you have a development capability, then every problem looks like a development nail and you have a hammer called development. "Let's hire more Java programmers." That's not the answer. Conversely, you don't want to lose sight of the fact that to really be successful in this millennium, you have to have a core competence around technology. So you want to carefully assemble and build your capability. Now, nobody should ever outsource management. That's a bad idea. (chuckles) But what you want to do is you want to think about those things that you want to buy as a package. Is that a core competence? So, there are excellent products for finance, for human capital management, for travel expense management. Coupa just announced today their for managing your spend. Some of the work at Ariba, now the Ariba Cloud at SAP, are excellent products to help you do certain job titles really well. So you really shouldn't be building those things. But what you should be doing is doing the right element of build and buy. So now, what does that mean for the world of analytics? In my view, people building data platforms or using a lot of open source and a lot of DevOps labor and virtualization engineering and all that stuff may be less valuable over time because where the puck is going is where a lot of people should skate to is there is a nature of developing certain machine language and certain kind of AI capabilities that I think are going to be transformational for almost every industry. It is hard to imagine anything in a more mechanized back office, moving paper, manufacturing, that cannot go through a quantum of improvement through AI. There are obviously moral and certain humanity dystopia issues around that to be dealt with. But what people should be doing is I think building out the AI capabilities because those are very custom to that business. Those have to do with the business's core competence, its milieu of markets and competitors. But there should be, in a sense, stroking a purchase order in the direction of a SAS provider, a cloud data provider like Microsoft Azure or Redshift, and shrinking down their lift-and-shift bill and their data center bill by doing that. >> It's fascinating how long it took enterprises to figure out that. Just like they've been leveraging ADP for God knows how many years, you know, there's a lot of other SAS applications you can use to do your non-differentiated heavy lifting, but they're clearly all in now. So Gaurav, we're running low on time. I just want to say, when we get you here next year, what's top of your plate? What's top of priorities for 2017? Cause obviously you guys are knocking down things left and right. >> Thank you, Jeff. Look, priority for us is growth. We're a growth company. We grow responsibly. We've seen a return to quality on the part of investors, on the part of public and private investors. And you know, you'll see us continue to sort of go at that growth opportunity in a manner consistent with our core values of building product with incredible success. 99% of our customers are new to our products last quarter. >> Jeff: Ninety-nine percent? >> Yes sir. >> That says it all. >> And in the world of enterprise software where there's a lot of snake oil, I'm proud to say that we are building new product with old-fashioned values, and that's what you see from us. >> Well 99% customer retention, you can't beat that. >> Gaurav: Hard to beat! There's no way but down from there, right? (laughing) >> Exactly. Alright Gaurav, well, thanks. >> Pleasure. >> For taking a few minutes out of your busy day. >> Thank you, Jeff. >> And I really appreciate the time. >> Thank you, Jeff, thank you, George. >> Alright, he's George Gilbert. I'm Jeff Rick. You're watching the Cube from the historic Pagoda Lounge in downtown San Jose. Thanks for watching.

this one minute I'm here with my co-host Jeff Frick who we just fresh off of the AWS summit the Amazon event Jeff and I covered that and we're here at knowledge 13 now this conference is all about the notion of going from IT as a service organization changing high teas mantra from no to now that really is the theme of this conference and we're here with Frank's luton who's the president and CEO of service now Frank welcome back to the cube thanks good to be here that's good to see you again we had you on that vm world is great story when we first introduced service now to our community you just fresh off the keynote fantastic keynote by the way thank you you had strong themes i mentioned the from no to now you talked about itu gave a little little tongue-in-cheek joke about the line outside the the rmv the Registry of Motor Vehicles and that's sort of the the idea is you guys are transforming IT from an organization that is trying to manage demand push off demand saying no we'll get it in six months it'll cost you five million dollars to one that really is redesigning IT processes around the globe so first of all welcome back congratulations how do you feel after that keynote I have to work a lot of energy in that room and it was electrifying it was awesome well one of the one of the guys in the panel stopped when you had asking the question I think was the guy from NY yes he said even stop you looked at the audience said i love this crowd that was a great crowd we gave a little goop out to the audience so talk about from know to now how'd you come up with that theme and you know give us a little color behind you know it's it's actually not easy for for us to communicate about service now desk to to lay people in sight unless you have lived in sight I t you just most people don't even know what I t really does on the day-to-day basis right so we've lived a fairly insular existence because you know everybody knows what sales people do and to some degree about HR doesn't finance people but I t it's a bit of a you know a bit of a mystery to what most folks do right but most people do know however is that the service experience with IT has been and challenging what's all we say I mean it's been you know sort of a service experience where if you have to ask the answer was going to be no right because IT organizations have been super preoccupied with infrastructure rapid change in the infrastructure for the last 30 40 years nothing ever set still long enough for us to really master the architecture and the platforms are really stabilizing mature our systems and they have to keep moving so you get pretty cranky it's back to your organization having to live that kind of life so their their their reputation for service has not been stellar and I love making the joke during the keynote their ranking right down there with legal in the basement you know of the corporate enterprise you know so well so talk a little bit about sort of how you guys you know go into an organism's you start with the IT organization right in helping them sort of automated processes connect all these different processes but you've been through your platform expanding out to other parts of the organization the irony is that I T which is the most technology savvy organization in the price as the least management sophistication in terms of managing their own activity which you know I duck to the CIO of a very large consumer gets company he said where does she make her son it's inexcusable right here here we are running milk that going in dollar budgets and staffs with tens of thousands of people and we're running it on spreadsheets email excel project management tools this is ridiculous right we don't have real information in near real time and show that we can drive our business as opposed to being driven by it right i key executives have a tendency to run from one crisis to another with their hair on fire and that's sort of the mental model and a note of now message is about out of a get these people out of this you know reactive crisis mode to where they become full-blown business partners and they start you know bring your guide to enterprise and in a very transformative way or they become the people that bring innovation to the enterprise you know here's so much Frank about shadow I teach my colleague Jeff Frick and I were at the AWS some of the few weeks and you see a lot of these cloud companies you mentioned your keynote Salesforce the salespeople workday talk to HR people they sort n run IT certainly amazon is the poster child for shadow IT but you know Jeff we have that sort of notion where IT people are not the center of the new cloud universe but that's different for service now yes it's very different but the other thing brought up amazon your keynote and how they've kind of fine what kind of a user expectation experiences with an application on the web a level of service a level of delivery and then you've got AWS its kind of the girl child of shadow IT but you guys are coming in really as the enabler to let the internal IT guys actually have the tools to compete with with guys trying to go around it really exact with delivery platform I mean we're trying to turn the tables here right because the entire history of IT is one big end around righty the many computer was an end-around of the glasshouse client-server was really pcs you know dribbling into departmental environments suffer as a service was an incredible end around people in there didn't realize it was seeping into the enterprise right now things like 80 lbs now infrastructure right is actually finding its way so we're saying look you know worthy Enterprise IT cloud company right we are going to empower and enable IT to be driving rather than just being driven and being taken over and run over by by events because that's what's been happening here's the goodness IT can start withdrawing and getting out of the business of infrastructure which is what they've been doing forever infrastructure is very challenging pretty soon that's going to be somebody else's problem right infrastructure goes behind the cooking all you have to do is in network connection so that means that the role of IT is moving from you know keeping the lights on to you know we're going to be the people who are experts at defining structuring and automating service relationships and so does relationship management I mean at this and I make a joke about you know your hole in the inbox of email you know it's full of basically service relationships that are unstructured and unlimited and undefined right right and there is this incredible opportunity to go aptet with record-keeping workflow systems and that's what we want to enable and empower IT to do right we had to give you a quick example actually very interesting we talked to our one of our very large retail customers and the supply chain office unbeknownst to us went to IT and said hey we want to build this app what should we use and Ikey said no you should try and do that on service now what's the app a supply chain office in a retail environment what they do is they take requests all day long stores distribution centers suppliers and they're rebalancing you know product right place right time right right product and they were doing that everybody running spreadsheets and emails and people constantly calling what's the update on my request and they decide no we're going to go to a record-keeping workflow system and from the moment you know they started using that system all of a sudden they had full visibility to a what the volume was of issues that was coming in but the nature of the volume was how well they were doing on their SOS relative to their storage and distribution centers and they were able to structurally go after you know the things that were a constant them grief because they just didn't know right so very simply in very short period of time you know they transformed themselves from the supply chain all those Devils running around like a chicken with his head cut off the people that were actually driving to supply chain now now supply chain management in the retail organization it's super mission-critical right because their results are directly impacted by having right product right time right place simple example where we moving from email and Excel to a record-keeping workflow system any impact with literally within 30 40 days is enormous yeah you hear that a lot of people just using Excel using email we talked to we talking some customers last night we talked to some perspective customers that were in so to check it out and they were big Lotus no shop and is describing sort of the difficulties and challenges of it you will sign them up I can almost see it but the other thing so so this notion of your customer base is very powerful in fact I tweeted out I said the service now has a sick logo basis and we said is that a typo said no sick like that sick touchdown catch it isn't good yeah sick is it good but I mean which I we hear from land o lakes Red Hat metropcs KPM nor Brent I mean just on and on and on at Facebook Intel google or customers what are some other favorite customer stories you hear a lot of the same themes Frank you know we used to use spreadsheets with using email or reliant on all these disparate processes bringing them all together getting some some other you know favorite stories of yours for customers I I relayed a bunch of him on stage this morning right beasties it's just extraordinary to me the the corporate America I mean you mentioned some of them but you know the people we had on stage you know AIG you know coca-cola company's general electric demand this is United States Army right and they owe is yeah New York Stock Exchange eli lilly big pharmaceuticals bristol-myers squibb they all have the same set of issues they have a completely fractured fragmented sprawled acti environment right and here's the interesting history we have not had CIOs that long you know I T used to report into a division next sag or a regional exact and there really wasn't one person that was responsible for running IT throughout the global enterprise because it was just a decentralized function by the way example when you in Europe yeah I ray mighty and I certainly wasn't IT guy stuff and by the way it wasn't my priority either you know it was just by the way that's for some of the history you know comes from so CIO comes in and they are now charged with you're going to run this thing they're not running anything they're being run by it right so until you get to global IT processes I mean City another you know big name they set to as rogue global bank that we don't have global IT right it is the inefficiency and the lack of ability to drive and manage is unacceptable for these very sophisticated large institutions it's embarrassing really you know yeah I mean you really can't go global as a come you can't scale your business not having all these surprises so to me it's about global scaling and it's about the business value of both having ITB accountable but also have the metrics and the visibility to be able to demonstrate the value to the organization you see i SAT with our executive sponsor from bristol-myers squibb last night and she said i got data and i got it in real time and i know it's good so I'm not putting my service providers on their heels you know before they were you know everything was you know in the realm of you know interpretation and fuzzy fuzzy right and now it's like I have data and I'm driving and I'm changing behavior right so the empowering effective it has mighty organizations it's just stomach right I thought that empowering note that came up in your keynote was interesting how the IT organizations themselves and their presentation now to their internal customers are looking more like a company you know they're they're being cute there yeah I'm taking branding they're there they're not just button pushers in and as you said you know infrastructure operators they are trying to be contributors to the business and keeping some this automobile shade of nail them to it's even stronger than now yes they want to be contributors to the business but they want to be the playmakers they wanted me to go to guys give me the ball you know that that's where we want to you know take itt there that people that really understand how to change how work gets done the enterprise I thought you characterize the dwelling experience in IT people have been running from crisis to crisis and they need to be more proactive so talk about how your system allows them to be more proactive well it's all about going from a message oriented environment to a system or an a message or environment is the one way l know it's email it's text you know it's voice right that doesn't work because you know we're just talking right systems have the ability to drive behavior because you know every time you send an email you should think to yourself could i create a service request instead right because a service request has a defined data ship it goes into a database it gets assigned you know in a workflow operation it has metrics around it if it doesn't get responded to a certain amount of time it gets accelerated to the escalator to the next level or management right so the process is defined structure to automate it is going to run its course right whether you know people are participating in it or not with this great example one of our customers equinix delilah or Brian Lily's here actually is a CIO and he said they will sell funny you know we have a system that all my life cycle application where our developers check-in fixes and enhancement to a particular software release for an application and he says because they know to work flows is completely structured an automated everybody knows that they don't get their fixes enhancement in by a certain time poof the dashboards pop the higher-ups see you know who's behind and who's not and that the threat alone of the transparency and visibility that the process introduces causes everybody there run harder right so people won't have to run around with the whip like where are you you know the process is driving is like a hamster on a treadmill you know so Freki used amazon as an example of the user experience that you know you covet as a CEO of this company and you believe you're your customer base desires at the back end also when you talk about companies like Amazon and Facebook and Google they are super highly automated you also talked about lights out automation yeah now normally IT organizations are managed now they're managed by humans they're not highly automated are you are you seeing your customers able to get to that sort of vision that you're talking about that lights-out automation almost like the hyperscale guys you know it's a super important custody I said during the cleanup or were overstaffed and under automated NIT we have reams of people on staff any large financial institutions have tens of thousands of people on staff they're bigger than any technology company right why is that it's because things are very laborious laborious and manual right the processes that they run require so many touch points I mean one of the things that we always tell our customers when you can reimplement these processes do not take your legacy forward because your legacy is very manual you remember the inbox in the outbox when we have physical in boxes and other boxes and now we know we have our laptop why do we have an inbox and outbox right does this message really this cross why are you even involved in this process right so we have to invert the process it's not like wouldn't it be nice for you to be involved in this process there'd better be a very good reason for you to touch this process because the moment you touch it you know we're going from the speed of light to you know the speed of the dirt road that Franco so service now is really in a rocket ship right now and you've demonstrated you've got a track record of being able to be sometimes call jump three myself throwing gasoline on the fire you look very good at that you got 1,600 customers you're growing like crazy but you're under penetrated in your target which is the global 2000 you're only fourteen percent penetrated in the global 2000 so get a long way to go in this journey we're very excited to be you know covering this event really appreciate you guys having us here Frank's loot Minh will give you the last word and then we'll wrap you know this is actually one of the great things that we are so on the front hood and they're penetrated because our investors are like wow you've got a lot of runway you know considering the size company that we we already are and you know the rate of monetization of our business is is extraordinarily I in other words the share of wallet that service now represents and the enterprise is so much larger than people had ever considered or thought because it was not an existing category that was fully metastasized and visible it's new it's emergent it is really transforming how people you know look at technology and process automation and so on now we're gonna be here all week covering knowledge we've got it we're going to double-click on so how is it that service now is able to deliver this cloud functionality the secret is in the single system of record the CMDB and that is not a trivial thing to do we didn't talk about that with Frankie could talk about it but we don't want to steal you know the name of thunder yeah fred muddies going to be on RNA Justin who's the CTO we're going to go deep into sort of how service now actually accomplishes this architecture Lee what their vision is so Frank thanks very much for spending so much time I know you're busy you got to run but appreciate you coming on terrific thanks for having me alright thanks for watching everybody keep it right there we'll be right back with more we're live from Las Vegas ServiceNow knowledge we'll be right back this is the Q cute baby rock and roll

>>we're back. >>This is Dave Volante. I'm with Wiki bond dot Oregon. This is Silicon angle's the cube where we extract the signal from the noise. We go into the events, we're bringing you the best guests that we can find. And we're here at the AWS summit. Amazon is taking the cloud world by storm. He was on, invented the cloud in 2006. They've popularized it very popular of course with developers. Everybody knows that story. Uh, Amazon appealing to the web startups, but what's most impressive is the degree to which Amazon is beginning to enter the enterprise markets. I'm here with my cohost Jeff Frick and Jeff, we heard Andy Jassy this morning just laying out the sort of marketing messaging and progress and strategies of AWS. One of the things that was most impressive was the pace at which they put forth innovations. We talked about that earlier, but also the pace at which they proactively reduce prices. Uh, that's different than what you'd see in the normal sort of enterprise space. Talk about that a little bit. >>Yeah. Again, I think it really speaks to their strategy to lock up the customer. It's really a lifetime value of the customer and making sure that they don't have a really an opportunity or a reason to go anywhere else. So as we discussed a little bit earlier, they leverage, you know, kind of the pure hardware economics of, of decreasing a computing power, decreasing storage, decreasing bandwidth, but then they also get all the benefits of scale. And I think what's in one of the interesting things that Andy talked about and kind of his six key messages was that it's actually cheaper to rent from them because of the scale than it is to buy yourself. And I know that's a pretty common knock between kind of a build or buy, um, kind of process you go through and usually you would think renting at some scale becomes less economical than if you just did it yourself. But because their scale is so massive because of the flexibility that you can bring, uh, computing resources to bear based on what you're trying to accomplish really kind of breaks down the, uh, the old age old thought that, you know, at scale we need to do it ourselves. >>Well, and that's the premise. Um, I think, and, uh, let's Brits break down a little bit about that, that analysis and, and Andy's keynote. So he put forth some data from IDC which showed that, uh, the Amazon cloud is cheaper than the, uh, a, a so-called private cloud or an in house on premise installation. You know, I certainly, there's, it's, it's a, it's an, it's depends, right? It really depends on the workload. That's somewhat of an apples to orange is going on here and the types of workloads that are going down in the AWS cloud, granted he's right and that they're running Oracle, they're running SAP, but the real mission critical workloads, what he calls mission critical aren't the same as what, you know, Citi would call mission critical. Right? So to replicate that level of mission criticality, uh, would probably almost most certainly be more expensive rental versus owning the real Achilles heel of, of, of any cloud, not just Amazon. >>Cloud really is getting data out. Um, moving data, right? Amazon's going to charge you not to get data in. They're gonna charge you to store it there to exercise, you know, compute. Uh, and then, but they're also gonna charge it if you wanted to take it out. That's expensive. The bandwidth costs and the extrication costs are expensive. Uh, the other issue with cloud again is data movement. It takes a long time to move a terabyte, let alone multiple terabytes. So those are sort of the two sort of Achilles heels of, of cloud. But that's not specific to Amazon's cloud. That's any cloud. Yeah. So we've got a great lineup today. Um, let's see. We've got Ariel Kelman coming on, uh, and I believe he's in the house. So we're going to take a quick break. Quick break. Right now we right back with Ariel Kelman, who's the head of marketing at AWS. Keep right there. This is the cube right back. >>we lift out all the programs out there and identified a gap in tech news coverage. Those shows are just the tip of the iceberg and we're here for the deep dive, the market beg for our program to fill that void. We're not just touting off headlines. We also want to analyze the big picture and ask the questions that no one else is asking. We work with analysts who know the industry from the inside out. So what do you think was the source of this missing? So you mentioned briefly there are, that's the case then why does the world need another song? We're creating a fundamental change in news coverage, laying the foundation and setting the standard, and this is just the beginning. We looked on all the programs out there and identified a gap in tech news coverage. There are plenty of tech shows that provide new gadgets and talk about the latest in gaming, but those shows aren't just the tip of the iceberg. And we're here for the deep dive. >>Okay, >>Dave Olanta. I'm with Wiki bond.org and this is Silicon angle's the cube where we extract signal from the noise. We bring you the best guest that we can find. We go into events like ESPN goes into sporting events, we go into tech events, we find the tech athletes and bring to you their knowledge and share with you our community. We're here at Moscone in San Francisco at the AWS summit. We're here with Arielle Kellman who's the head of worldwide marketing for AWS. Arielle, welcome to the cube. Thanks for having me, Dave. Yeah, our pleasure. I really appreciate you guys having us here. Great venue. Uh, let's see. What's the numbers? It looks like you know, many, many thousands, well over 5,000 people here by four or 5,000 people here. We're doing a about a dozen of these around the world, one to 4,000 people to help educate our customers about all the new things we're doing, all the new partners that are available to help them thrive in the AWS cloud. >>It's mind boggling the amount of stuff that you guys are doing. We just heard NG Jesse's keynote, for those of you who saw Andy's keynote at reinvent, a lot of similar themes with some, some new stuff in there, but one of the most impressive, he said, he said, other than security, one of the things that we're most proud of is the pace at which we introduce new services. And he talked about this fly wheel effect. Can you talk about that a little bit? Sure. Well, there's kind of two different things going on. The pace of innovation is we're really trying to be nimble and customer centric and ultimately we're trying to give our customers a complete set of services to run virtually any workload in the cloud. So you see us expanding a broader would additional services. And then as we get feedback we add more and more features. >>Yeah. So we're obviously seeing a big enterprise push. Uh, Andy was, was very, I thought, politically correct. He said, look, there's one model which is to keep charging people as much as you possibly can. And then there's our model, which is we proactively cut prices and we passed that on to customers. Um, and, and he also stressed that that's not something that's not a gimmick. It's not a sort of a onetime thing. Can you talk about that in terms of your philosophy and your DNA? It's just our philosophy. It's actually a lot less dramatic than is often portrayed in the press. Just the way we look at things as we're constantly trying to drive efficiencies out of our operations. And as we lower our cost structure, we have a choice. We can either pocket those savings as extra margin or we can pass those savings along to our customers in the form of lower prices. >>And we feel that the ladder is the approach that customers like and we want to make our customers happy. So this event, uh, we were talking off camera, you said you've been doing these now for about two years. You do re-invent once a year. That's your big conference out in Vegas and it's a very, very large event, very well attended. And you do these regionally and in and around the world, right. Talk about that a little bit. We do about a dozen of these a year. Um, we did, uh, New York a couple of weeks ago, London, Australia and Sydney. I'm going to go to India and Tokyo, really about a dozen cities in the world and it's a little tactic. I'm not going to beat all of them, but you know, the focus is to really, uh, deliver educational content. Uh, we'll do about maybe 12 to 16 technical breakout sessions all for free, uh, for, for customers and people who want to learn about AWS for the first time. >>And the, and the audience here is largely practitioners and partners, right? Can it talk about the makeup a little bit? Sure. It's a pretty diverse set of people. Um, we have a technical executives like CEOs and architects and we have lots of developers and then lots of people from our, our partner ecosystem of integrators wanting to, um, you know, brush up on the latest technologies and skills and a lot of people who just want to learn about the cloud and learn about AWS. I think there are a lot of misconceptions about AWS and I'd like to just tackle some of those with you if I may. So let me just sort of, let's list them off and you can respond. Yeah, we'll let our audience to sort of decide. So the first is that AWS has only tested dev workloads. Can you talk about that a little bit? >>Sure. Um, well test and dev local workloads are very popular. We saw, we covered that in the keynote. Um, and it's often a place where it organizations will start out with AWS, but it is by no means the most popular or most dominant workload. We have a lot of people migrating, uh, enterprise apps to the cloud. Um, if you look at, uh, in New York, uh, in our summit we talked about Bristol Myers Squibb, uh, running all of their, um, clinical trial simulations and reducing the amount of time it takes to run a simulation by 98%. Uh, if people are running Oracle, SharePoint, SAP, pretty much any workload in the cloud. And then another popular use is building brand new applications, uh, for the cloud. You can miss, some people call them cloud native applications. A good example is the Washington post who built an app called the social reader that delivers their content to Facebook and now as more people viewing their content, their than with their print magazines and they just couldn't have done that, uh, on premises. >>So, uh, the other one I want to talk about, we're going to do some serious double clicking on security so we don't have to go crazy on it, but, but there's a sort of common perception that the cloud is not secure. What do you guys say about that? Yeah, so, um, really our number one priority is security. You're looking at a security, operational performance, uh, and then our pace of innovation. But with security, um, what we want to do is to give enterprises everything they need to understand how our security works and to evaluate it and how it meets with their requirements for their projects. So it really all starts with our, our physical security, um, our network security, the access of our people. They're all the similar types of technologies that our customers are familiar with. And then they also tend to look at all the certifications and accreditations, SAS 70 type two SOC one SIS trust. >>I ATAR for our government customers. And then I think it was something a lot of people don't understand is how much work we've put into the security features. It's not just is the cloud secure, but can I interact and integrate, uh, your security functionality with all of my existing systems so we can integrate with people's identity and access systems. You could have a private dedicated connection from your enterprise to AWS with direct connect to, I really encourage anyone who has interest in digging into our security features to go to the security center and our website. It's got tons of information. So I'm putting on the spot. Um, what percent of data centers in the world have security that are, that is as good or better than AWS. It'd be an interesting thing for us to do a survey on. But if you think about security at the infrastructure layer down is what we take care of. >>Now when you build your application, you can build a secure app or non-secure app. So the customer has some responsibility there. But in terms of that cloud infrastructure, um, for a vast majority of our customers, they're getting a pretty substantial upgrade in their security. And here's something to think about is that, um, we run a multitenant service, so we have lots and lots of customers sharing that infrastructure and we get feedback from some of the most security conscious companies in the world and government agencies. So when our customers are giving us a enhancement request, and let's say it is, uh, an oil company like shell or financial services company like NASDAQ, and we implement that improvement because there's always new requirements. We implement that all of our hundreds of thousands of customers get those improvements. So it's very hard for a lot of companies to match that internally, to stay up to speed with all the latest, um, requirements that people need. >>Yeah. Okay. So, uh, and you touched on this as well as the compliance piece of it, but when you think of things like, like HIPAA compliance for example, I think a lot of people don't realize that you guys are a lead in that regard. Can you talk about that a little bit more? Yeah. So, uh, we have a lot of customers running HIPAA compliant, uh, workloads. Um, there's, there's one company or the, the Schumacher group, which does emergency room staffing out of Lafayette, Louisiana. And we, companies like that are going through the process. They have to follow their internal compliance guidelines for implementing a HIPAA compliant plan app. It's actually, it's more about how you implement and manage the application than the infrastructure, which is part of it. But we, we satisfy that for our customers. Let's talk a little bit about SLA. That didn't come up at least today in Andy's keynote, but it didn't reinvent and he made a statement at reinvent. >>He said, we've never lost a piece of business because of SLS. And that caught my attention and I said, okay, interesting. Um, talk about, uh, the criticisms of the SLA. So a lot of people say, wow, SLA, not just of Amazon's cloud, but any public cloud. I mean, SLA is a really a, in essence, a, an indication of the risk that you're able to take and willing to take. What are your customers tell you about SLS? The first thing is we don't hear a lot of questions about SLS from our customers. Some customers, it's very important that we have SLA is for most of our services, but what they're usually judging us on is the operational track record that we provide and doing testing and seeing how we operate and how we perform. Uh, and, uh, we had an analyst from IDC recently do a survey of a bunch of our customers and they found that on average the average app that runs on AWS had 80% less downtime than similar apps that are running on premises. >>So we have a lot of anecdotal evidence to suggest that our customers are seeing a reliability improvement by migrating their apps to AWS. You're saying don't judge us on the paper, judge us on our actual activities in production and in the field. Typically what most of our customers are asking for is they want to dig into the actual operational features and, and a track record. Now the other thing I want to address is the so called, you know, uh, uh, exit tax, right? It's no charge to get my data in there. I keep my data in there. You, you, you charged me for storing it for exercise and compute activity, but it's expensive to get it out. Um, how do you address that criticism? Well, our pricing is different for every service and we really model it around our customers to both really to really satisfy a broad set of use cases. >>So one example I think you may be talking about is I would Amazon glacier archive service, which is one penny per gigabyte per month. And for an archive service, we figured that most people want to keep their data in there for a long period of time so that we want to make it as cheap as possible for people to put it in. And if you actually needed to pull it out, the reason is because you may have had some disaster or you accidentally deleted something and that you are going to be, uh, you're going to be retrieving data on a far less frequent basis. So on an overall basis for most customers it makes sense that we could have done is made the retrieval costs lower and then made the storage costs higher. But the feedback we got from customers is, you know, archiving a majority of customers may never even retrieve that data at all. >>So it ended up being cheaper for a vast majority of our customers. I mean that's the point of glacier. If you put it there, you kind of hope you never have to go back and get it. Um, the other thing I wanted to ask you about is some of the innovations that we've seen lately in the industry, like a red shift, right? The data warehouse, you mentioned glacier. It was interesting. Andy said that glacier is the fastest growing service in terms of customers. Red shift was the fastest growing service, I guess overall at NAWS. So Redshift is an interesting move for you guys. Uh, that whole big data and analytics space. What if you could talk about that a little bit? If you talk to it, executives in the enterprise and even startups now, they have to analyze lots of data. Building a big data warehouse is, is one of the best examples of how much the pain of hardware and software infrastructure gets in the way of people. >>And there's also a gatekeeping aspect to it. If you're working in a big company and you want to run, you have a question and a hypothesis, you want to run queries against terabytes and petabytes of data, you pretty often have to go and ask for permission. Can I borrow some time from the data warehouse? No, no, no, no. You're not as important. Well, what are customers going to go, Hey, I'm going to go load the data, load a petabyte of data, run a bunch of analysis, and shut it down and only pay for a few hours. So it's not just about making a cheaper, it's about making use of technology possible where it was just not possible in feasible and cost prohibited before. Yeah, so that's an important point. I mean, it's not, it's not just about sort of moving workloads to the cloud, you know, the old saying a my mess for less. >>It's about enabling new business processes and new procedures and deeper business integration. Um, can you talk about that a little bit more? Add a little color to that notion of adding value beyond just moving workloads out of, you know, on premise into the cloud to cut costs, cut op ex, but enabling new business capabilities. When you remove the infrastructure burden between your ideas and what you want to do, you enable new things to be possible. I think innovation is a big aspect of this where if you think about if you reduce the cost of failure for technology projects so much that approaches zero, you change the whole risk taking culture in a company and more people can try out new ideas and companies can Greenlight more ideas because if they fail it doesn't cost you that much. You haven't built up all this infrastructure. So if you have more ideas that are, that are cultivated, you end up with more innovation. >>Whereas before people are too afraid to try new things. So I'm a reader of of Jeffrey's a annual letters. I mean I think they're great. They're Warren buffet like in that regard. One of the exact emphasizes, you know this year was the customer focus. You guys are a customer focused organization, not a competitive focused organization. And again, you got to recognize that both models can work, right? Can you talk about that a little bit? Just the church of the culture. Yeah, I mean when, you know, starts out with how we build our products. Anyone who has a new idea for a product, first thing they got to do is write the press release. So what our customers are going to see is it valuable to them. And then we get come get products out quickly and then we iterate with customers. We don't spend five years building the first version of something. >>We get it out quickly. Uh, sort of the, the, the lean startup, if you heard of the minimum viable product approach, get it out there and get feedback from customers. Uh, and iterate. We don't spend a lot of time looking at what our competitors are doing cause they're not the ones that pay our bill. They're not the ones that can hire and fire us. It's the customers. So I'm you've seen this thing come, you know, quite a ways. I mean, you were at Salesforce, right? Um, which I guess started at all in 99. You could sell that, look at that as the modern cloud sort of movement was, wasn't called cloud. And then you guys in 2006 actually announced what we now know is, you know, the cloud, where are we in terms of, you know, the cloud, you know, what ending is it? To use the sports analogy, I don't know what ending is it, but you know, it's an amazing time where there's such a massive amount of momentum of adoption of the cloud from every type of company, every type of government agency. >>But yet still, when you look at the percentage of it spend or you go talk to a large company and you say, even with all these projects, what percentage of your total projects, there's still tremendous growth ahead of us. Yeah. So, um, there's always that conversation about the pie charts. 70% of our, our effort is spent on keeping the lights on. 30% is spent on, on innovation. And I don't know where that number came from but, but I think generally anecdotally it feels about right. Um, talk about that shift. Yeah. Well I mean your customer base, you talk to any CIO, they don't like the idea of having 80% of their staff and budget being focused on keeping the lights on and the infrastructure would they like to do is to really shift the mix of what people are working on within their organization. It's not about getting rid of it, it's about giving it tools so that every ounce of effort they're doing is geared towards delivering things to the business. >>And that, that, that's what gets CIO is excited about the cloud is really shifting that and having a majority of their people building and iterating with their end users and with their customers. So we talked about the competition a little bit. I want to ask you a question in general, general terms, you guys have laid out sort of the playbook and there's a lot more coming. We know that, uh, but you know this industry quite well. You know, it's very competitive. People S people see what leaders are doing and they all sort of go after it. Why do you feel confident that AWS will be able to maintain its lead and Kennedy even extend its lead in why? Well, there's a couple things that we sort of suggest for customers to look at. I think first of all is the track record and experience of when you're looking at a cloud provider, have they been in this business for a long time? >>Do they have a services mentality where they've had customers trust them for their, for applications that really they trust their business on? Um, and then I think secondly, is there a commitment to innovation? Is there a pace of new features and new technologies as requirements change? And I think the other, the other piece that our customers really give us a lot of feedback on is that they can count on us Lauren prices, they can count on a real partnership as we get better at this and we're always learning as we get better and we reduce our cost structure, they're going to get to benefit and lower their costs as well. So I think those are kind of big things. The other thing is, is the customer ecosystem I think is a big part of it where, um, you know, this is technology. Uh, people need advice, they need, uh, best practices. >>They often need help. And I'm in a kind of analogy I make is if I have a problem with my phone, with my iPhone, I can probably close my eyes and throw it, I'm going to hit someone who also has an iPhone. I can ask them for help. Well, if you're a startup in San Francisco or London or if you're an enterprise in New York or Sydney, odds are that your colleagues, if they're doing cloud, they're doing it with AWS and you have a lot of people to help you out. A lot of people to share best practices with. And that's a subtle but important point is as, as industry participants begin to aggregate within your cloud, there's a data angle there, right? Because there's data that potentially those organizations could share if they so choose to a, that is a, that is a value. And as you say, the best practice sharing as well. >>I have two last questions for you. Sure. First is, is what gets you excited in this whole field? I think it's like seeing what customers are doing. I mean, that's the cool thing about, uh, offering cloud infrastructure is that anything is possible. Like we met Ryan, uh, who spoke from atomic fiction. These guys are the world's first digital effects agency that's 100% in the cloud. And to see that they made a movie and all the effects like the Robertson mech, his flight film without owning a single server, um, it's just, it's amazing. And to see what these guys can do, how happy they are to have a group of 30, 40 artists that, um, can say yes when the director says I want it to do differently. I want to add, go from 150 to 300 shots and to see how happy and excited they are. >>I mean that, that's what motivates me. Yeah. Okay. And then my last question, Ariel, is, um, you know, what keeps you up at night? What worries you? Well, I think, you know, the most important thing that we can't forget is to really keep our fingers on the pulse of the customers and what they want, and also helping them to figure out what they want next. Because if we don't keep moving, then we're not going to keep pace with what the customers want to use the cloud for. All right, Ariel Kelman thanks very much. Congratulations on the Mason's progress and we'll be watching and, and really appreciate, again, you having us here. Appreciate your time coming on. Good luck with the rest of the tour. I hope you don't have to do every city. It sounds like you don't, but, uh, but if it sounds like you've enjoyed them, so, uh, congratulations again. Great. All right. This is Dave Milan to keep it right there. This is the cube. We'll be back with our next guest right after this word.