>> From theCUBE studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante >> In its early days, robotic process automation emerged from rudimentary screen scraping, macros and workflow automation software. Once a script heavy and limited tool that largely was used to eliminate mundane tasks for individual users, and by the way still is, RPA's evolved into an enterprise-wide mega trend that puts automation at the center of digital business initiatives. Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this breaking analysis, we present our quarterly update of the trends in RPA and automation and share the latest survey data from enterprise technology research. RPA has grown quite rapidly and the acronym is becoming a convenient misnomer in a way. I mean the real action in RPA has evolved into enterprise-wide automation initiatives. Once exclusively focused really on back office automation and areas such as finance, RPA has now become an enterprise initiative as many larger organizations especially, move well beyond cost savings and outside of the CFO's purview. We predicted in early "Breaking Analysis" episodes that productivity declines in the US and Europe especially, would require automation to solve some of the world's most pressing problems. And that's what's happening. Automation today is attacking not only the labor shortage but it's supporting optimizations in ESG, supply chain, helping with inflation challenges, improving capital allocation. For example, the supply chain issues today, think about what they require. Somebody's got to do research, they got to figure out inventory management, they got to go into different systems, do prioritizations, do price matching, and perform a number of other complex tasks. These are time consuming processes. Now the combination of RPA and machine intelligence is helping managers compress the time to value and optimize decision making. Organizations are realizing that a digital business goes beyond cloud and SaaS, and puts data, AI and automation at the core leveraging cloud and SaaS but reimagining entire workflows and customer experiences. Moreover, low code solutions are taking off and dramatically expanding the ability of organizations to make changes to their processes. We're also seeing adjacencies to RPA becoming folded into enterprise automation initiatives. And that trend will continue for example Legacy software testing tools. This is especially important as companies SaaSify their business and look for modern testing tools that can keep pace with their transformations. So the bottom line is, RPA or intelligent automation has become a strategic priority for many companies. And that means you got to get the CIO involved to ensure that the governance and compliance edicts of the organization are appropriately met. And that alignment occurs across the technology and business lines. A couple of years ago, when we saw that RPA could be much much more than what it was at the time, we revisited our total available market or TAM analysis. And in doing so, we felt there would be a confluence of automation, AI, and data and that the front and back office schism would converge. That is shown here. This is our updated TAM chart, which we shared a while back with a dramatically larger scope. We were interested that, just a few days ago by the way Forrester put out a new report, picked up by Digital Nation, that the RPA market would reach 22 billion by 2025. Now, as we said at the time our TAM includes the entire ecosystem including professional services as does Forrester's recent report and the projections they're in. So see that little dotted red line there, that's about at the 22 billion mark. We're a few years away but we definitely feel as though this is taking shape the way we had previously envisioned. That is to say a progression from back office blending with customer facing processes becoming a core element of digital transformations and eventually entering the realm of automated systems of agency where automations are reliable enough and trusted enough to make realtime decisions at scale for a much, much wider scope of enterprise activities. So we see this evolving over the 2020s or the balance of this decade and becoming a massive multi hundred billion dollar market. Now, unfortunately for later investors, this enthusiasm that I'm sharing around automation has not translated into price momentum for the stocks in this sector. Here are the charts, the stock charts for four RPA related players with market values inserted in each graphic. We've set the cross hairs approximately at the timing of UiPath's IPO. And that's where we'll start. UiPath IPOed last April and you can see the steady decline in its price. UiPath's Series F investors got in at $30 billion valuation, so that's been halved, more than half. But UiPath is the leader in this sector as we'll see in a moment. So investors are just going to have to be patient. Now, you know the problem with these hot tech companies is the cat gets let out of the bag before the IPO because they raise so much private money, it hits the headlines and then, at the time you had zero interest rates, you had the tech stock boom during the pandemic, so you're just going to have to wait it out to get a nice return if you got in sort of post IPO. You know, which... I think this business will deliver over the long term. Now, Blue Prism is interesting because it's being bought by SS&C Technologies after a bidding war with Vista. So that's why their stock has held up pretty reasonably. Vista's PE firm, which owns TIBCO and was going to mash it, Blue Prism that is, together with TIBCO. That was a play I always liked because RPA is going to be integrated across the board. And TIBCO is an integration company, and I felt it was in a good position to do that. But SS&C obvious said, "Hey, we can do that too." And look, they're getting a proven RPA tech stack for 10% of the value of UiPath. Might be a sharp move, we'll see. Or maybe they'll jack prices and squeeze the cashflow, I honestly have no idea. And we shelled the other two players here who really aren't RPA specialists. Appian is a low code business process development platform and Pegasystems of course, we've reported on them extensively. They're a longtime business process player that has done pretty well. But both stocks have suffered pretty dramatically since last April. So let's take a look at the customer survey data and see what it tells us. The ETR survey data shows a pretty robust picture frankly. This chart depicts the net score or customer spending momentum on that vertical axis and market share or pervasiveness relative to other companies and technologies in the ETR dataset, that's on the horizontal. That red dotted line at the 40% mark, that indicates an elevated spending level for the company within this technology. The chart insert you see there shows how the company positions are plotted using net score and market share or Ns. And ETR's tool has a couple of cool features. We can click on the dot and it allows you to track the progression over time, in this case going back to January, 2020 that's the lines that we've inserted here. So we'll start with Microsoft and we'll get that over with. Microsoft acquired a company called Softomotive for a reported a hundred million dollars thereabout, it's a little more than that. So pretty much a lunch money for Mr. Softy. So Microsoft bought the company in May and look at the gray line where it started showing up in the October ETR surveys at a very highly elevated level, typical Microsoft, right? I mean, a lot of spending momentum and they're pretty much ubiquitous. And it just stayed there and it's gone up and to the right, just really a dominant picture. But Microsoft Power Automate is really kind of a personal productivity tool not super feature rich like some of the others that we're going to talk about, it's just part of the giant Microsoft software estate. And there's a substantial amount of overlap between, for example, UiPath's and Automation Anywhere's customer bases and Power Automate users. And it's speaking with the number of customers. They'll say, "Yeah, we use Power Automate," but they see enterprise automation platforms as much more feature rich and capable and they see a role for both. But it's something to watch out for because Microsoft can obviously take a bite out of virtually any platform and moderate the enthusiasm for it. But nonetheless, these other firms that we're mentioning here, the two leaders, they really stand out, UiPath and Automation Anywhere. Both are elevated well above that 40% line with a meaningful presence in the data set. And you can see the path that they took to get to where they are today. Now we had predicted in 2021 in our predictions post that Automation Anywhere would IPO in 2021. So we predicted that in December of 2020 but it hasn't happened yet. The company obviously wasn't ready, and it brought in new management. We reported on that, Chris Riley as the Chief Revenue Officer, and it made other moves to show up their business. Now let me say this about Riley. I've known him him for years, he's a world class sales leader, one of the best in the tech business. And he knows how to build a world class go to market team, I guarantee that's what he's doing. I have no doubt he's completely reinventing his sales team, the alliances, he's got a lot of experience of that when he was at EMC and Dell and HPE, and he knows the channel really well. So I have a great deal of confidence that if Automation Anywhere's product is any good, which the ETR data clearly shows that it is, then the company is going to do very well. Now, as for the timing of an IPO, look, with the market choppiness, who knows? Automation Anywhere, they raised a ton of dough and it was last valued around... In 2019, it was just north of 7 billion. And so if UiPath is valued at 15 billion, you could speculate that Automation Anywhere can't be valued at much more than 10 billion, maybe a little under, maybe a little over. And so they might wait for the market volatility to chill out a little bit before they do the IPO or maybe they've got some further cleanup to do and they want to get their metrics better, but we'll see. Now to the point earlier about Blue Prism, look at its position on the vertical axis, very respectable. Just a finer point on Pega. We've always said that they're not an RPA specialist but they have an RPA offering and a presence in the ETR data set in this sector. And they got a sizeable market cap so we'd like to include them. Now here's another look at the net score data. The way net score works is ETR asks customers, are you adopting a platform for the first time? That's that lime green there. Are you accelerating spending on the platform by 6% or more relative to last year, or sometimes relative to some other point in time, this is relative to last year. That's the forest green. Is your spending flat or is it, that's the gray, or is it decreasing by 6% or worse? Or are you churning? That's that bright red. You subtract the reds from the greens and you get net score which is shown for each company on the right along with the Ns in the survey. So other than Pega, every company shown here has new adoptions in the double digits, not a lot of churn. UiPath and and Automation Anywhere have net scores well over that 40% mark. Now, some other data points on those two, ETR did a little peeling of the onion in their data set and I found a couple of interesting nuggets. UiPath in the Fortune 500 has a 91% net score and a 77% net score in the Global 2000. So significantly higher than its overall average. This speaks to the company's strong presence in larger companies and the adoption and how larger companies are leaning in. Although UiPath's actually still solid in smaller firms as well by the way but... Now the other piece of information is, when asked why they buy UiPath over alternatives customers said a robust feature set, technical lead and compatibility with their existing environment. Now to Automation Anywhere. They have a 72% net score in the Fortune 500, well above its average across the survey, but 46% only in the Global 2000 below its overall average shown here of 54. So we'd like to see a wider aperture in the Global 2000. Again, this is a survey set, who knows, but oftentimes these surveys are indicative. So maybe Automation Anywhere just working that out, more time, figuring out the go to market in the Global 2000 beyond those larger customers. Now, when asked why they buy from Automation Anywhere versus the competition customers cited a robust feature set, just like UiPath, technological lead, just like UiPath, and fast ROI. Now I really believe that both for Automation Anywhere and UiPath, the time to value is much compressed relative to most technology projects. So I would highlight that as well. And I think that's a fundamental reason, one of the reasons why RPA has taken off. All right let's wrap up. The bottom line is this space is moving and it's evolving quickly, and will keep on a fast pace given the customer poll, the funding levels that have been poured into the space, and, of course, the competitive climate. We're seeing a new transformation agenda emerge. Pre COVID, the catalyst was back office efficiency. During the pandemic, we saw an acceleration and organizations are taking the lessons learned from that forced March experience, the digital I sometimes call it, and they're realizing a couple things. One, they can attack much more complex problems than previously envisioned. And two, in order to cloudify and SaaSify their businesses, they need to put automation along with data and AI at the core to completely transform into a digital entity. Now we're moving well beyond automating bespoke tasks and paving the cow path as I sometimes like to say. And we're seeing much more integration across systems like ERP and HR and finance and logistics et cetera, collaboration, customer experience, and importantly, this has to extend into broader ecosystems. We're also seeing a rise in semantic workflows to tackle more complex problems. We're talking here about going beyond a linear process of automation. Like for instance, read this, click on that, copy that, put it here, join it with that, drag and drop it over here and send it over there. It's evolving into a much more interpreter of actions using machine intelligence to watch, to learn, to infer, and then ultimately act as well as discover other process automation opportunities. So think about the way work is done today. Going into various applications, you grab data, you trombone back out, you do it again, in and out, in and out, in and out of these systems, et cetera, NASM, and replacing that sequence with a much more intelligent process. We're also seeing a lot more involvement from C-level executives, especially the CIO, but also the chief digital officer, the chief data officer, with low code solutions enabling lines of business to be much more involved in the game. So look, it's still early here. This sector, in my view, hasn't even hit that steep part of the S-curve yet, it's still building momentum with larger firms leading the innovation, investing in things like centers of excellence and training, digging in to find new ways of doing things. It's a huge priority because the efficiencies that large companies get, they drop right to the bottom line and the big ER the more money that drops. We see that in the adoption data and we think it's just getting started. So keep an eye on this space. It's not a fad, it's here to stay. Okay, that's it for now. Thanks to my colleagues, Stephanie Chan who helped research this week's topics and Alex Myerson on the production team who also manages the Breaking Analysis Podcast, Kristen Martin and Cheryl Knight, helped get the word out on social. Thanks guys. Your great teamwork, really appreciate that. Now remember, these episodes, they're all available as podcasts, wherever you listen just search "Breaking Analysis Podcast". Check out ETR's website at etr.ai. And we also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me directly, david.vellante@siliconangle.com is my email. You can DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights, powered by ETR. Have a great week, stay safe, be well, and we'll see you next time. (outro music)

>> Live from Washington DC, it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and its ecosystem partners. >> Hello everyone, welcome back. It's theCUBE's exclusive coverage. We're here in Washington, D.C. for live coverage of theCUBE here at Amazon Web Services, AWS Public Sector Summit. This is the re-invent for the global public sector. Technically they do a summit but it's really more of a very focused celebration and informational sessions with customers from Amazon Web Services, GovCloud, and also international, except China, different world. John Furrier, Dave Vellante here for our third year covering AWS Public Sector Summit and again our next guest is Max Peterson, the Vice President of International Sales Worldwide for public sector data, Max, good to see you, thanks for coming back. >> It's good to see you again, John, thank you. >> So, we saw you at dinner last night, great VIP Teresa Carlson dinner last night, it's a who's who in Washington, D.C., but also international global public sector. >> Absolutely. >> And so, I want to get your thoughts on this, because AWS is not just in D.C. for GovCloud, there's a global framework here. What's goin' on, what's your take on how this cloud is disrupting the digital nations, and obviously here at home in D.C.? >> Well, John, so first of all, I love your description of this as a celebration, because really that's one of the things that we do, is we celebrate customer success, and so when you look at AWS around the world, we've got customers that are delivering solutions for citizens, new solutions for healthcare, a great solution to education all around the world. In Europe, we serve all those customers from London, Ireland, Germany, Frankfurt, Paris, all open regions, and we're bringing two new regions that we've announced, in the Middle East, which is an exciting part of the Europe, Middle East, and Africa business, and then also up in the Nordics, with Sweden. >> Yeah, so I want to ask you about EMEA, Europe, Middle East and Africa, it's the acronym for essentially international. Huge growth, obviously Europe is a mature set of countries, and it has its own set of issues, but in the Middle East and outside of Europe there's a huge growing middle class of digital culture. >> Yes. >> You're seeing everything from cryptocurrency booming, blockchain, you're seeing kind of the financial industries changing, obviously mobile impact, you got a new revolution going on with digital. You guys have to kind of thread the needle on that. What are you guys doing to support those regions? Obviously, you got to invest, got GDP always in the headlines >> Right. >> Recently, that's Europe's issue, and globally, but you got Europe, and you got outside of Europe. Two different growth strategies, how is AWS investing, what are some of the things you guys are doing? >> Sure, let me try and get all of those questions >> (laughs) Just start them one at a time >> That was very good, yeah. So, let's do the invest and grow piece. Digital skills are critical, and that's one of the challenges with the overall digital transformation, and, by the way, that's not just EMEA, that's all around the world, right? Including the U.S., and so we're doing a lot of things to try to address the digital skills requirement, a program that we've got called AWS Educate just yesterday announced the Cloud Academy Course. So, career colleges, technical colleges will be able to teach a two-year course specifically on cloud, right? For traditional university education, we provide this thing called AWS Educate. We, in the UK, we started a program over 18 months ago called Restart, where we focus on military leavers, spouses, and disadvantaged youth through the prince's trust, and we're training a thousand people a year on AWS cloud computing and digital skills. Taking them, in this case, out of military, or from less advantaged backgrounds and bringin' 'em into tech. And then, finally in April of this year, at our Brussels public sector summit, a celebration of customers in EMEA, we announced that we're going to be training 100,000 people across Europe, Middle East and Africa, with a combination of all of these programs, so skills is absolutely top in terms of getting people on to the cloud, right, and having them be digitally savvy, but the other part that you talked about is really the generational and cultural changes. People expect service when they touch a button on the phone. And that's not how most governments work, it's not how a lot of educational institutions work, and so we're helping them. And so, literally now, across the region, we've got governments that are delivering online citizen services at the touch of a button. Big organizations, like the UK Home Office, like the Department for Wealth and Pensions, like the Ministry of Justice. And then, I think the other thing that you asked about was GDPR. >> Yeah. (laughs) >> Am I covering all the bases? >> You're doing good Max. >> You keep it rollin'. >> You're a clipping machine, here. >> So, GDPR might be thought of as a European phenomenon, but my personal opinion is that's going to set the direction for personal data privacy around the world, and we're seeing the implementation happen in Europe, but we're seeing also customers in the Middle East, in Asia, down in Latin America going, "Hey, that's a good example." And I think you'll see people adopt it, much like people have adopted the NIST definition of cloud computing. Why re-invent it? If there's something that's good, let's adopt it and go, and Amazon understood that that was coming, although some people act like it's a surprise. >> Yeah. >> Did your e-mail box get flooded with e-mail? >> Oh, Gosh. >> God, tons Well the day >> Day before. >> Yes! >> (laughs) >> Yes, day before! Acting like this was, like a surprise. It started two years before, so Amazon actually started our planning so that when the day arrived for it to be effective, AWS services were GDPR compliant so that customers could build GDPR compliant solutions on top of the cloud. >> So, I mean generally I know there's a lot of detail there, but what does that mean, GDPR compliant? 'Cause I like having my data in the cloud with GDPR, 'cause I can push a lot of the compliance onto my cloud provider, so what does that really mean, Max? >> Yeah, well fundamentally, GDPR gives people control of their information. An example is the right to be forgotten, right? Many companies, good companies were already doing that. This makes it a requirement across the entire EU, right? And so, what it means to be compliant is that companies, governments, people need to have a data architecture. They really have to understand where their data is, what information they're collecting, and they have to make the systems follow the rules for privacy protection. >> So how does AWS specifically help me as a customer? >> Right, so our customers around Europe, in fact, around the world build their solutions on top of Amazon. The Amazon services do things that are required by GDPR like encryption, alright? And so, you're supposed to encrypt and protect private data. In Amazon, all you do is click a button, and no matter where you store it, it's encrypted and protected. So a lot of organizations struggled to implement some of these basic protections. Amazon's done it forever, and under GDPR, we've organized those so that all of our services act the same. >> Max, this brings up security questions, 'cause, you know obviously we hear a lot of people use the cloud, as an example, for getting things stood up quickly, >> Yep. >> Whether it's an application in the past, and then say a data warehouse, you got redshifts, and kinesis, and at one point was the fastest growing service, as Andy Jassy said, now that's been replaced by a bunch of other stuff. You got SageMaker around the corner, >> SageMaker's awesome. >> So you got that ability, but also data is not just a data warehouse question. It's really a central value proposition, whether you're talking about in the cloud or IOT, so data becomes the center of the value proposition. How are you guys ensuring security? What are some of the conversations, because it certainly differs on a country by country basis. You got multiple regions developing, established and developing new ones for AWS. How do you look at that? How do you talk to customers and say, "Okay, here's our strategy, and here's what we're doing to secure your data, here's how you can go faster (laughs), keep innovating, because you know they don't want to go slower, because it's complicated. To do a GDPR overhaul, for some customers, is a huge task. How do you guys make it faster, while securing the data? >> Yeah, so first of all, your observation about data, having gravity, is absolutely true. What we've struggled with, with government customers, with healthcare and commercial enterprise, is people have their data locked up in little silos. So the first thing that people are doing on the cloud, is they're taking all that and putting it into a data warehouse, a data repository. Last night we heard from NASA, and from Blue Origin about the explosion in data, and in fact, what they said, and we believe, is that you're going to start bringing your compute to the data because the amount of information that you've got, when you've got billions of sensors, IOT, billions of these devices that are sending information or receiving information, you have to have a cloud strategy to store all that information. And then secondly, you have to have a cloud compute strategy to actually make use of that information. You can't download it anymore. If you're going to operate in real time, you've got to run that machine learning, right, in real time, against the data that's coming in, and then you've got to be able to provide the information back to an application or to people that makes use of it. So you just can't do it in-house anymore. >> You mentioned the talk last night as part of the Earth and Science Program, which you guys did, which by the way, I thought was fabulous. For the folks watching, they had a special inaugural event, before this event around earth and space, Blue Origin was there, Jet Propulsion Lab, much of the NASA guys, a lot of customers. But the interesting thing he said also, was is that they look at the data as a key part, and then he called himself a CTO, Chief Toy Officer. And he goes, "you got to play with the toys before they become too old," but that was a methodology that he was talking about how they get involved in using the tooling. Tooling becomes super important. You guys have a set of services, AWS, Amazon Web Services, which essentially are tools. >> Yeah. >> Collectively tools, you know global, you end up generalizing it, but this is important because now you can mix and match. Talk about how that's changed the customer mindset and how they roll out technology because they got to play, they got to experiment, as Andy Jassy would say, but also, also put the tools into production. How is it changing the face of your customer base? >> Sure, well, one of the things that customers love, is the selection of tools, but one of the most important things we actually do with customers, is help them to solve their problems. We have a professional service organization, we have what we call Envision Engineering, which is a specialized team that goes in and develops prototypes with customers, so that they understand how they can use these different tools to actually get their work done. One quick example: in the UK, the NHS had to implement a new program for people calling in to understand health benefits. And they could've done this in a very traditional fashion, it would've taken months and months to set up the call center and get everything rolling. Fortunately, they worked with one of our partners, and they understood that they could use new speech and language processing tools like Lex, and Amazon's in-the-cloud call center tools, like Connect. In two weeks, they were able to develop the application that handled 42% of the inbound call volume entirely automated, with speech and text processing, so that the other 52% could go to live operators where they had a more complex problem. That was prototyped in two weeks, it was implemented in three more weeks, a total of five weeks from concept to operation of a call center receiving thousands and thousands of inbound calls on the cloud. >> Max, can you paint a picture of the EMEA customer base, how it sort of compares to the US, the profile? I mean, obviously here, in the United States, you got a healthy mix of customers. You got startups, you're announcing enterprises, you got IOT use cases. I imagine a lot of diversity in EMEA, but how does it compare with the US, how would you describe it? Paint a picture for us. >> Yeah sure, candidly, we see the same exact patterns all around the world. Customers are in different stages of readiness, but across Europe, we have central governments that are bringing online, mission systems to the cloud. I mentioned Home Office, I mentioned DWP, I mentioned Her Majesty Revenue and Customs, HMRC. They're bringing real mission systems to the cloud now because they laid the right foundations, right? They've got a cloud native policy, and that's what directs government, that says stop building legacy systems and start building for the future by using the cloud. Educational institutions across the board are using AWS. Science and research, like the European Space Agency is using AWS, so we see, really, just the same pattern going on. Some areas of the world are newer to the cloud, so in the Middle East, we're seeing that sort of startup phase, where startup companies are gettin' onto the cloud. Some of 'em are very big. Careem is a billion dollar startup running on AWS, right. But we're helping startups just do the basics on the cloud. In Bahrain, which is a small country in the Middle East, they realized the transformative opportunity with cloud computing, and they decided to take the lead. They worked with AWS, they produced a national cloud policy, their CIO said we will move to the cloud, and that's key. Leadership is absolutely key. And then they put in place a framework, and they very systematically identified those applications that were ready, and they moved those first. Then they tackled the ones that weren't quite ready, and they moved those. They moved 450 applications in a matter of three months, to the cloud, but it was by having a focused program, top-level leadership, the right policy, and then we provided technical resources to help them do it. >> Max, I want to get one last question before the time comes up, but I want to put you on the spot here. >> Oh good. >> In the United States, Amazon Web Services public sector has really kind of changed the game. You saw the CIA deal that you guys did years ago, the Department of Defense is all in the news, obviously it's changing the ecosystem. How is that dynamic happening in Europe? You said the patterns are the same. Take a minute to just quickly describe, what's going on in the ecosystem? What's the partner profile look like? You've got a great partner ecosystem, and there are different partners. You mentioned Bahrain, Digital Nation, changing the game. You guys seem to attract kind of a new guard, a new kind of thinking, partners. What is the ecosystem partnerships look like for you guys, internationally, and is there the same dynamic going on that's happening in the US with the CIA, and DOD leaders around changing the narrative, changing the game, with technology? >> Sure, good questions. We wouldn't be able to deliver the solutions that we deliver to customers without our partner ecosystem. And sometimes, they're small, born in the cloud partners, the same sort of phenomenon that we have in the US. The example with the National Health Service was delivered by a expert consulting partner called Arcus Global, about a hundred person strong consulting organization that just knows cloud and makes it their business. And we see those throughout Europe, Middle East, and into Africa. We have our large global partners, Capgemini, Accenture, and then I think the other thing that's really important, is the regional partners. So what's happening is we're seeing those regional partners, partners like Everee, or Dee-Ecto, or SCC. We're seeing them now realize that their customers want to be agile, they want to be innovative, they want to be fast, and it doesn't hurt that they're going to save some money. And so we're seeing them change their business model, to adopt cloud computing, and that's the tipping point. When that middle, that trusted middle of partners, starts to adopt cloud and help the customers, that's when it really swings the other direction. >> It's great growth, and new growth brings new partners, new profiles, new brands, new names, and specialty is key. Max, thanks for coming on the CUBE. Really appreciate you taking the time. International, we're riding the wave of home sector with CUBE here in the US, soon we'll see you in some international summits. >> I'm looking forward, >> Alright. >> John, Dave, it was awesome to talk to you. >> Thanks Max. >> Alright, we are here live in Washington, D.C., for Amazon Web Services, AWS, Public Sector Summit 2018, we are in Washington, I'm John Furrier, Dave Vellante, and also Stu Miniman is here, the whole CUBE team is here, unpacking the phenomenon that is AWS, rocking the government and digital nations around the world. We're back with more, after this short break. (upbeat techno music)

>> Announcer: Live from Las Vegas. It's the Cube. Covering IBM Think 2018, brought to you by IBM. >> Hello everyone, I'm John Furrier. We are here in the Cube at IBM Think 2018. Great conversations here in the Mandalay Bay in Las Vegas for IMB Think, which is six shows wrapped into one, all combined into a big tent event. Good call by IBM, great branding. Our next guest is Rob Thomas. Cube alumni, general manager of IBM Analytics. Great to see you. >> John, great to see you. Thanks for being here. >> We love having you on, Cube alumni many times. I mean, you've seen the journey. I can remember when I talked to you, it was almost five, four or five years ago. Data, Hadoop, big data analytics, data lakes evolved significantly now where Jenny's major keynote speech has data at the center of the value proposition. I mean, we've said that before. >> Yes, we have. >> The data is the center of the value proposition. >> Every company is finally waking up. >> And then I had coined the term "the innovation sandwich." Blockchain on one side of the data, and you got AI on the other side, it's actually software. This is super important with multi-cloud. You've got multiple perspectives. You've got regions all around the world, GDPR, which everyone's been talking about, you guys have been doing lately, but the bigger question is: the technical stacks are changing. 30 years of stacks evolving, technology under the hood is changing, but the business models are also changing. This puts data as the number one conversation. That's your division. Your keynote here, what are you guys talking about? Are you hitting that note as well? >> So, number one is, think of this ladder to AI. We've talked about that before. Every client's on a journey towards AI, and there's a set of building blocks everybody needs to get there. We used the phrase once before, "There's no AI without IA," meaning if you want to get to that end point, you have to have the right information architecture. We're going to focus a lot on that. We've got a new product we've released called IBM Cloud Private for Data, which takes all of the assembly out of the data process. A really elegant solution to see all your enterprise data. That's going to be the focus for me this week. >> I want to get into that, but I also heard Scott, your VP of marketing now, talk about bad data can cripple you. So, I want to explain what that actually means. Because it's always been dirty data, it's been kind of a data science word, data warehouse word, clean data, you know, data cleanliness, but if you're going to use AI as a real strategic thing, you need high quality data. >> You do. >> John: Your thoughts? >> Think backwards from the shiny object, 'cause everybody loves the shiny object, which is some type of AI outcome, customer centricity, making you feel like a celebrity. There's two things that have to happen before that, or really three. One is you need some type of inferencing, a model layer where you're actually automating a lot of the predictive process. Before that, you need to actually understand what the data is. That's the data governance, the data integration. And before that, you need to actually have access to the data, meaning know where it's stored. Without those things, you just have a shiny object and not necessarily an outcome. That's why these building blocks are fundamental. And the clients, they get to this point, and they're the ones who try to jump to the shiny object and they don't have the data to support that. >> And then you've got companies going on digital transformation, which is basically saying all their data legacy, trying to modernize it. The modern companies like Uber, and we saw the first fatality of an Uber car this week, again, points out the reality that realtime is realtime, and the importance of having data, whether it's sensing data. We're not, it's coming there, you can start to see it happening. Realtime data is key. That means data mobility is critical, and you mentioned private, public. Storing the data and moving the data around, having data intelligence, is the most important thing. Realtime data in motion, intelligence, you know, where are we? Is that a setback with the Uber incident? Is it a step forward, is it learning? What's your view of the data quality of movement in realtime? >> I think data ingestion is one of the least talked about topics that is one of the most important. With IBM Cloud Private for data, we can ingest 250 billion events a day. Let me give you some context for that. 2016, the entire credit card industry, everywhere in the world, did 250 billion transactions. So what credit cards do in a year, we can do in a day. Biggest stock trading day ever on the New York Stock Exchange, what got done in that entire day, we can do in the first 40 minutes of trading. But that value there is, how fast can you bring data in to be analyzed, and can you do a decent bit of that pre-processing, or analytics, on the way in? That's how you start to solve some of the problems that you're describing, because it's instant >> John: Yeah. >> And it's unsurpassed amounts of data. >> So ingestion's a key part of the value chain, if you will, on data management. The new kind of data management. Ingesting it, understanding context, then is that where AI kicks in? Where does the AI kick in? Because the ingestion speaks to the information architecture, IA. >> Rob: Yes. >> Now I got to put AI on top of that data, so is the data different? Talk about the dynamic between, okay I'm ingesting data for the sake of ingesting, where does the AI connect? >> So you got the data, yep. So you go the data, AI starts where you're saying, all right, now we want to automate this. We're going to build models, we're going to use the data that we've got in here to train those models. As we get more data, the models are going to get better. Now we're going to connect it to how humans want to interact. Maybe it's natural language processing, maybe it's visualizing data. That's the whole lineage of how somebody gets toward this AI idea. >> What are some of the conversations you're having with customers, and how have they changed? And give some color, I mean, only a few years ago we're talking about data lakes. >> Right. >> Okay, what is the conversation now, and give some context of how far that conversation has gone down the road toward advancement. >> I think we're going from data lakes to an idea of a fluid data layer, which is all your data assets managed as a single system, even if they sit in different architectures. Because there's no one, we all know this. We've been around this industry forever. There's no one way to support or manage data that's going to support every use case. So this idea of a fluid data layer becomes critical for every organization. That's one big change. Other big change is containers. What we're doing with Cloud Private for Data is based on Kubernetes, that's how people want to consume applications, but nobody's really solved that for data. I think we're solving that for data. >> Let's dig into that. It was one of my topics I wanted to drill down on. Containers have been great for moving workloads around, certainly Kubernetes has been a great orchestration tool. How does that fit for data? I'm just putting a container on data sets? Who's addressing the envelope of that container? How is that addressable? I mean, how does it work? >> Let me give you an analogy. So you go back to the year 1955. There is no standards in any shipping port around the world. Everybody is literally building their own containers, building their own ships, building their own trucks. It's incredibly expensive and takes forever to get cargo to move from one place to the next. 1956, a guy named Malcom McClean, he invents the first intermodal shipping container, patents it. It becomes the standard. So now, every port, every container looks identical. What's the benefit? Sure, it made more flexibility. Saved lot of money, 90% of the cost came out of shipping a container. But the biggest thing is it changed commerce. So, you look at GDP at that time, it took off. All because of the standardization around a form factor that made it accessible to everybody. Now, let's put that in the IT world. We got containers for the application world. Made it much easier to deploy, a standard, again. >> Yeah, and program around. >> More cost-effective, more-- Yep, exactly. What's the cargo in IT? It's data. Data is the cargo, that's what's sitting inside the container. Now you have to say, how do we actually take the same concepts that we did for applications, make that available for data so that my data can fit anywhere? That's what we're doing. >> How does that work and what's the impact to the customer? Is it IBM software that you're doing? Is it Kubernetes open source software? Just tie that together for me. >> So IBM Cloud Private is our Kubernetes distribution, with some different pieces we put on it. When you add the Cloud Private for Data, it's got a Spark Engine, like everything we do it's based on open source to start with. And then we have an experience for a data scientist, an experience for a data analyst. It's your view to your enterprise data. You'll love the UI when you see it. First, above the fold, all my machine learning models in the organization, what's working, what's not working. Below the fold, what's my data? Structured or unstructured? Sensitive, non-sensitive? I click it on, I can see all of my data. Hadoop, Cloud-A, Cloud-B, Cloud-C, on-premise system. It's get a view to all of your data. >> So is the purpose to move the data around? >> No, the purpose is actually the exact opposite. Leave the data in place, but be able to treat it as a single data environment. We're doing a lot of work with Federation, our SQL technology which historically, as we all know, Federation hasn't really performed. We have it performing. >> Okay, so I'm just, in the use case in my head, so I store the data on my private, secure, comfortable, feeling good about it, but I have a public cloud app. How does that work? Is it a replica of the data? Is it just the container that makes it addressable? How does that move across? >> So, click a button, move the data. If you want it to be a replica, click a button and say "replicate." If you want to just move it, just click a button and move it. It's literally that easy. >> And so the customers can choose where to put the data. >> Yes. >> Can they do a public version of this, or only private? >> Both, it connects to public as well. >> Okay, so that was Jenny's mention, okay cool. What's the most exciting thing for you this week going on in your world? Obviously, center of the value proposition, and Jenny used your lines so I'm sure you fed her some good sound bytes there, because she was basically taking your pitch as the headline for the keynote. Is that the highlight, or is it customer activity? >> I think the exciting thing, and Jenny did talk about it, is connecting data to AI. I'd say many clients have kind of thought of those as two different topics. We do that in three ways. We say common machine learning fabric. You can build a model in Watson, you can deploy it where your enterprise data is or vice versa. We do that with the metadata. You create business or technical metadata on-premise, you can push that to Watson or vice versa. And like we just talked about, we make the data movement incredibly easy. So we're uniting these two worlds of data and AI that have tended to be different parts of an organization in many clients. We're uniting that, I think that's pretty interesting. >> All right, so final question, I've got to ask the tough one, which is, okay, Rob I love it, but I'm really not paying attention to the data because I've got my hands full in my IT transformation and we're making critical decisions on cloud globally, I've got multiple regions to deal with, I got different issues outside in each digital nation, but I'm going to get the data after. What's in it for me, your whole pitch? I'm dealing with cloud right now, so why should I be cross-connecting with the cloud decision and the cloud conversations that relate to the benefit of what you're doing? >> If you're not paying attention to the data, you're not going to be around. So your cloud decisions are kind of worthless, because you're not going to be around if you're not paying attention to the data. >> So I can make a bad cloud decision if I don't factor in what? >> I believe you have to think about your data strategy. Look, every organization is going to be multi-cloud, but you have to have a single data strategy regardless of what your cloud strategy is. You've got to think about all those building blocks I talked about. Manage data, collect data, govern data, analyze data. That has to be one strategy regardless of cloud. If you're not thinking about that, you're in trouble. >> Or making sure that I have Kubernetes? Is that a good decision? >> That is a great decision. >> (laughs) >> Makes it really easy, seamless to deploy applications, to deploy data, to move it around clouds. Makes it really easy. >> And what's the business model for containers? Kind of shifts to being a commodity? >> I think over time, yes, but there's so much to do around containers because containers, again, go back to the analogy. It's just the crate. >> John: Makes things easy. >> It's not the cargo, it's not the ship. It's just the crate, it's one piece. >> Yeah, and there's no, a lot of choice there, too. Clients can do whatever they want. >> Yeah. >> All right, we love Kubernetes. We'll be at KubeCon in Copenhagen next month, so keep a lookout there for us. This is Rob Thomas, here inside the Cube, here at IBM Think, breaking down all the action in the data science world, data world. It's the center of the value proposition. Main story here at IBM Think is data at the center of the value proposition for the modern enterprise. I'm John Furrier inside the Cube. We'll be back with more after this short break. (light electronic music)