>>From the Bellagio hotel in Las Vegas. It's the cube covering UI path forward for brought to you by UI path. >>Good morning. Welcome to the cubes coverage of UI path forward for day two. Live from the Bellagio in Las Vegas. I'm Lisa Martin with Dave Velante, Dave. We had a great action packed day yesterday. We're going to have another action packed day today. We've got the CEO coming on. We've got customers coming on, but there's been a lot in the news last 24 hours. Facebook, what are your thoughts? >>Yeah, so wall street journal today, headline Facebook hearing fuels call for rain in on big tech. All right, everybody's going after big tech. Uh, for those of you who missed it, 60 minutes had a, uh, an interview with the whistleblower. Her name is, uh, Francis Haugen. She's very credible, just a little background. I'll give you my take. I mean, she was hired to help set Facebook straight and protect privacy of individuals, of children. And I really feel like, again, she, she didn't come across as, as bitter or antagonistic, but, but I feel as though she feels betrayed, right, I think she was hired to do a job. They lured her in to say, Hey, this is again, just my take to say, Hey, we want your help in earnest to protect the privacy of our users, our citizens, et cetera. And I think she feels betrayed because she's now saying, listen, this is not cool. >>You hired us to do a job. We in earnest, went in and tried to solve this problem. And you guys kind of ignored it and you put profit ahead of safety. And I think that is the fundamental crux of this. Now she made a number of really good points in her hearing yesterday and I'll, and we'll try to summarize, I mean, there's a lot of putting advertising revenue ahead of children's safety and, and, and others. The examples they're using are during the 2020 election, they shut down any sort of negative conversations. They would be really proactive about that, but after the election, they turned it back on and you know, we all know what happened on January 6th. So there's sort of, you know, the senators are trying that night. Um, the second thing is she talked about Facebook as a wall garden, and she made the point yesterday at the congressional hearings that Google actually, you can data scientists, anybody can go download all the data that Google has on you. >>You and I can do that. Right? There's that website that we've gone to and you look at all the data Google has and you kind of freak out. Yeah, you can't do that with Facebook, right? It's all hidden. So it's kind of this big black box. I will say this it's interesting. The calls for breaking up big tech, Bernie Sanders tweeted something out yesterday said that, uh, mark Zuckerberg was worth, I don't know. I think 9 billion in 2007 or eight or nine, whatever it was. And he's worth 122 billion today, which of course is mostly tied up in Facebook stock, but still he's got incredible wealth. And then Bernie went on his red it's time to break up big tech. It's time to get people to pay their fair share, et cetera. I'm intrigued that the senators don't have as much vigilance around other industries, whether it's big pharma, food companies addicting children to sugar and the like, but that doesn't let Facebook. >>No, it doesn't, but, but you ha you bring up a good point. You and I were chatting about this yesterday. What the whistleblower is identifying is scary. It's dangerous. And the vast majority, I think of its users, don't understand it. They're not aware of it. Um, and why is big tech being maybe singled out and use as an example here, when, to your point, you know, the addiction to sugar and other things are, uh, have very serious implications. Why is big tech being singled out here as the poster child for what's going wrong? >>Well, and they're comparing it to big tobacco, which is the last thing you want to be compared to as big tobacco. But the, but the, but the comparison is, is valid in that her claim, the whistleblower's claim was that Facebook had data and research that it knew, it knows it's hurting, you know, you know, young people. And so what did it do? It created, you know, Instagram for kids, uh, or it had 600,000. She had another really interesting comment or maybe one of the senators did. Facebook said, look, we scan our records and you know, kids lie. And we, uh, we kicked 600,000 kids off the network recently who were underaged. And the point was made if you have 600,000 people on your network that are underage, you have to go kill. That's a problem. Right? So now the flip side of this, again, trying to be balanced is Facebook shut down Donald Trump and his nonsense, uh, and basically took him off the platform. >>They kind of thwarted all the hunter Biden stuff, right. So, you know, they did do some, they did. It's not like they didn't take any actions. Uh, and now they're up, you know, in front of the senators getting hammered. But I think the Zuckerberg brings a lot of this on himself because he put out an Instagram he's on his yacht, he's drinking, he's having fun. It's like he doesn't care. And he, you know, who knows, he probably doesn't. She also made the point that he owns an inordinate percentage and controls an inordinate percentage of the stock, I think 52% or 53%. So he can kind of do what he wants. And I guess, you know, coming back to public policy, there's a lot of narrative of, I get the billionaires and I get that, you know, the Mo I'm all for billionaires paying more taxes. >>But if you look at the tax policies that's coming out of the house of representatives, it really doesn't hit the billionaires the way billionaires can. We kind of know the way that they protect their wealth is they don't sell and they take out low interest loans that aren't taxed. And so if you look at the tax policies that are coming out, they're really not going after the billionaires. It's a lot of rhetoric. I like to deal in facts. And so I think, I think there's, there's a lot of disingenuous discourse going on right now at the same time, you know, Facebook, they gotta, they gotta figure it out. They have to really do a better job and become more transparent, or they are going to get broken up. And I think that's a big risk to the, to their franchise and maybe Zuckerberg doesn't care. Maybe he just wants to give it a, give it to the government, say, Hey, are you guys are on? It >>Happens. What do you think would happen with Amazon, Google, apple, some of the other big giants. >>That's a really good question. And I think if you look at the history of the us government, in terms of ant anti monopolistic practices, it spent decade plus going after IBM, you know, at the end of the day and at the same thing with Microsoft at the end of the day, and those are pretty big, you know, high profiles. And then you look at, at T and T the breakup of at T and T if you take IBM, IBM and Microsoft, they were slowed down by the U S government. No question I've in particular had his hands shackled, but it was ultimately their own mistakes that caused their problems. IBM misunderstood. The PC market. It gave its monopoly to Intel and Microsoft, Microsoft for its part. You know, it was hugging windows. They tried to do the windows phone to try to jam windows into everything. >>And then, you know, open source came and, you know, the world woke up and said, oh, there's this internet that's built on Linux. You know, that kind of moderated by at T and T was broken up. And then they were the baby bells, and then they all got absorbed. And now you have, you know, all this big, giant telcos and cable companies. So the history of the U S government in terms of adjudicating monopolistic behavior has not been great at the same time. You know, if companies are breaking the law, they have to be held accountable. I think in the case of Amazon and Google and apple, they, a lot of lawyers and they'll fight it. You look at what China's doing. They just cut right to the chase and they say, don't go to the, they don't litigate. They just say, this is what we're doing. >>Big tech, you can't do a, B and C. We're going to fund a bunch of small startups to go compete. So that's an interesting model. I was talking to John Chambers about this and he said, you know, he was flat out that the Western way is the right way. And I believe in, you know, democracy and so forth. But I think if, to answer your question, I think they'll, they'll slow it down in courts. And I think at some point somebody's going to figure out a way to disrupt these big companies. They always do, you know, >>You're right. They always do >>Right. I mean, you know, the other thing John Chambers points out is that he used to be at 1 28, working for Wang. There is no guarantee that the past is prologue that because you succeeded in the past, you're going to succeed in the future. So, so that's kind of the Facebook break up big tech. I'd like to see a little bit more discussion around, you know, things like food companies and the, like >>You bring up a great point about that, that they're equally harmful in different ways. And yet they're not getting the visibility that a Facebook is getting. And maybe that's because of the number of users that it has worldwide and how many people depend on it for communication, especially in the last 18 months when it was one of the few channels we had to connect and engage >>Well. And, and the whistleblower's point, Facebook puts out this marketing narrative that, Hey, look at all this good we're doing in reality. They're all about the, the, the advertising profits. But you know, I'm not sure what laws they're breaking. They're a public company. They're, they're, they have a responsibility to shareholders. So that's, you know, to be continued. The other big news is, and the headline is banks challenge, apple pay over fees for transactions, right? In 2014, when apple came up with apple pay, all the banks lined up, oh, they had FOMO. They didn't want to miss out on this. So they signed up. Now. They don't like the fact that they have to pay apple fees. They don't like the fact that apple introduced its own credit card. They don't like the fact that they have to pay fees on monthly recurring charges on your, you know, your iTunes. >>And so we talked about this and we talk about it a lot on the cube is that, that in, in, in, in his book, seeing digital David, Michelle, or the author talked about Silicon valley broadly defined. So he's including Seattle, Microsoft, but more so Amazon, et cetera, has a dual disruption agenda. They're not only trying to disrupt horizontally the technology industry, but they're also disrupting industry. We talked about this yesterday, apple and finances. The example here, Amazon, who was a bookseller got into cloud and is in grocery and is doing content. And you're seeing these a large companies, traverse industry value chains, which have historically been very insulated right from that type of competition. And it's all because of digital and data. So it's a very, pretty fascinating trends going on. >>Well, from a financial services perspective, we've been seeing the unbundling of the banks for a while. You know, the big guys with B of A's, those folks are clearly concerned about the smaller, well, I'll say the smaller FinTech disruptors for one, but, but the non FinTech folks, the apples of the world, for example, who aren't in that industry who are now to your point, disrupting horizontally and now going after individual specific industries, ultimately I think as consumers we want, whatever is going to make our lives easier. Um, do you ever, ever, I always kind of scratch my nose when somebody doesn't take apple pay, I'm like, you don't take apple pay so easy. It's so easy to make this easy for me. >>Yeah. Yeah. So it's, it's going to be really interesting to see how this plays out. I, I do think, um, you know, it begs the question when will banks or Willbanks lose control of the payment systems. They seem to be doing that already with, with alternative forms of payment, uh, whether it's PayPal or Stripe or apple pay. And then crypto is, uh, with, with, with decentralized finance is a whole nother topic of disruption and innovation, >>Right? Well, these big legacy institutions, these organizations, and we've spoke with some of them yesterday, we're going to be speaking with some of them today. They need to be able to be agile, to transform. They have to have the right culture in order to do that. That's the big one. They have to be willing. I think an open to partner with the broader ecosystem to unlock more opportunities. If they want to be competitive and retain the trust of the clients that they've had for so long. >>I think every industry has a digital disruption scenario. We used to always use the, don't get Uber prized example Uber's coming on today, right? And, and there isn't an industry, whether it's manufacturing or retail or healthcare or, or government that isn't going to get disrupted by digital. And I think the unique piece of this is it's it's data, data, putting data at the core. That's what the big internet giants have done. That's what we're hearing. All these incumbents try to do is to put data. We heard this from Coca-Cola yesterday, we're putting data at the core of our company and what we're enabling through automation and other activities, uh, digital, you know, a company. And so, you know, can these, can these giants, these hundred plus year old giants compete? I think they can because they don't have to invent AI. They can work with companies like UI path and embed AI into their business and focused on, on what they do best. Now, of course, Google and Amazon and Facebook and Microsoft there may be going to have the best AI in the world. But I think ultimately all these companies are on a giant collision course, but the market is so huge that I think there's a lot of, >>There's a tremendous amount of opportunity. I think one of the things that was exciting about talking to one, the female CIO of Coca-Cola yesterday, a hundred plus old organization, and she came in with a very transformative, very different mindset. So when you see these, I always appreciate when I say legacy institutions like Coca-Cola or Merck who was on yesterday, blue cross blue shield who's on today, embracing change, cultural change going. We can't do things the way we used to do, because there are competitors in that review mirror who are smaller, they're more nimble, they're faster. They're going to be, they're going to take our customers away from us. We have to deliver this exceptional customer and employee experience. And Coca-Cola is a great example of one that really came in with CA brought in a disruptor in order to align digital with the CEO's thoughts and processes and organization. These are >>Highly capable companies. We heard from the head of finance at, at applied materials today. He was also coming on. I was quite, I mean, this is a applied materials is really strong company. They're talking about a 20 plus billion dollar company with $120 billion market cap. They supply semiconductor equipment and they're a critical component of the semiconductor supply chain. And we all know what's going on in semiconductors today with a huge shortage. So they're a really important company, but I was impressed with, uh, their finance leaders vision on how they're transforming the company. And it was not like, you know, 10 years out, these were not like aspirational goals. This is like 20, 19, 20, 22. Right. And, and really taking costs out of the business, driving new innovation. And, and it's, it was it's, it's refreshing to me Lisa, to see CFOs, you know, typically just bottom line finance focused on these industry transformations. Now, of course, at the end of the day, it's all about the bottom line, but they see technology as a way to get there. In fact, he put technology right in the middle of his stack. I want to ask him about that too. I actually want to challenge him a little bit on it because he had that big Hadoop elephant in the middle and this as an elephant in the room. And that picture, >>The strategy though, that applied materials had, it was very well thought out, but it was also to your point designed to create outcomes year upon year upon year. And I was looking at some of the notes. I took that in year one, alone, 274 automations in production. That's a lot, 150,000 in annual work hours automated 124 use cases they tackled in one year. >>So I want to, I want to poke at that a little bit too. And I, and I did yesterday with some guests. I feel like, well, let's see. So, um, I believe it was, uh, I forget what guests it was, but she said we don't put anything forward that doesn't hit the income statement. Do you remember that? Yes, it was Chevron because that was pushing her. I'm like, well, you're not firing people. Right. And we saw from IDC data today, only 13% of organizations are saying, or, or, or the organizations at 13% of the value was from reduction in force. And a lot of that was probably in plan anyway, and they just maybe accelerated it. So they're not getting rid of headcount, but they're counting hours saved. So that says to me, there's gotta be an normally or often CFOs say, well, it's that soft dollars because we're redeploying folks. But she said, no, it hits the income statement. So I don't, I want to push a little bit and see how they connect the dots, because if you're going to save hours, you're going to apply people to new work. And so either they're generating revenue or cutting costs somewhere. So, so there's another layer that I want to appeal to understand how that hits the income state. >>Let's talk about some of that IDC data. They announced a new white paper this morning sponsored by UI path. And I want to get your perspectives on some of the stats that they talked about. They were painting a positive picture, an optimistic picture. You know, we can't talk about automation without talking about the fear of job loss. They've been in a very optimistic picture for the actual gains over a few year period. What are your thoughts about that? Especially when we saw that stat 41% slowed hiring. >>Yeah. So, well, first of all, it's a sponsored study. So, you know, and of course the conferences, so it's going to be, be positive, but I will say this about IDC. IDC is a company I would put, you know, forest they're similar. They do sponsored research and they're credible. They don't, they, they have the answer to their audience, so they can't just out garbage. And so it has to be defensible. So I give them credit there that they won't just take whatever the vendor wants them to write and then write it. I've used to work there. And I, and I know the culture and there's a great deal of pride in being able to defend what you do. And if the answer doesn't come out, right, sorry, this is the answer. You know, you could pay a kill fee or I dunno how they handle it today. >>But, but, so my point is I think, and I know the people who did that study, many of them, and I think they're pretty credible. I, I thought by the way, you, to your 41% point. So the, the stat was 13% are gonna reduce head count, right? And then there were two in the middle and then 41% are gonna reduce or defer hiring in the future. And this to me, ties into the Erik Brynjolfsson and, and, and, uh, and, and McAfee work. Andy McAfee work from MIT who said, look, initially actually made back up. They said, look at machines, have always replaced humans. Historically this was in their book, the second machine age and what they said was, but for the first time in history, machines are replacing humans with cognitive functions. And this is sort of, we've never seen this before. It's okay. That's cool. >>And their, their research suggests that near term, this is going to be a negative economic impact, sorry, negative impact on jobs and salaries. And we've, we've generally seen this, the average salary, uh, up until recently has been flat in the United States for years and somewhere in the mid fifties. But longterm, their research shows that, and this is consistent. I think with IDC that it's going to help hiring, right? There's going to be a boost buddy, a net job creator. And there's a, there's a, there's a chasm you've got across, which is education training and skill skillsets, which Brynjolfsson and McAfee focused on things that humans can do that machines can't. And you have this long list and they revisited every year. Like they used to be robots. Couldn't walk upstairs. Well, you see robots upstairs all the time now, but it's empathy, it's creativity. It's things like that. >>Contact that humans are, are much better at than machines, uh, even, even negotiations. And, and so, so that's, those are skills. I don't know where you get those skills. Do you teach those and, you know, MBA class or, you know, there's these. So their point is there needs to be a new thought process around education, public policy, and the like, and, and look at it. You can't protect the past from the future, right? This is inevitable. And we've seen this in terms of economic activity around the world countries that try to protect, you know, a hundred percent employment and don't let competition, they tend to fall behind competitively. You know, the U S is, is not of that category. It's an open market. So I think this is inevitable. >>So a lot about upskilling yesterday, and the number of we talked with PWC about, for example, about what they're doing and a big focus on upscaling. And that was part of the IDC data that was shared this morning. For example, I'll share a stat. This was a survey of 518 people. 68% of upscaled workers had higher salaries than before. They also shared 57% of upskilled workers had higher roles and their enterprises then before. So some, again, two point it's a sponsored study, so it's going to be positive, but there, there was a lot of discussion of upskilling yesterday and the importance on that education, because to your point, we can't have one without the other. You can't give these people access to these tools and not educate them on how to use it and help them help themselves become more relevant to the organization. Get rid of the mundane tasks and be able to start focusing on more strategic business outcome, impacting processes. >>We talked yesterday about, um, I use the example of, of SAP. You, you couldn't have predicted SAP would have won the ERP wars in the early to mid 1990s, but if you could have figured out who was going to apply ERP to their businesses, you know what, you know, manufacturing companies and these global firms, you could have made a lot of money in the stock market by, by identifying those that were going to do that. And we used to say the same thing about big data, and the reason I'm bringing all this up is, you know, the conversations with PWC, Deloitte and others. This is a huge automation, a huge services opportunity. Now, I think the difference between this and the big data era, which is really driven by Hadoop is it was big data was so complicated and you had a lack of data scientists. >>So you had to hire these services firms to come in and fill those gaps. I think this is an enormous services opportunity with automation, but it's not because the software is hard to get to work. It's all around the organizational processes, rethinking those as people process technology, it's about the people in the process, whereas Hadoop and the big data era, it was all about the tech and they would celebrate, Hey, this stuff works great. There are very few companies really made it through that knothole to dominate as we've seen with the big internet giants. So you're seeing all these big services companies playing in this market because as I often say, they like to eat at the trough. I know it's kind of a pejorative, but it's true. So it's huge, huge market, but I'm more optimistic about the outcomes for a broader audience with automation than I was with, you know, big data slash Hadoop, because I think the software as much, as much more adoptable, easier to use, and you've got the cloud and it's just a whole different ball game. >>That's certainly what we heard yesterday from Chevron about the ease of use and that you should be able to see results and returns very quickly. And that's something too that UI path talks about. And a lot of their marketing materials, they have a 96, 90 7% retention rate. They've done a great job building their existing customers land and expand as we talked about yesterday, a great use case for that, but they've done so by making things easy, but hearing that articulated through the voice of their customers, fantastic validation. >>So, you know, the cube is like a little, it's like a interesting tip of the spirits, like a probe. And I will tell you when I, when we first started doing the cube and the early part of the last decade, there were three companies that stood out. It was Splunk service now and Tableau. And the reason they stood out is because they were able to get customers to talk about how great they were. And the light bulb went off for us. We were like, wow, these are three companies to watch. You know, I would tell all my wall street friends, Hey, watch these companies. Yeah. And now you see, you know, with Frank Slootman at snowflake, the war, the cat's out of the bag, everybody knows it's there. And they're expecting, you know, great things. The stock is so priced to perfection. You could argue, it's overpriced. >>The reason I'm bringing this up is in terms of customer loyalty and affinity and customer love. You're getting it here. Absolutely this ecosystem. And the reason I bring that up is because there's a lot of questions in the, in the event last night, it was walking around. I saw a couple of wall street guys who came up to me and said, Hey, I read your stuff. It was good. Let's, let's chat. And there's a lot of skepticism on, on wall street right now about this company. Right? And to me, that's, that's good news for you. Investors who want to do some research, because the words may be not out. You know, they, they, they gotta prove themselves here. And to me, the proof is in the customer and the lifetime value of that customer. So, you know, again, we don't give stock advice. We, we kind of give fundamental observations, but this stock, I think it's trading just about 50. >>Now. I don't think it's going to go to 30, unless the market just tanks. It could have some, you know, if that happens, okay, everything will go down. But I actually think, even though this is a richly priced stock, I think the future of this company is very bright. Obviously, if they continue to execute and we're going to hear from the CEO, right? People don't know Daniel, Denise, right? They're like, who is this guy? You know, he started this company and he's from Eastern Europe. And we know he's never have run a public company before, so they're not diving all in, you know? And so that to me is something that really pay attention to, >>And we can unpack that with him later today. And we've got some great customers on the program. You mentioned Uber's here. Spotify is here, applied materials. I feel like I'm announcing something on Saturday night. Live Uber's here. Spotify is here. All right, Dave, looking forward to a great action packed today. We're going to dig more into this and let's get going. Shall we let's do it. All right. For David Dante, I'm Lisa Martin. This is the cube live in Las Vegas. At the Bellagio. We are coming to you presenting UI path forward for come back right away. Our first guest comes up in just a second.

>> Announcer: From Chicago, it's theCUBE, covering Oracle Transformation Day 2020. Brought to you by Oracle Consulting. >> Welcome back, everybody, to this special digital event coverage that theCUBE is looking into the rebirth of Oracle Consulting. Janet George is here, she's a group VP, autonomous for advanced analytics with machine learning and artificial intelligence at Oracle, and she's joined by Grant Gibson, who's a group VP of growth and strategy at Oracle. Folks, welcome to theCUBE, thanks so much for coming on. >> Thank you. >> Thank you. >> Grant, I want to start with you because you've got strategy in your title. I'd like to start big-picture. What is the strategy with Oracle, specifically as it relates to autonomous, and also consulting? >> Sure, so, I think Oracle has a deep legacy of strength in data, and over the company's successful history, it's evolved what that is from steps along the way. And if you look at the modern enterprise, an Oracle client, I think there's no denying that we've entered the age of AI, that everyone knows that artificial intelligence and machine learning are a key to their success in the business marketplace going forward. And while generally it's acknowledged that it's a transformative technology, and people know that they need to take advantage of it, it's the how that's really tricky, and that most enterprises, in order to really get an enterprise-level ROI on an AI investment, need to engage in projects of significant scope. And going from realizing there's an opportunity or realizing there's a threat to mobilizing yourself to capitalize on it is a daunting task for enterprise. Certainly one that's, anybody that's got any sort of legacy of success has built-in processes, has built-in systems, has built-in skill sets, and making that leap to be an autonomous enterprise is challenging for companies to wrap their heads around. So as part of the rebirth of Oracle Consulting, we've developed a practice around how to both manage the technology needs for that transformation as well as the human needs, as well as the data science needs to it. So there's-- >> So, wow, there's about five or six things that I want to (Grant chuckles) follow up with you there, so this is a good conversation. Janet, ever since I've been in the industry, when you're talking about AI, it's sort of start-stop, start-stop. We had the AI winter, and now it seems to be here. It almost feels like the technology never lived up to its promise, 'cause we didn't have the horsepower, the compute power, it didn't have enough data, maybe. So we're here today, it feels like we are entering a new era. Why is that, and how will the technology perform this time? >> So for AI to perform, it's very reliant on the data. We entered the age of AI without having the right data for AI. So you can imagine that we just launched into AI without our data being ready to be training sets for AI. So we started with BI data, or we started with data that was already historically transformed, formatted, had logical structures, physical structures. This data was sort of trapped in many different tools, and then, suddenly, AI comes along, and we say, take this data, our historical data, we haven't tested it to see if this has labels in it, this has learning capability in it. We just thrust the data to AI. And that's why we saw the initial wave of AI sort of failing, because it was not ready for AI, ready for the generation of AI, if you will. >> So, to me, this is, I always say this was the contribution that Hadoop left us, right? I mean, Hadoop, everybody was crazy, it turned into big data. Oracle was never that nuts about it, they just kind of watched, sat back and watched, obviously participated. But it gathered all this data, it created cheap data lakes, (laughs) which people always joke, turns into data swamps. But the data is oftentimes now within organizations, at least present, right. >> Yes, yes, yes. >> Like now, it's a matter of what? What's the next step for really good value? >> Well, basically, what Hadoop did to the world of data was Hadoop freed data from being stuck in tools. It basically brought forth this concept of platform. And platform is very essential, because as we enter the age of AI and we enter the petabyte range of data, we can't have tools handling all of this data. The data needs to scale. The data needs to move. The data needs to grow. And so, we need the concept of platform so we can be elastic for the growth of the data. It can be distributed. It can grow based on the growth of the data. And it can learn from that data. So that's the reason why Hadoop sort of brought us into the platform world. And-- >> Right, and a lot of that data ended up in the cloud. I always say for years, we marched to the cadence of Moore's law. That was the innovation engine in this industry. As fast as you could get a chip in, you'd get a little advantage, and then somebody would leapfrog. Today, it's, you've got all this data, you apply machine intelligence, and cloud gives you scale, it gives you agility. Your customers, are they taking advantage of that new innovation cocktail? First of all, do you buy that, and how do you see them taking advantage of this? >> Yeah, I think part of what Janet mentioned makes a lot of sense, is that at the beginning, when you're taking the existing data in an enterprise and trying to do AI to it, you often get things that look a lot like what you already knew, because you're dealing with your existing data set and your existing expertise. And part of, I think, the leap that clients are finding success with now is getting novel data types. You're moving from the zeroes and ones of structured data to image, language, written language, spoken language. You're capturing different data sets in ways that prior tools never could, and so, the classifications that come out of it, the insights that come out of it, the business process transformation that comes out of it is different than what we would have understood under the structured data format. So I think it's that combination of really being able to push massive amounts of data through a cloud product to be able to process it at scale. That is what I think is the combination that takes it to the next plateau for sure. >> So you talked about sort of we're entering the new era, age of AI. A lot of people kind of focus on the cloud as sort of the current era, but it really does feel like we're moving beyond that. The language that we use today, I feel like, is going to change, and you just started to touch on some of it, sensing, our senses, and the visualization, and the auditory, so it's sort of this new experience that customers are seeing, and a lot of this machine intelligence behind that. >> I call it the autonomous enterprise, right? >> Okay. >> The journey to be the autonomous enterprise. And when you're on this journey to be the autonomous enterprise, you need, really, the platform that can help you be. Cloud is that platform which can help you get to the autonomous journey. But the autonomous journey does not end with the cloud, or doesn't end with the data lake. These are just infrastructures that are basic, necessary, necessities for being on that autonomous journey. But at the end, it's about, how do you train and scale very large-scale training that needs to happen on this platform for AI to be successful? And if you are an autonomous enterprise, then you have really figured out how to tap into AI and machine learning in a way that nobody else has to derive business value, if you will. So you've got the platform, you've got the data, and now you're actually tapping into the autonomous components, AI and machine learning, to derive business intelligence and business value. >> So I want to get into a little bit of Oracle's role, but to do that, I want to talk a little bit more about the industry. So if you think about the way the industry seems to be restructuring around data, historically, industries had their own stack or value chain, and if you were in the finance industry, you were there for life, you know? >> Yes. >> You had your own sales channel, distribution, et cetera. But today, you see companies traversing industries, which has never happened before. You see Apple getting into content, and music, and there's so many examples, Amazon buying Whole Foods. Data is sort of the enabler there. You have a lot of organizations, your customers, that are incumbents, that they don't want to get disrupted. A big part of your role is to help them become that autonomous enterprise so they don't get disrupted. I wonder if you could maybe comment on how you're doing. >> Yeah, I'll comment, and then, Grant, you can chime in. >> Great. >> So when you think about banking, for example, highly regulated industry, think about agriculture, these are highly regulated industries. It is very difficult to disrupt these industries. But now you're looking at Amazon, and what does an Amazon or any other tech giant like Apple have? They have incredible amounts of data. They understand how people use, or how they want to do, banking. And so, they've come up with Apple Cash, or Amazon Pay, and these things are starting to eat into the market. So you would have never thought an Amazon could be a competition to a banking industry, just because of regulations, but they are not hindered by the regulations because they're starting at a different level, and so, they become an instant threat and an instant disruptor to these highly regulated industries. That's what data does. When you use data as your DNA for your business, and you are sort of born in data, or you've figured out how to be autonomous, if you will, capture value from that data in a very significant manner, then you can get into industries that are not traditionally your own industry. It can be the food industry, it can be the cloud industry, the book industry, you know, different industries. So that's what I see happening with the tech giants. >> So, Grant, this is a really interesting point that Janet is making, that, you mentioned you started off with a couple of industries that are highly regulated and harder to disrupt. You know, music got disrupted, publishing got disrupted, but you've got these regulated businesses, defense. Automotive hasn't been truly disrupted yet, so Tesla maybe is a harbinger. And so, you've got this spectrum of disruption. But is anybody safe from disruption? >> (laughs) I don't think anyone's ever safe from it. It's change and evolution, right? Whether it's swapping horseshoes for cars, or TV for movies, or Netflix, or any sort of evolution of a business, I wouldn't coast on any of it. And I think, to your earlier question around the value that we can help bring to Oracle customers is that we have a rich stack of applications, and I find that the space between the applications, the data that spans more than one of them, is a ripe playground for innovations where the data already exists inside a company but it's trapped from both a technology and a business perspective, and that's where, I think, really, any company can take advantage of knowing its data better and changing itself to take advantage of what's already there. >> The powerful people always throw the bromide out that data is the new oil, and we've said, no, data's far more valuable, 'cause you can use it in a lot of different places. Oil, you can use once and it's all you can do. >> Yeah. >> It has to follow the laws of scarcity. Data, if you can unlock it, and so, a lot of the incumbents, they have built a business around whatever, a factory or process and people. A lot of the trillion-dollar startups, that become trillionaires, you know who I'm talking about, data's at the core, they're data companies. So it seems like a big challenge for your incumbent customers, clients, is to put data at the core, be able to break down those silos. How do they do that? >> Mm, grating down silos is really super critical for any business. If it's okay to operate in a silo, for example, you would think that, "Oh, I could just be payroll and expense reports, "and it wouldn't matter if I get into vendor "performance management or purchasing. "That can operate as a silo." But anymore, we are finding that there are tremendous insights between vendor performance management and expense reports, these things are all connected. So you can't afford to have your data sit in silos. So grating down that silo actually gives the business very good performance, insights that they didn't have before. So that's one way to go. But another phenomena happens. When you start to grate down the silos, you start to recognize what data you don't have to take your business to the next level. That awareness will not happen when you're working with existing data. So that awareness comes into form when you grate the silos and you start to figure out you need to go after a different set of data to get you to new product creation, what would that look like, new test insights, or new capex avoidance, that data is just, you have to go through the iteration to be able to figure that out. >> And then it becomes a business problem, right? If you've got a process now where you can identify 75% of the failures, and you know the value of the other 25% of the failures, it becomes a simple investment. "How much money am I willing to invest "to knock down some portion of that 25%?" And it changes it from simply an IT problem or an expense management problem to the universal cash problem. >> To a business problem. >> But you still need a platform that has APIs, that allows you to bring in-- >> Yes, yes. >> Those data sets that you don't have access to, so it's an enabler. It's not the answer, it's not the outcome, in and of itself, but it enables the outcome. >> Yeah, and-- >> I always say you can't have the best toilet if your plumbing doesn't work, you know what I mean? So you have to have your plumbing. Your plumbing has to be more modern. So you have to bring in modern infrastructure, distributed computing, that, there's no compromise there. You have to have the right ecosystem for you to be able to be technologically advanced and a leader in that space. >> But that's kind of table stakes, is what you're saying. >> Stakes. >> So this notion of the autonomous enterprise, help me here. 'Cause I get kind of autonomous and automation coming into IT, IT ops. I'm interested in how you see customers taking that beyond the technology organization into the enterprise. >> Yeah, this is such a great question. This is what I've been talking about all morning. I think when AI is a technology problem, the company is at a loss. AI has to be a business problem. AI has to inform the business strategy. When companies, the successful companies that have done, so, 90% of our investments are going towards data, we know that, and most of it going towards AI. There's data out there about this. And so, we look at, what are these 90% of the companies' investments, where are these going, and who is doing this right, and who is not doing this right? One of the things we are seeing as results is that the companies that are doing it right have brought data into their business strategy. They've changed their business model. So it's not making a better taxi, but coming up with Uber. So it's not like saying, "Okay, I'm going to be "the drug manufacturing company, "I'm going to put drugs out there in the market," versus, "I'm going to do connected health." And so, how does data serve the business model of being connected health, rather than being a drug company selling drugs to my customers? It's a completely different way of looking at it. And so now, AI's informing drug discovery. AI is not helping you just put more drugs to the market. Rather, it's helping you come up with new drugs that will help the process of connected care. >> There's a lot of discussion in the press about the ethics of AI, and how far should we take AI, and how far can we take it from a technology standpoint, (laughs) long road map, there. But how far should we take it? Do you feel as though public policy will take care of that, a lot of that narrative is just kind of journalists looking for the negative story? Will that sort itself out? How much time do you spend with your customers talking about that, and what's Oracle's role there? Facebook says, "Hey, the government should figure this out." What's your sort of point of view on that? >> I think everybody has a role, it's a joint role, and none of us can give up our responsibilities. As data scientists, we have heavy responsibility in this area, and we have heavy responsibility to advise the clients on this area also. The data we come from, the past, has to change. That is inherently biased. And we tend to put data science on biased data with a one-dimensional view of the data. So we have to start looking at multiple dimensions of the data. We've got to start examining, I call it irresponsible AI, when you just simply take one variable, we'll start to do machine learning with that, 'cause that's not right. You have to examine the data. You've got to understand how much bias is in the data. Are you training a machine learning model with the bias? Is there diversity in the models? Is there diversity in the data? These are conversations we need to have. And we absolutely need policy around this, because unless our lawmakers start to understand that we need the source of the data to change, and if we look at the source of the data, and the source of the data is inherently biased or the source of the data has only a single representation, we're never going to change that downstream. AI's not going to help us there. So that has to change upstream. That's where the policy makers come into play, the lawmakers come into play. But at the same time, as we're building models, I think we have a responsibility to say, "Can we triangulate? "Can we build with multiple models? "Can we look at the results of these models? "How are these features ranked? "Are they ranked based on biases, sex, age, PII information? "Are we taking the PII information out? "Are we really looking at one variable?" Somebody failed to pay their bill, but they just failed to pay their bill because they were late, versus that they don't have a bank account and we classify them as poor on having no bank account, you know what I mean? So all this becomes part of responsible AI. >> But humans are inherently biased, and so, if humans are building algorithms-- >> That's right, that's right. >> There is the bias. >> So you're saying that through iteration, we can stamp out the bias? Is that realistic? >> We can stamp out the bias, or we can confirm the bias. >> Or at least make it transparent. >> Make it transparent. So I think that even if we can have the trust to be able to have the discussion on, "Is this data "the right data that we are doing the analysis on?" and start the conversation there, we start to see the change. >> Well, wait, so we could make it transparent, then I'm thinking, a lot of AI is black box. Is that a problem? Is the black box syndrome an issue, or are we, how would we deal with it? >> Actually, AI is not a black box. We, in Oracle, we are building our data science platform with an explicit feature called explainability of the model, on how the model came up with the features, what features it picked. We can rearrange the features that the model picked. So I think explainability is very important for ordinary people to trust AI. Because we can't trust AI. Even data scientists can't trust AI, to a large extent. So for us to get to that level where we can really trust what AI's picking, in terms of a model, we need to have explainability. And I think a lot of the companies right now are starting to make that as part of their platform. >> So that's your promise to clients, is that your AI will not be a black box. >> Absolutely, absolutely. >> 'Cause that's not everybody's promise. >> Yes. >> I mean, there's a lot of black box in AI, as you well know. >> Yes, yes, there is. If you go to open source and you start downloading, you'll get a lot of black box. The other advantage to open source is sometimes you can just modify the black box. They can give you access and you can modify the black box. But if you get companies that have released to open source, it's somewhat of a black box, so you have to figure out the balance between. You don't really have to worry too much about the black box if you can see that the model has done a pretty good job as compared to other models. If I triangulate the results of the algorithm, and the triangulation turns out to be reasonable, the accuracy and the r values and the matrixes show reasonable results, then I don't really have to worry if one model is too biased compared to another model. But I worry if there's only one dimension to it. >> Mm-hm, well, ultimately, to much of the data scientists' dismay, somebody on the business side is going to ask about causality. >> That's right. >> "Well, this is what "the model says, why is it saying that?" >> Yeah, right. >> Yeah. >> And, ethical reasons aside, you're going to want to understand why the predictions are what they are, and certainly, as you go in to examine those things, as you look at the factors that are causing the predictions and the outcomes, I think any sort of business should be asking those responsibility questions of everything they do, AI included, for sure. >> So, we're entering a new era, we kind of all agree on that. So I just want to throw a few questions out and have a little fun here, so feel free to answer in any order. So when do you think machines will be able to make better diagnoses than doctors? >> I think they already are making better diagnoses. I mean, there's so much, like, I found out recently that most of the very complicated cancer surgeries are done by machines, doctors just standing by and making sure that the machines are doing it well. And so, I think the machines are taking over in some aspects, I wouldn't say all aspects. And then there's the bedside manners, where you (laughs) really need the human doctor, and you need the comfort of talking to the doctor. >> Smiley face, please! (Janet laughs) >> That's advanced AI, to give it a better bedside manner. >> Okay, when do you think that driving and owning your own vehicle is going to be the exception rather than the rule? >> That, I think, is so far ahead, it's going to be very, very near future, because if you've ever driven in an autonomous car, you'll find that after your initial reservations, you're going to feel a lot more safer in an autonomous car. Because it's got a vision that humans don't. It's got a communication mechanism that humans don't. It's talking to all the fleets of cars. >> It's got a richer sense of data. >> It's got a richer sense of data, it's got a richer sense of vision, it's got a richer sense of ability to (snaps) react when a kid jumps in front of the car. Where a human will be terrified and not able to make quick decisions, the car can. But at the same time, we're going to have some startup problems. We're going to see AI misfire in certain areas, and insurance companies are gearing themselves up for that, 'cause that's just, but the data's showing us that we will have tremendously decreased death rates. That's a pretty good start to have AI driving our cars. >> You're a believer, well, and you're right, there's going to be some startup issues, because this car, the vehicle has to decide, "Do I kill that person who jumped in front of me, "or do I kill the driver?" Not kill, I mean, that's overstating-- >> Yeah. >> But those are some of the startup things, and there will be others. >> And humans, you don't question the judgment system for that. >> Yes. >> There's no-- >> Dave: Right, they're yelling at humans. >> Person that developed, right. It's treated as a one-off. But I think if you look back five years, where were we? You figure, the pace of innovation and the speed and the gaps that we're closing now, where are we going to be in five years? >> Yeah. >> You have to figure it's, I have an eight-year-old son, and I question if he's ever going to drive a car. >> Yeah. >> Yeah. >> How about retail? Do you think retail stores largely will disappear? >> Oh, I think retail, there will be a customer service element to retail, but it will evolve from where it's at in a very, very high-stakes rate, because now, with RFID, you know who's, we used to be invisible as we walked, we still are invisible as you walk into a retail store, even if you spend a lot of money in retail. And now, with buying patterns and knowing who the customer is, and your profile is out there on the Web, just getting a sense of who this person is, what their intent is walking into the store, and doing responsible AI, bringing value to that intent, not irresponsibly, that will gain the trust, and as people gain the trust. And then RFIDs, you're in the location, you're nearby, you'd normally buy the suit, the suit's on sale, bring it all together. So I think there's a lot of connective tissue work that needs to happen, but that's all coming together. >> Yeah, it's about the value-add and what the proposition to the customer is. If it's simply there as a place where you go and pick out something you already know what you're going to get, that store doesn't add value, but if there's something in the human expertise, or in the shared, felt sudden experience of being in the store, that's where you'll see retailers differentiate themselves. >> I like to shop still. (laughs) >> Yeah, yeah. >> You mentioned Apple Pay before. Well, you think traditional banks will lose control of the payment systems? >> They're already losing control of payment systems. If you look at, there was no reason for the banks to create Siri-like assistants. They're all over right now. And we started with Alexa first. So you can see the banks are trying to be a lot more customized, customer service, trying to be personalized, trying to really make you connect to them in a way that you have not connected to the bank before. The way that you connected to the bank is you knew the person at the bank for 20 years, or since when you had your first bank account. That's how you connected with the banks. And then you go to a different branch, and then, all of a sudden, you're invisible. Nobody knows you, nobody knows that you were 20 years with the bank. That's changing. They're keeping track of which location you're going to, and trying to be a more personalized. So I think AI is a forcing function, in some ways, to provide more value, if anything. >> Well, we're definitely entering a new era, the age of AI, the autonomous enterprise. Folks, thanks very much for a great segment, really appreciate it. >> Yeah, our pleasure, thank you for having us. >> Thank you for having us. >> You're welcome, all right, and thank you. And keep it right there, we'll be right back with our next guest right after this short break. You're watching theCUBE's coverage of the rebirth of Oracle Consulting. We'll be right back. (upbeat electronic music)

(lively pop music) >> Live from Mountain View, California. It's the Cube covering DevNet Create 2019. Brought to you by Cisco. >> Okay welcome back everyone, we're here at day two coverage live of coverage at Mountain View, Cube coverage of Cisco's DevNet Create. I'm John Furrier, your host, where all the action is in the creation side of two communities, DevNet, Cisco developers and then the open cloud native world entrepreneurship coming together to create products. Our next guest is Nik Kalyani, co-founder of WhenHub and TryCrypto. He's a builder, he's a creator, he's an entrepreneur. Welcome to The Cube, thanks for coming on >> John, thanks for having me. >> You just gave a long talk so I'll let you breathe a little bit. You're an entrepreneur, you're an inventor, you see things early. You got a lot of your hands on lots of good stuff here. This is the perfect place for you to be giving talks and hanging out. >> Absolutely I love the fact that people are here to learn. They're here to find out about the new innovative things that they can experience hands-on. I just gave a workshop on smart contracts, on the blockchain and I loved the questions I got and the energy that's there. >> What sort of questions were you getting? What was the interest? Where are people going at it? Because networking's a supply chain problem you can almost imagine applying blockchain to networking constructs. >> Yeah absolutely, you know blockchain is one of those technologies that is misunderstood quite a bit and some of the questions I got really helped me, help reinforce that. Ultimately, what I was trying to do is make sure that people understand that blockchain is not a solution for everything. There are certain things where there are scenarios where there are multiple un-trusted parties where blockchain is great, but otherwise it's just a slow database. So you want to make sure that you use it in the right scenarios and supply chain is a very common example where it's used, especially private blockchains. >> If latency's not a concern blockchain might be a solution if other things line up. Great point, I'm glad you brought that up. I want to just ask you because your profile as a person you're a visionary, you see things early. The part of the show here that's interesting is it's not like there's this research kind of thinking, although researchers tends to think about the waves coming. It's about what's here and now and what's coming but it's also making things real and creating. So a lot of the conversations are fun, exploratory, discovery orientated but also there's a lot of reality kind of grounded in it. You know entrepreneurs make some mistakes if you're too early, you're misunderstood for a long time. It's got to be a little bit early at the right time, timing's everything. Talk about the dynamic of timing and building and creating with big waves that are coming. You got cloud, you got blockchain, you got AI, you got machine learning. Talk about this dynamic. >> Absolutely, yeah so timing is so important, especially when you have start-ups right? You could have the greatest technology and maybe the market's not ready for it and so yeah it fails. My first start up was like that. I created something that the market was not ready for but fortunately the stuff I'm working on the market is ready for. So I think one of the things that developers, engineers can do is really look at how not necessarily how a technology is being marketed but what the adoption rate is. If there are more people jumping on it, and a good way to look at that is to look at GitHub and see how many people are creating samples, boilerplates, how many people are writing blog posts et cetera. That I think is a better indicator of whether a technology is ready for prime time or if it's just all vaporware. >> Tell about what you're working on now you're working on some very interesting projects. Where are they? What's the status, size of the team, collaborative open source. What's going on? >> So I have two start-ups I'm working on. the first one is called WhenHub. So we have a product called Interface that allows anyone to be an expert on any topic, and promote themselves through the platform. And allows anyone who's looking for expertise on any topic to find them and then pay for them and do a video call, get their questions answered and the whole transaction is handled via blockchain with either our cryptocurrency or you can use Apple Pay or Google Pay. So we launched a few months ago, we have about 75,000 users, it's growing very fast. We are just at the point right now where we are trying to scale-up. Our crypto token is called WHEN token. It's listed on five different exchanges. So that's one thing. While building that product one thing became very clear to me. Mainstream users have a very challenging time with using anything blockchain or cryptocurrency related. And it's through no fault of theirs, the ecosystem has been created for developers by developers and the tools lack empathy for the users. And that lead me to create an open source project called TryCrypto. The mission is to create free open source content and tools to make blockchain and cryptocurrency more accessible to users. >> To mainstream not the killer dorks and the guys coding. >> Yeah we want it to be like non-technical folks >> Is it the wallet that's the problem or is it just overall too techy? >> You know what John, the very word wallet is the problem. (John laughs) Because it gives this idea that there's something within it. As we were talking earlier, you know about blockchain, there's nothing in a wallet. It's just a placeholder for all of your addresses, right? So in fact, I'm trying to solve that problem with a new tool I've created called Photoblock, where I use a photo and emoji's to replace that. Yes, wallets are problems. The fact that it requires you to have all these parts in place before you can do anything useful, that's a big problem also. People really need to step back and look at the user experience and say what are the friction points and how can we eliminate them and that needs to happen before blockchain and cryptocurrency can have mass adoption. >> Talk about the choice of smart contract language used. Ethereum which was the hottest development oriented the most traction. A lot of ICOs kind of watered that down, it's still under 300. Other ones are emerging, NEO, EO, a bunch of other ones. It seems to be kind of like a NASCAR race, one's in the lead, someone's coming up. How do you look at that marketplace as other developers start to kick the tires? As people start building these real-world apps is that important to have a selector? Does it matter? What's your thoughts on selection? >> That's a great question. I think going back to what I said about how to evaluate a technology. You can see that Ethereum is still continues to be the leader, by far. So while EO and other blockchains have what appears to be a lot of momentum, if you dig down below the surface you don't find as much. So I continue to remain a big fan of Ethereum. Which doesn't mean I don't care for the other blockchains but I find that right now Serenity and Ethereum are a good way to move forward. I think EO is also a good platform to build on but I think their developing tools need to reach some level of maturity. On Ethereum, the folks that have created the truffle stack, the truffle and ganache package, have done a great service for developers because they make them so simple and easy. Something like that needs to evolve. >> Yeah and your point earlier I think it's important to know for the developers out there don't confuse the protocol and the token selection on smart contracts with blockchain. Again, you don't have to anything on blockchain 'cause it's a slow database. You're doing smart contracts which doesn't really require a lot of overhead. I mean it's a contract, it does. You want to have it reliable, but you're not doing zillions of contracts per second. The IOPs are not that high. >> Yeah, actually smart contracts is also a very misunderstood term. In fact, someone asked me is it legal contracts or medical contracts, what is it? A smart contract is really just an application. A programming code that runs on the virtual machines on blockchain. They call it a contract because once it's out there it's immutable. Which means the rules are defined, known and fixed and can't be changed. So when you create a smart contract, really what you're doing is handling a very small amount of data that you want to persist forever that runs with some rules. >> And in a decentralized world, as we call it in our community, it's a digital handshake. You agreed that we would do this, there it is, it's un-hackable. What are the cool things you're working on? What else you got? Opensource project's awesome. You got a lot going on. Life's good. >> Life is good. As I mentioned, Photoblock is the thing that I'm really excited about. Another app that we are building is called Public Record. The problem we are solving there is that in areas where there is strife, or maybe there's dictators et cetera, sometimes when you have people who have photos of some crime occurring or some event occurring, they are reluctant to share it because it could be traced back and have adverse consequences. With Public Record we are building a smart contract driven blockchain app. Where you can just take a photo and it will push that photo on to IPFS. Which stands for the InterPlanetary File System, which is a decentralized file system. It will anonymize the photo. It will strip all the stuff that your camera puts on there like GPS, the camera model et cetera. It'll manipulate that photo and it will then put a hash of that on the blockchain and make it available by location. So you can go to any location look at all the photos that people have taken there that are completely anonymous and impossible to track back to the >> And what about tampering proof? You have origination data, you strip out the real origination data, that's really important for some of these countries where people get killed for sharing or trying to get the backdoor out of the country for political revolution or just simply I don't want anybody to know. How about tamper proof? >> It is, it's on IPFS, which is immutable file system. What we also do is we manipulate the colors and tones of the photo a little bit so it's impossible to even use AI to go back and reverse engineer and figure out who created the photo. The location, the time and the actual content of the photo is not tampered. So Public Record will do that. >> Just a little quick Q and A on your company. Did you do an ICO, did you finance it yourself? >> With WhenHub we did do an ICO, but it was at a time when the market was at its bare things so our ICO was moderately successful. In addition to the ICO funds, we are primarily funded by one of my co-founders, Scott Adams, the creator of the Dilbert comic strip. We are doing quite well. >> He's a cool guy to hang out with, huh? >> He is. >> Never a dull moment? >> Never a dull moment, I learn quite a bit. >> Congratulations. How do people find out how to hang out with you? You got some good things going on here. Where do you hang out? What do you do for fun? What events do you go to? What's going on with you? >> I'm on Twitter quite a bit. >> Say your Twitter handle. >> It's @techbubble. I'm there. I like to blog. on TryCrypto and also my own personal blog. I go to meet-up events here in Silicon Valley and I do make an effort to speak at least five to six conferences each year. >> Aim it forward. >> Yep. >> A lot more action going on in crypto and token economics not just from an ICO standpoint always been some negative scams out there and global fraud, but generally, blockchain and token economics is real and getting more traction and soon I think it will be clearer. Your thoughts on that, if you could share your perspective in terms of the opportunities around those two areas. >> Like any other new and exciting technology goes through the hype cycle, they've gone through that now. I think there's really two types of people in this ecosystem. The ones that are focused on the cryptocurrency and the pricing around it et cetera. But I'd really like to separate that from the blockchain aspect of it. Blockchain is a very real technology, it's a really different technology that the world has never seen before. Yes, it's very true that not everything is a good candidate for the blockchain. But there are many, many scenarios where there are multiple un-trusted parties that are excellent for blockchain. I think what needs to happen is persons in leadership position need to really evaluate: what are the scenarios where there are un-trusted entities involved? And limit their blockchain involvement, test pilots, all of that they're more likely to see more success. Versus just throwing blockchain into it, replace the database, 'cause that's guaranteed to be a fail. >> Nik, great to have you on. I totally agree with you. The team here we were in Puerto Rico, we've been in the Bahamas, we've been Toronto we've been to all the blockchain events. Consensus is coming up in New York. We might be there, May 14th. Patrick, getting ready to head down to New York. Maybe go down there. Great to have your perspective. Great to see the blockchain conversation coming in here as the emerging tech and the creation here at DevNet Create continues. Thanks for coming out. >> Thank you so much. I appreciate you having me here. >> More Cube coverage here coming live here at Mountain View after this short break. (pop music plays)

(enlightening music) >> Hello everyone, I'm John Furrier here at theCUBE headquarters in Palo Alto, California, for a special CUBE Conversation. I'm the host of theCUBE here with my special guest, Monica Kumar, vice president of Oracle Cloud platform. Monica, thanks for joining me today. >> Thank you so much for having me. >> So Oracle Cloud has got some great stuff goin' on, one of the things I'm most intrigued about, I've heard a lot about, is this autonomous database. I have a lot of questions, want to dig into it and really unpack that, so first take a minute to explain, what is the autonomous database? >> You know, before I do that, John, can I ask you a question? >> Sure! >> You use a smartphone, right? >> Yep. >> Do you know what happens every minute of when we use a smartphone and use the internet, how much data gets generated? >> No. >> Okay, I'm going to tell you. >> Alright, good. >> 16 million text messages happen every single minute, about four million Google searches, we're talking four million YouTube videos watched, about a million Facebook pages are open, and half a million Tweets. Now think about the impact of all this data in just one minute. Somebody, somewhere, is finding this data useful, and can actually extract some value out of it. Now, you might have heard this also, that in the last two years, the world's 90 percent of data has actually been created, and it's doubling every two years. >> So my kid's LTE bill, that's why, they're watching Netflix, that's why I'm paying all this extra bandwidth. (laughs) This is a real world. I mean, I can imagine my iPhone, I got multiple apps on there, lot of power being used, but that's just one piece, like when I'm buying with Apple Pay, or I'm doing things around, there's a lot of mobility involved, what's the value of all this? >> Well see, there's also a lot of devices, I mean we talk about IoT. By the year 2021, or in about the next five years, there'll be 50 billion devices that will be collecting data, analyzing data, sharing data. So what we're talking about is the sheer volume of the data that's being generated. And ultimately, every organization is trying to figure out how to extract insights from this data, how to make their businesses run better because of those insights. Whether create new revenue streams, maybe optimize for efficiency, deliver better customer services. So that is the problem we are dealing with today is, how do we get more value out of that data? >> So how does it all work, I mean autonomous driving, you see cars around, Uber's been trying to do it, other people have fleets, cars all over the place. Autonomous database, I mean it sounds like it's self-driving, which implies that's what cloud is all about, automation. How does the check work, what's goin' on under the hood? >> Yeah so let me explain to you, I mean this is where Oracle comes in. We've been in the data and information business for over four decades. This is what we've done. We've actually been solving the hard problem for our customers when it comes to data management, and using data. And now with this new whole deluge of more and more data, who better than Oracle to solve this problem? And one of the more important ways in which we can solve this problem is by automation, is by the use of machine learning. So that's where we're moving as a company, is you're moving to adopt and embed more and more machine learning across our entire cloud portfolio. And one of the biggest things we're doing is what you're talking about, autonomous database, which is exactly that, it's combining machine learning with the decades and decades of the database optimizations that we've been putting out in the industry. It's the power of that combination, which has culminated into what we call autonomous database today. >> Is autonomous database on-premises and Cloud, or both, how does that work? >> Yes, Oracle's always been about choice, so definitely it's both. And I'll explain to you the cloud offering, in fact, you eluded to self-driving cars. It's very similar to that. So there are three core attributes of autonomous database. It's self-driving, self-securing, and self-repairing, and let me explain to you what I mean by each of those. So self-driving is really the database provisioning itself, upgrading itself, patching, tuning, monitoring, backing up, all of the functions that are very manual today, are all done by autonomous database itself, so that's the self-driving part. Self-securing, applying all of the security patches by itself so the user doesn't have to worry about it. And the self-repairing is really focused on maximizing uptime, productivity. So today we offer with autonomous 99.995 percent uptime, which means 2.5 minutes of downtime or less per month, per month, which includes, by the way, both planned and unplanned downtime. So that's what autonomous database is, it's using the power of machine learning to automate all of the manual tasks that a human being is doing, which is really not of high value, which is really very administrative type of work. >> So I can see some of the time things are great for customers, what other benefits do those customers have in terms of having this, obviously automation takes away a lot of, makes free time, but what specific benefits do you guys see coming out of this for customers? >> Yeah, absolutely, I think for businesses it's all about outcome. So there are three major benefits of autonomous. The first one is reducing cost, it's making sure that the administrative times, I'll give you an example, we now with autonomous can cut off the administrative time by 80 percent, the cost of administering a database. So that's real hard savings for the customer, and they can then take that and put into something else that more strategic to them. It's about reducing risk. The risk of breeches, which could cause reputational damage to companies, which could cause, shareholder value loss. So the fact that we are reducing risk with autonomous technology is another big benefit. And the third, and the most important one, is really innovation, the time to innovation, the time to insights, more productivity for the customer. So those three, in my opinion, are the top three benefits >> To organizations. >> Now being agile, having flexibility, the cloud certainly brings that scale out mentality, that server list we hear things like that in the industry, so certainly very relevant, and machine learning makes that automation happen. Love that message. The question I would have for you is okay, in my mind, I'm trying to think, how would I buy this, how would I use it? What are some of the offerings that you guys have, is it turnkey box, is it software, how do you roll this out to customers, how do they consume it? Take us through the offering itself. >> Sure, today we offer autonomous in our cloud in two different offerings. One is autonomous data warehouse, which is purely for analytics, so you can actually create new data warehouses, or data mods to get insights from your data. The second one is transaction processing, it's autonomous transaction processing, which can be used to develop applications, to deploy applications, high-performance workloads, mission-critical workloads in the cloud. So those are the two ways we can do, in fact, we have many customers who are using our technology today in our cloud. But like I said, this is also going to be available in on-premises as well. >> That's awesome. So, when you get into the customer examples, who's using this now? Is it shipping? What's the status of it? I mean this gets a lot of attention, and the press articles are great. We covered it on SiliconANGLE, what are the customer examples? >> Absolutely, so of course it's shipping, and it's the first and only self-driving database in the industry. We have many, many customers for the last few months who are using it. I'll give you a few examples. We have a major Enterprise car rental company who is using it, and they were able to cut down their time to provision databases from two weeks to eight minutes. Now what does that mean? That means they can now roll out projects faster, and improve their customer services and offers they are making to customers. We have another customer who is in the shipping and oil industry, and they've cut down their time to querying complex data sets from 20 minutes to a few seconds. Again, which means they can get access to insights much faster to make decisions. And they've also eliminated downtime from patching because everything is done online, patching is done automatically on the database while it's running online. And then we have another customer who's a managed service provider. They're now able to provision their customers 10 times faster. So that means they can grow their business, they can provision more customers, their current customers can be happier because they are supporting them better and faster. >> What are some of the comments and messages, to kind of go off tangent for a second here but, I mean, they go "Wow, this is amazing"? What's some of the feedback you're getting? What are they saying, what are some the anecdotal comments? Share some color around that. >> Sure, I mean one of the big comments is "Wow! Me, I'm a DB, I thought this was "going to take my job away, but actually, "to the contrary, it's making my job easier." DBAs are now realizing they can actually manage many more databases efficiently in the same time that they were doing before. And secondly, they don't have to be involved in manual drudgery tasks, they can now offload all of that to autonomous database, and they can now focus on more strategic tasks. They can become a partner to the business, they can focus on application life-cycle management, on data security, on data architectures. So that's the one reaction we are getting is like "Wow, I didn't realize how much of my time "I was spending doing maintenance stuff, "which really adds no value to the organization." So customers are seeing a lot of productivity gains. I think the second thing is the speed of innovation. The fact that it would take them three months, six months, to deploy new projects, and now they can do it quickly within a few minutes is actually unbelievable to them. >> This is a real good point, I just want more double-down on that real quick, because one of the things we're seeing is, across all the events we go to, that message of the fear of "Oh my god, "I'm going to lose my job" or "I'm going to be automated away" actually isn't true. If they get re-deployed in other easier jobs, I don't want to say easier, but all the mundane tasks can be automated, that's a good thing. The security thing about the patching and self-updating, that's amazing. But the skill gaps is a huge problem CIOs face is that they need more people. And cloud architects are the number-one demand jobs, so I mean this must be really refreshing to hear that when you say "Hey, you were doing "a DBA job before, or something else, "now you're a cloud architect." Are you seeing the cloud architect role become important, and if so, what are they doing? What's the role of a cloud architect, and how does this fit into that? >> Yeah, I think the way we describe it, I think it's close to cloud architect, but think about it from administering data, or managing databases to actually using databases to mine insights, it's a different mindset. So you're becoming a data professional from a data administrator. So as opposed to having a job of managing a database, that's not important, what's important is you use the database to get insights and make your business smarter. So now we are working with, for example, our DBA stakeholders, which have been our Oracle family for four decades, to help them re-skill, to new ways of thinking, to becoming data professionals, to becoming data architects, and like I said, focusing on things like data life-cycle management, how do you work with application developers, how do you work with lines of businesses when your line of business comes to you and says "Hey, I want a database tag deployed for XYZ", the ability for them to say "Of course, I can give it to you in minutes." as opposed to saying "Oh, you'll have to wait two months." Imagine that. >> Yeah they're helping people, and they're also, more important, they're powerful. >> Right, right. >> Okay, Oracle OpenWorld is happening, and so one of the conversations we're hearing, and certainly this is consistent throughout the industry, the role of security. I put my skeptic hat on like okay Monica, tell me the truth, is it really self-updating the security patches? What about the phishing attacks? There's a real paranoia on the security. Take me through the security, while you guys are comfortable with the security, what's the big message and what's the big feature of why it's so secure? >> Right. But before I do that, let me paint a picture for you. We all know the opportunity that comes with Cloud, it presents huge opportunities to organizations. But with every opportunity, there comes a challenge that needs to be solved. And like you said, security is a big challenge. We are talking about massive scale of security breeches happening in the industry. We are talking about bad guys having access to very sophisticated technologies to wage this war against us, the organizations, to get access to core data. And we are talking about the number of security issues that are happening multiplying and compounding, and I'll give you some data points. There are 3.5 million cyber security jobs that are open in the next couple years. We don't have enough people to fill those jobs, even if we did, we can't keep pace with the amount of security threats and challenges that we need to navigate and address. >> And by the way, that's a data problem by the way, too. >> Back to your data is the central value proposition. >> Exactly, and also the other point I want to give you, which is equally important is of all the breeches that have happened, 85 percent actually had to fix available, and yet it wasn't applied and the breech happened. So again, we are talking about human beings who are very busy >> The human error on the patch side is huge. Spear phishing and also patches are the two number one areas of security. >> Right, but also people are busy. You kind of say "Okay, I'm going to do this later, "I have so many other 10 things to take care of first, "and I'm going to apply this patch later." Now what happens is, that's why we need to throw automation and machine learning at this problem. I don't think we can solve it by throwing just more and more human man-power on it. We need to combine the power of human and machine to tackle this security problem, and that's what we're doing with autonomous database. Not only can we predict a breech before it happens, we can actually fix it before it becomes an issue. And that's what I'm talking about with the whole self-securing notion. That's the power of autonomous database. >> A few Oracle OpenWorlds ago, Larry Ellison said on stage, I'll never forget this, I actually loved the line, other people kind of gave him some heat for it, but he said "Security should always be on. "Off is the exception." Has that view permeated through Oracle? >> Oh, Oracle was built on that view. We have, if you look again at our history, and our customer base, we are supporting the largest and the biggest governments in the world. We support from federal governments, to state governments, to public sector, to every organization who cares deeply about security, and it's not just a government issue, it's every organization has to safeguard the data of their customers. I mean that's the law. Every single organization cares about it. Oracle was built on that, that's the foundation that we are built on. So for us, security is very important, that's the first design principle of our data management, and all of our technology solutions. >> Well you guys are in the middle of all the cloud action, for sure, we're covering you guys, it's great to have you on theCUBE. Monica, thanks for coming and sharing your story. Where can people find out more information on the autonomous database, this awesome new product? >> Well, it's going to be all over oracle.com, so I'd say go there at first and from there you can navigate to a lot of great content on autonomous database. We have customer studies, we have free trials, so you can take us for a spin. It's like driving a self-driving car, it's self-driving database. >> It's a Tesla. >> Yeah, it's like the Tesla of databases, exactly. >> Monica, thanks for coming, I'm John Furrier here for CUBE Conversation, we are in Palo Alto at our headquarters, I'm John Furrier with theCUBE, thanks for watching. (enlightening music)

>> Announcer: Live, from Las Vegas, it's the Cube. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to ServiceNow Knowledge18 the Cube's live coverage. We are the Cube, the leader in live tech coverage. I'm your host, Rebecca Knight, along with my co-host, Dave Vellante. We're joined by Jason Scott-Taggart. He is the head of Business Technology Support at WorldPay. He's in direct from London. So welcome, Jason, to the show. >> Thank you, it's good to be here. >> So first lay the scene for our viewers. Tell us a little bit about what WorldPay is and what you do. >> So WorldPay is the largest payments company in the world. So it's a hidden gem that not a lot of people know about. So recently we merged with Vantiv, which is huge in domestic US. And WorldPay is very large in the rest of the world. So a marriage made in heaven. We're what's technically known as a merchant acquirer, which is a fancy way of saying that we take credit card payments. And we do that for both online or in the store, putting your card in a machine. So billions of transactions a year. >> And what's your relationship with the banking infrastructure around the world? How does that all work? >> Sure, so the banks issue credit cards and your relationship as an individual is with the bank. So you pay your bills to the bank and have that transaction. We look after the merchants. So we're the ones that do the services for the, we quaintly call the merchants still, so for the shops and the traders, we have that relationship. And basically the transactions then go between the two. So individuals to the bank, bank to us, us to the merchants. And we just aggregate that because if you're, even if you're a large company like Costco or Google, you don't want to have to have a relationship with every one of the credit cards let alone every one of the banks. So we aggregate that. >> So tell us about your ServiceNow journey. When did you start using the platform? >> So ServiceNow, we're on our third year now I think with ServiceNow. And it's been explosive. It was a quite seamless transition. We were really pleased with the previous platform we were on, how we moved over. And we slowly added to it. We slowly turned on other modules, other functionality. And it's just become ingrained in our day-to-day IT operations. >> It was simpler because you had had other processes in place? You didn't have to rip and replace those processes and skill sets? >> We took it as an opportunity to do best-of-breed. So there were some things that we carried over. But we took the opportunity for a clean start as well. Even before a lot of the buzz here is back to basics and staying out of the box, and we did that for a lot of it, and that was quite refreshing, and it was quite cathartic in a way that we could make that change. But then there were some bits that weren't really well and were ingrained in our business process so we had to carry those over. But we found it easy to do a mixture of both. >> And you carried those over in the form of custom modifications? >> Some, not a lot. We tried to stay as much out of the box as possible. >> So how does that having some custom mods affect your ability to go to subsequent releases? >> I think it's fair to say that ServiceNow is one of the easier platforms to upgrade. I probably shouldn't say that. They should be doing more work to make it easier for me. (laughing) >> Dave: Do a better job of upgrades. >> But compared to some other platforms we have even Cloud ones, it's not the hardest. It's not the worst. However, we've tried to stay close to the box to make it even easier. We want to stay N plus one no more, and when you're coming out with a major upgrade twice a year, that means we've got to factor that into our road map. But we do. We make sure that we try and stay up to date. >> So where are you now? You're in, are you? >> We're in Jakarta. >> Jakarta, okay. >> Yeah. >> So you're pretty current. >> Yeah, only just though, so. >> Okay, but we heard a lot about Madrid today. >> Yeah. >> Which is Q119. And a lot about DevOps. So talk about, it was very good that the DevOps 101 that Pat Casey gave. I'll give my version of DevOps 101 if I can. (laughs) Back in the day, the developers would write some code, maybe on their laptop or whatever, they'd throw it over the fence to the ops guys, and say, here, deploy this. And the ops guys would go to deploy, and they say, ah, this thing doesn't meet up to our enterprise standards. It doesn't have the security and the governance. So they go in and they hack the code, invariably break it, and then they go to deploy it, and it doesn't work. And they go back to the developers and your code doesn't work. And the developers say, well it worked when I gave it to you. And you get this back and forth, back and forth, back and forth. So DevOps consolidates that into a single programming environment. >> That's good, I appreciate this. >> Infrastructure is code. And so that's my version. Pat Casey gave a much more eloquent description, but what is DevOps to you guys and how are you applying it? >> So we've got two major competitive drivers in the market. One is scale. So we're the largest payments company in the world so we need to leverage that. We can operate in most countries of the world, take most currencies, so that's a scale thing that we try and leverage. Scale tends to lend itself more to waterfall kind of traditional projects. (laughs) The other competitive pressure that we face is from small fintech startups that are nibbling away at our ankles for niche products and new services or disrupting the whole way we do payments. Will there be banks tomorrow? Who knows. The whole way could be disrupted. That innovation lends itself more to a DevOps kind of, or at least an agile form of development. You want rapid prototyping, trying things, seeing what works. So one of the things we've been struggling with at WorldPay is how can we foster more of the DevOps whilst not endangering the traditional kind of waterfall that we need to do. The vast majority of our development is done agile, but hardly any of it is DevOps. And a lot of people confuse agile for being DevOps. And agile is just the dev part of it, it isn't the ops bit of it. So where's the ops in DevOps? What we did, you just outlined classic reasons why people might want to do that, and having a single team owning something all the way through the life cycle. What we've done is we've tried to separate out different layers and kinds of services to allow that to happen. So with scale, you have to have one level one. You have to have a front door for IT that everybody comes to. Whether you're a squidgy resource, a human needing to phone someone or your tin and wires, there's got a problem and alerting an event. So you have one front door. What you need to do is you need to try and have a high first-time fix. That's cheapest and that's most best experience for the end user. So we aim for 60, 70% of issues to just be killed at that front door. That's the aim. After that, we then put a lot of work and effort to make sure that we had a business-oriented, service-oriented CMDB. So we worked with the lines of business to describe WorldPay and what we do in a way that they understood and the IT understood, and then we translated that into a service management language in the CMDB. Once you go past that level one, the level one know they can't fix it, they know what's broken, or they're pretty certain what's broken, they will put it into the right service line. That level two is still run only. So we split, the dev and the run at that level two. You're aiming for 25% of things to stop there. That leaves only about 5% of things that would ever go wrong needing to go to a third line. That third line we refer to as technical services. So you've got business services in the middle of that level two, that the business would recognize and they consume or our merchants would. The technical services at the third line are the components. They're the building blocks that we use to make those business services. And those are where we start doing the DevOps. Another word for it is microservices. So microservices, we have components, sensors of excellence, in both infrastructure, so a virtualized platform, or applications. So a fraud module or a billing module, or a authorization module. And those teams, because they're only getting 5% of things coming through to them that are wrong, they can cope with being small teams that do both the dev and the ops. And that makes it feasible, and we're fostering that. And we're starting to get live services that are being supplied in that DevOps manner, and that means that that can grow as it succeeds or fail as it doesn't, and it's not endangering the huge machine that is the rest of the organization. >> So the huge machine, the core piece of your systems, you still apply waterfall, is that right? >> Jason: Yes. >> And then in the new stuff where you don't mind breaking things, you're applying agile and DevOps. >> Exactly. And that's what we're seeing is that that then what succeeds and what the ways of working or the particular needs that that microservices is addressing, if they're successful it feeds it, awards it, and they do more. So the teams that are going live with some of these microservices, if they put enough effort into making it resilient, doing the non-functional as well as the functional requirements, which is a DevOps thing as well, so you make something and you get it right first time, so it's not breaking all the time, they can then have spare cycles to go and do other sprints where they're building the next thing. And what we hope to see over time is that we will have a larger and larger proportion of the components that make those business services being supplied in the DevOps way. And that is also complementary with going to Cloud services 'cause they're just other building blocks. They're just components that you use to put together something. >> You saw Pat Casey and C. J. Desai, they showed a little leg today on Madrid. They basically developed a DevOps capability for their own purposes and they're going to release it in Madrid. The problem they're trying to solve if I understood it was you've got 500 DevOps tools out there and there's complexity, did that resonate with you? Is that something you'll adopt? Or are you comfortable with your DevOps tools? >> No we're keen and eager to adopt. Well, I'm an IT ops guy by trade. That's what I've been doing for the last 20, 30 years, but I'm not afraid of DevOps. I love DevOps. DevOps means faster delivery with more control. It's automated ITIL. And what the ServiceNow road map is giving me is a way that I can continue to be the air traffic control for IT. I want people to come to me and my team and say, where are we at? What's moving where? And if we get the hooks into ServiceNow into all of those DevOps tools, the names are up there, the Jenkins, the Chef, the Puppets, if we get the hooks in, then it expands more of the PMO work that we almost do as well. So instead of talking about just a single change ticket or a release that's happening here, we can go, that train in the safe framework or this, that sprint over there, they've got to this point. They're in testing. They're about to release this. Actually I can tell you the features that they're proposing will come with this. Because that's hooked in. So that's the dream. That's where we want to get. Because we want to facilitate more of this happening within our development community. >> So from a legacy talent standpoint, are you more DevOps or are you OpsDev? (laughs) >> Rebecca: Oh, I like that. >> Me personally I'm OpsDev. >> Well right, but I mean for your organization was it kind of retraining the ops guys to think more like devs or was it kind of jamming the ops piece into-- >> We've got challenged with both. And the real success that we've had so far has mainly been greenfield. We've set up teams from scratch with the purpose of testing out DevOps as a theory. And it's worked brilliantly. Now though, the bigger struggle is how do you get existing teams? We've got hundreds of developers in our own squad, so working on agile, but they do pure dev. They build it and they hand it over and then they're off, they're onto the next thing. How do we mix those teams? How do you get multi-disciplinary teams that have both the operational knowledge as well as the development? And that's a cultural thing as well as the tooling. Tooling helps. If you get nice tooling that makes it easier for them to operate in a particular way, that's a big important thing, but it's only half the battle. You've got to get people thinking in a slightly different way. And that's true of the ops people have got to think more of the life cycle. How do they feed back what's working and what's not into the next development cycle. And the development people have got to think about what happens once they let it go. And they've got skin in the game now. It's going to come back and bite them. If they didn't do it well, if they didn't put the dashboards for the support people to see how well it's working, then the support people are going to be banging on their door to get it. So it's a cultural thing as well. >> It's a cultural thing. >> So I'm going to ask you a business question. You referred a little bit to disruption before. You talked about banks and the future of banks. Do you think, and you're very tied into the banks, obviously, do you think, and I wonder if this is a discussion inside the organization that banks, traditional banks will lose control of today's payment systems? >> Well, arguably they're not fully in control of it today anyway. (laughs) And so that's not to mean that they're not in control of what they are to do, but they don't own the payment process end-to-end. >> But they own the consumer. >> They own the consumer relationship, yeah. And that's going to be disrupted in the same way the way that we take payments at the other end of the life cycle is disrupted as well. Contactless, block chain, these kind of things mean that it's not going to be the same. However, you're not going to get rid of large organizations overnight. Because what is also increasing day-by-day, is regulation, security requirements. You want to know that your card's going to be safe. You don't want, if you're going to use Apple Pay, or a new contactless technology, you're only going to do that if you know there's no danger of you losing money by doing it. To have that certainty and to meet the regulators' requirements you need organizations like WorldPay looking after the merchants' interests, you need organizations like banks looking after the individual's interests. So I think, unfortunately, it's not as sexy an answer, but I'm afraid that they're not going to disappear overnight. They're adding valuable service. >> A lot of barriers to entry to those Fintech startups that are nibbling at your ankle. >> However though, it's changed dramatically in the last five years, 10 years, so what on earth it's going to look like in the next five or 10 years, bringing it back, that's why I think innovation is so important. We need to be trying to stay ahead of the curve. We need to meet the needs of our merchants so that they can get as many transactions as possible successfully. And we need to do that at the lowest cost possible. So that's all about innovation. Innovation is hard to do top-down. You've got to find ways of fostering it bottom-up. We have have great leadership top-down. This is where we're going. But actually the way that we're going to get there is down to the troops. It's down to the people on the coal face, so. >> When did you buy your first Bitcoin? >> My first Bitcoin? I bought Bitcoin about four years ago. >> Awesome. >> So yeah, I've done all right. It's paid for a holiday. >> There you go. (laughing) That's good for you. That's great. >> Well, Jason, thanks so much for coming on the show. >> Jason: Thank you. >> It's great talking to you. I'm Rebecca Knight for Dave Vellante. We will have more from ServiceNow Knowledge18 just after this. (upbeat music)

>> Announcer: Live from the Wynn hotel in Las Vegas, it's theCUBE covering Magento Imagine 2018. Brought to you by Magento. (music fades out) >> Hello everyone welcome back we are here, broadcasting here at the Wynn in Las Vegas for the Magento event here, theCUBE with exclusive coverage 2018, Imagine 2018. And I'm here with John Stockton, who is the Vice President of Product Management at Magento. Tell me about the new product news really modernizing the e-commerce tag and enabling digital growth. Great to have you. Thanks for coming on. >> Great! Thanks for being here. >> So, you guys have a digital experience culture here at the company but one of the things that's interesting is the modern stack of e-commerce needs an upgrade. >> John S.: Right >> It's been talked about for years. You guys are doing that, you've got thousands and thousands of customers and partners you've got product news here. >> John S.: Yep. >> Let's dig into the news, what do you guys have, what are you refreshing, what are you bringing to the table? >> Well it's a really exciting time here to be at Magento. We are announcing a number of big initiatives here at the conference. The first is around our superior shopping experience goal, our goal is to continue to support an evolving consumer culture where more and more people are doing things on mobile devices, more and more people are doing things in store. >> We've been working very closely with Google on their progressive web apps initiative, and we'll be announcing here our PWA developers studio is going to be an early adopter program and generally available at the end of the year. That's going to enable Magento merchants, and our partners, and our ecosystem, to be able to create really cool progressive web apps. Progressive web apps are going to revolutionize the way we experience digital commerce on mobile devices, they're much more performant, much faster. They're going to be the way of the future and I don't think any merchant in the world can afford to ignore them. Our PWA dev studio is going to make it easy for merchants to create those apps, and that's really exciting. >> That's the first big news. >> John S.: That's the first big news. >> Let's dig into that, I know you got two more I want to get to but, this is kind of important. We've been hearing about mobile first for years. >> John S.: Right. >> Certainly Google has put the screws on search results, >> John S.: Absolutely. >> response time on mobile. What's the impact to customers on this news, what does it give them? >> Yeah, for a lot of our customers more than 50% of their transactions today are coming from mobile so it's just a trend that they can't ignore at all. What happens when you take a native app in mobile today is, you might be able to do a bit of work with responsive design but the performance expectations the consumers have for a page loading instantaneously, for no delays in scrolling around, for checkout. Increasingly things like Apple Pay and Google Pay, the ability to just do a facial recognition and actually check-out and pay for something on a phone. That's what consumers are going to expect in the future, and PWA is really the only way you're going to be able to meet those expectations. >> That makes them have to take a web response design, >> John S.: Right. >> and make it feel like a native app. >> John S.: Yes. >> Both performance, and experience. >> John S.: (talking over John F.) Very high performance and very high integration with the actual phone itself. >> Alright so the next announcement is what? >> The next big this is on our Omnichannel initiative we want to enable our merchants to be able to sell effectively in any channel. The big news there is we are going to be releasing a Amazon sales channels module for Magento commerce that enables the Magento merchant to push their catalog out to the Amazon marketplace, do things like dynamic competitive pricing, and then track all that transaction data as their products are sold on Amazon. So from directly within Magento they can manage both channels, and see all their results all in one place. >> So this is kind of interesting. Amazon obviously is Amazon, we know what's going on with those guys. So what's the improvement, I mean obviously you can publish-- >> John S.: Right. >> Amazon marketplace. What's the innovation, where's the new updates, you mention pricing, the relationship with Amazon is it the code native, what's going on? >> The innovation is in the data integration of getting you product catalog into Amazon which is going to be easier than ever before. You're going to have visibility into performance within Amazon directly from Magento, and then all that transaction data is going to come back to Magento. So when you're using Magento commerce or our business intelligence tools, you're going to have a single source of truth for how you're performing across both channels. >> John F.: And plus massive sales opportunity for growth >> Right. >> Just on a sales perspective. (laughing) >> Right, right, yeah, yeah. >> Amazon's the big gorilla. >> Yep. >> Okay so third announcement? >> The third announcement is in our business intelligence planning so we have a Magento business intelligence product is now available to all Magento customers who have a commercial license with us, at no extra cost, so. MBI is a full-stack business intelligence data warehouse solution that tracks all your data from all Magento products, commerce, order management, and rolls it up into great dashboards, visualization tools, allows you to integrate it with Google analytics and other data sources, so. We're collecting rich data on consumers behavior across both your physical store, with our order management solution, and your online properties with Magento commerce, and giving you really an unbeatable combination of data points on your consumers that's going to really unlock a lot of potential value. >> So does this bring more wrangling to the table, less complexity, offline-online kind of perspective? >> Yeah a lot less complexity. It is an out of the box PI solution, it's an out of box data warehouse that integrates the core data that you want. We have a pro edition that allows you to integrate your other data, so you could integrate CRM data or other things. It's a great way to get a single source of truth reporting solution for all of your commerce touch points. >> And that's all customers, no charge, part of the platform? >> Yeah the essential edition is now included no charge, and there is a pro edition that is a premium product. >> So product, you run the product management, which you got to-- >> Yep keep your eye on the prize, you got to look at the engineering, and then look at the customers. You've got to kind of make decisions, so as you look at the growth of commerce, just in general, online. >> Yeah. >> There's no denying that we're going to a whole nother level. >> Yep. >> (laughing) How do you guys prioritize? (laughing) Because I mean, there's like so many things you could work on. >> Yeah, it is-- >> What are some of the guiding principles, how do you guys make these decisions, what's the internal DNA like? Share some inside baseball, what goes on? >> Yeah sure. You know our philosophy is the three pillars I mentioned, superior shopping experiences, omnichannel, and business intelligence, those are areas that we know are durable areas of investment that are going to provide value to a merchant. The fourth one is our open ecosystem, and that's really unique to Magento, so we partner with over eleven hundred partners, we have an open source platform that a community contributes to. We're doing a lot to get a lot more leverage out of that, and that allows us to innovate a lot faster. So for example, the day the Amazon patent expired, we had a community partner submit a one-click order feature into the code base, we ran it through a quality assurance product. And I believe we were the first to market with one-click order. So what happens is, even beyond the core organic development that the internal R&D team is doing, we have so much innovation going on, that's customer driven, partner driven. That gives us a very rich opportunity to go into areas that, even where we are following our partners or our community, we're able to incorporate things into the product as the market demands them. >> You know I think that's a unique and compelling thing that's different I think about you guys that I like is, you know the old model was we got to own everything, >> John S.: Right. >> every little feature. And you know you look at startups out there, oh that's really a feature not a startup, that's the old joke of silicon valley but, the reality is, is that, you have partners that have business, >> John S.: Yep. >> So they could build a really hyper focused feature, >> John S.: Yep. >> Bring it to the table, you incorporate it in through your ecosystem, >> John S.: That's right. >> That's what you're referring to, right? >> Yeah absolutely, and you know, I think the business model around closed platforms is kind of fundamentally flawed in that regard, because the vendor can never keep up with the rate of innovation. Especially not a space like e-commerce where things are happening so fast, it would be impossible for any one vendor to stay on top of it all. >> John F.: So your strategy: Stay to your core pillars >> John S.: Yep. >> Let the ecosystem innovate, you've got the open source which is the playground for more innovation-- >> John S.: Yep. creative ideation. And then you have a pipeline in through the product team. >> Yep. >> For QA, quality assurance kind of thing going on there. >> Absolutely, absolutely. >> And then ship it our to all your customers-- >> That's right. >> Through what, marketplace? >> That's right. Well we have a variety of ways to get out. So our partners can get extensions out to the market through our marketplace, which is the best place to get Magento extensions. We're also doing a core bundled extension program, so we will be announcing tomorrow that we're-- we have three new core bundled extension partners. We're partnering with Vertex for tax, (mumbling) for deferred payments, and Amazon Pay as a payment method. So those are integrations that those vendors have done to Magento, that we have certified and blessed as the highest quality. And merchants who deploy Magento 224 which will include those bundled extensions and turn them on with the flip of the switch. So we're doing a lot more innovation to make those solutions available to customers. >> I mean it's innovative because you have some things that might not be in the product, well we've got resources, there's always the contention for resources, but when you've got partners innovating. I just saw folks, I was taking a lunch break walking around, you got a coin crypto solution here, hey we could do, you know, 400 tokens. >> John S.: Yeah. >> Or I don't even know, it's like thousands of tokens but, if someone wants to do say cryptocurrency. >> John S.: Right. >> A partner steps up, >> Yeah. >> And that's enabled, that's an option >> Yes, yep. >> So today I want to take bitcoin, >> Yep. >> You could fit that in. >> John S.: Yes, absolutely. it also gives us great advantage on our global reach as well because we can work with partners who want to localize this and take us into markets where we don't have direct presence today. But the open platform and the fact that we're so partner friendly and ecosystem friendly, makes it possible for other people to build businesses and to take us into places faster than anybody else. >> We were talking before we came on camera about your previous experience, you've been in the industry for a while, you've seen some waves. We know, we're old enough to see some of those. E-commerce, and again, e-commerce is 25 years old, and you know it's always been kind of monolithic, you know, one directional. >> John S.: Right. You push to an endpoint, yeah you got JSON now endpoints but the demand is for rich experience, consumer to consumer potentially, >> John S.: Right. >> Peer to peer action, >> John S.: Right. >> All this stuffs going on, what attracted you to these guys for you job, and what do you look at in terms of big waves, that you guys want to ride on. >> Yeah, you know what attracted me, Magento is my first opportunity to be at an open source platform company. And so the excitement all around here at this event is really validating that this is a fun place to be and this is a great approach to market, I think it's a much more interesting way to build products than the old school ways are. So I'm really excited about that. You know, to your point about evolving needs, both the omnichannel need and then also, we've been doing a lot of b to b scenarios, so we have customers using Magento in very innovative ways that again, are outside the box of what we intended when we first built the product. We have partners here who are doing marketplace solutions right now, where our customers are hosting marketplaces where other consumers are selling products to each other, which is a really cool use case. We have always had customers using us in a b to b context, even though we didn't have native b to b functionality built in. In two dot two which just came out last year, we made a big investment to beef up some b to b capabilities in the product and we'll be making more investments in those in the coming years as well. >> Everything flows from the b to c because, mobiles expected there-- >> John S.: Yeah. >> Now you're seeing mobile first-- >> John S.: Yeah. >> cloud first-- >> John S.: Yeah. >> for b to b-- >> John S.: Yeah. And they're kind of upping their game-- >> John S.: Yep. >> You got to up your game, you know everything's online now. And a lot of, if not all of our b to c customers have some b to b dimension to their business, right? So it makes sense for their digital platform to serve not only their direct consumer up fronts, but all their commerce initiatives. >> What's the big thing that you see out there, for the b to b customers because I see b to b really, moving faster now-- >> John S.: Yeah. >> Than ever before-- >> John S.: Yeah. >> Because they used to have the old websites-- >> John S.: Right. >> Now they're puttin' rich media on there they want to do some, you know, some for some service-- >> John S.: Yeah. >> Everything's moving digital-- >> John S.: Yeah. >> On b to b-- >> John S.: Yep. >> Is it awakening, is it-- >> John S.: Yeah, no I think-- >> like, they're waking up and smelling the coffee, what's going on? >> I think it is, I don't think, you know, people are people, and whether you're shopping for a blender or you're a procurement officer and you need to buy IT equipment, you have expectations that you're going to be digitally served with a high quality. The market is moving that way very fast, there's a lot of potential to create better experiences for your customer that way. There's a lot of opportunity to get more efficiency out of your processes by bringing them to the digital so that they can carry on. >> And then obviously outsourcing the role of the community is super important. Talk about the labs, Magento labs, how does that fit into all this, we saw some folks up there gettin' awards on keynote today. >> John S.: Yeah. What's this labs thing about? >> So we have a program with our Magento masters where we recognize people for contributions to the community and so we gave out awards yesterday morning for the top contributors. We had in the two dot two dot four release, that's coming out tomorrow, we had over 200 community contributions before submitting. Enhancements to the product, fixes, improvements. Security improvements, performance improvements, so the amount of contribution to the community is still, really, from the community is still really really valuable and we really recognize and reward and support that. >> Real competitive advantage. So I got to ask you the data question. >> John S.: Yeah. >> The role of data's so valuable you're seeing data, whether it's IOT devices being potentially in retail outlets i mean, wearables is a IOT device. >> John S.: Yep. >> You know Apple pay could be considered a wearable, to some degree as a device. But data moving around, having data integrate-- >> John S.: Right. >> Is a huge issue-- >> John S.: Yes. >> How is that impacting your business, obviously can imagine pretty significantly impacting both market intelligence, real-time bidding, real-time user experiences-- >> John S.: Yeah. >> Without data you really can't get near real time. >> John S.: That's absolutely right, yeah. >> What's your view on that? >> So data is going to be the next big revolution, I think, as digital commerce spreads across all panels consumers are going to expect you to know who they are when you walk in the store, you, they, you remember the past transactions and interactions you had with them. You're personalizing your outreach and experience for them. Data is key to all that. Right now we're in a foundation building phase where we're getting all that data into Magento business intelligence, we're building a data lake. We recognize, for our customers, that connecting all that data together and rationalizing it all is a challenge. We think we can do a lot to solve that challenge for them through our business intelligence tools and our data. >> John great to have you on theCUBE sharing the insights, final question for you is what's one or two things that someone might not know about Magento that they should know about? The approach, the products, how you guys build technology, happy customers, let's see one-two things that they should know about, that may not know about. >> I would say I mean, I think people know Magento as an opensource platform, an opensource brand. They may not know that we are having a lot of success up market right now, we are increasingly getting pulled into enterprise businesses and running very large-scale businesses for people. They may not know us as a b to b solution provider, they may think of us as a b to c only solution provider, so we're doing a lot in b to b right now. They may not know how much we've invested in the people of Magento. In the Austin office where I work, we've more than doubled in size in the last year. So we are growing like crazy, we're bringin' a lot of talent to the company and it's a great place to be. >> John F.: Yeah, you've got a great ecosystem. And what's the reason why you guys are being successful, speed, performance, flexibility, all of the above, what's the key thing? >> All of the above, I mean, I think we get a lot of pull from the market, the Magento brand is still very solid, there's a lot of people out on opensource who are looking to upgrade and move up and that creates a great pipeline for us. I think the competitive landscape is, got options on the lower end and options on the higher end that are a little bit old-school. I think we have an advantage in the innovation and the things we're bringin' to the market that's going to serve us well in the future. >> The pressure to go digital all the time, 100%, is really on every ones shoulders these days, everything's digital. >> John S.: Yep. >> John Stockton Vice President of Product Management at Magento here at Imagine 2018 in Vegas, theCUBE's exclusive coverage. Be back with more coverage after this short break. (pop music)

>> Narrator: Live from New York, it's theCUBE. Covering machine learning everywhere. Build your ladder to AI. Brought to you by IBM. >> Welcome back to IBM's Machine Learning Everywhere. Build your ladder to AI, along with Dave Vellante, John Walls here, wrapping up here in New York City. Just about done with the programming here in Midtown. Dave, let's just take a step back. We've heard a lot, seen a lot, talked to a lot of folks today. First off, tell me, AI. We've heard some optimistic outlooks, some, I wouldn't say pessimistic, but some folks saying, "Eh, hold off." Not as daunting as some might think. So just your take on the artificial intelligence conversation we've heard so far today. >> I think generally, John, that people don't realize what's coming. I think the industry, in general, our industry, technology industry, the consumers of technology, the businesses that are out there, they're steeped in the past, that's what they know. They know what they've done, they know the history and they're looking at that as past equals prologue. Everybody knows that's not the case, but I think it's hard for people to envision what's coming, and what the potential of AI is. Having said that, Jennifer Shin is a near-term pessimist on the potential for AI, and rightly so. There are a lot of implementation challenges. But as we said at the open, I'm very convinced that we are now entering a new era. The Hadoop big data industry is going to pale in comparison to what we're seeing. And we're already seeing very clear glimpses of it. The obvious things are Airbnb and Uber, and the disruptions that are going on with Netflix and over-the-top programming, and how Google has changed advertising, and how Amazon is changing and has changed retail. But what you can see, and again, the best examples are Apple getting into financial services, moving into healthcare, trying to solve that problem. Amazon buying a grocer. The rumor that I heard about Amazon potentially buying Nordstrom, which my wife said is a horrible idea. (John laughs) But think about the fact that they can do that is a function of, that they are a digital-first company. Are built around data, and they can take those data models and they can apply it to different places. Who would have thought, for example, that Alexa would be so successful? That Siri is not so great? >> Alexa's become our best friend. >> And it came out of the blue. And it seems like Google has a pretty competitive piece there, but I can almost guarantee that doing this with our thumbs is not the way in which we're going to communicate in the future. It's going to be some kind of natural language interface that's going to rely on artificial intelligence and machine learning and the like. And so, I think it's hard for people to envision what's coming, other than fast forward where machines take over the world and Stephen Hawking and Elon Musk say, "Hey, we should be concerned." Maybe they're right, not in the next 10 years. >> You mentioned Jennifer, we were talking about her and the influencer panel, and we've heard from others as well, it's a combination of human intelligence and artificial intelligence. That combination's more powerful than just artificial intelligence, and so, there is a human component to this. So, for those who might be on the edge of their seat a little bit, or looking at this from a slightly more concerning perspective, maybe not the case. Maybe not necessary, is what you're thinking. >> I guess at the end of the day, the question is, "Is the world going to be a better place with all this AI? "Are we going to be more prosperous, more productive, "healthier, safer on the roads?" I am an optimist, I come down on the side of yes. I would not want to go back to the days where I didn't have GPS. That's worth it to me. >> Can you imagine, right? If you did that now, you go back five years, just five years from where we are now, back to where we were. Waze was nowhere, right? >> All the downside of these things, I feel is offset by that. And I do think it's incumbent upon the industry to try to deal with the problem, especially with young people, the blue light problem. >> John: The addictive issue. >> That's right. But I feel like those downsides are manageable, and the upsides are of enough value that society is going to continue to move forward. And I do think that humans and machines are going to continue to coexist, at least in the near- to mid- reasonable long-term. But the question is, "What can machines "do that humans can't do?" And "What can humans do that machines can't do?" And the answer to that changes every year. It's like I said earlier, not too long ago, machines couldn't climb stairs. They can now, robots can climb stairs. Can they negotiate? Can they identify cats? Who would've imagined that all these cats on the Internet would've led to facial recognition technology. It's improving very, very rapidly. So, I guess my point is that that is changing very rapidly, and there's no question it's going to have an impact on society and an impact on jobs, and all those other negative things that people talk about. To me, the key is, how do we embrace that and turn it into an opportunity? And it's about education, it's about creativity, it's about having multi-talented disciplines that you can tap. So we talked about this earlier, not just being an expert in marketing, but being an expert in marketing with digital as an understanding in your toolbox. So it's that two-tool star that I think is going to emerge. And maybe it's more than two tools. So that's how I see it shaping up. And the last thing is disruption, we talked a lot about disruption. I don't think there's any industry that's safe. Colin was saying, "Well, certain industries "that are highly regulated-" In some respects, I can see those taking longer. But I see those as the most ripe for disruption. Financial services, healthcare. Can't we solve the HIPAA challenge? We can't get access to our own healthcare information. Well, things like artificial intelligence and blockchain, we were talking off-camera about blockchain, those things, I think, can help solve the challenge of, maybe I can carry around my health profile, my medical records. I don't have access to them, it's hard to get them. So can things like artificial intelligence improve our lives? I think there's no question about it. >> What about, on the other side of the coin, if you will, the misuse concerns? There are a lot of great applications. There are a lot of great services. As you pointed out, a lot of positive, a lot of upside here. But as opportunities become available and technology develops, that you run the risk of somebody crossing the line for nefarious means. And there's a lot more at stake now because there's a lot more of us out there, if you will. So, how do you balance that? >> There's no question that's going to happen. And it has to be managed. But even if you could stop it, I would say you shouldn't because the benefits are going to outweigh the risks. And again, the question we asked the panelists, "How far can we take machines? "How far can we go?" That's question number one, number two is, "How far should we go?" We're not even close to the "should we go" yet. We're still on the, "How far can we go?" Jennifer was pointing out, I can't get my password reset 'cause I got to call somebody. That problem will be solved. >> So, you're saying it's more of a practical consideration now than an ethical one, right now? >> Right now. Moreso, and there's certainly still ethical considerations, don't get me wrong, but I see light at the end of the privacy tunnel, I see artificial intelligence as, well, analytics is helping us solve credit card fraud and things of that nature. Autonomous vehicles are just fascinating, right? Both culturally, we talked about that, you know, we learned how to drive a stick shift. (both laugh) It's a funny story you told me. >> Not going to worry about that anymore, right? >> But it was an exciting time in our lives, so there's a cultural downside of that. I don't know what the highway death toll number is, but it's enormous. If cell phones caused that many deaths, we wouldn't be using them. So that's a problem that I think things like artificial intelligence and machine intelligence can solve. And then the other big thing that we talked about is, I see a huge gap between traditional companies and these born-in-the-cloud, born-data-oriented companies. We talked about the top five companies by market cap. Microsoft, Amazon, Facebook, Alphabet, which is Google, who am I missing? >> John: Apple. >> Apple, right. And those are pretty much very much data companies. Apple's got the data from the phones, Google, we know where they get their data, et cetera, et cetera. Traditional companies, however, their data resides in silos. Jennifer talked about this, Craig, as well as Colin. Data resides in silos, it's hard to get to. It's a very human-driven business and the data is bolted on. With the companies that we just talked about, it's a data-driven business, and the humans have expertise to exploit that data, which is very important. So there's a giant skills gap in existing companies. There's data silos. The other thing we touched on this is, where does innovation come from? Innovation drives value drives disruption. So the innovation comes from data. He or she who has the best data wins. It comes from artificial intelligence, and the ability to apply artificial intelligence and machine learning. And I think something that we take for granted a lot, but it's cloud economics. And it's more than just, and somebody, one of the folks mentioned this on the interview, it's more than just putting stuff in the cloud. It's certainly managed services, that's part of it. But it's also economies of scale. It's marginal economics that are essentially zero. It's speed, it's low latency. It's, and again, global scale. You combine those things, data, artificial intelligence, and cloud economics, that's where the innovation is going to come from. And if you think about what Uber's done, what Airbnb have done, where Waze came from, they were picking and choosing from the best digital services out there, and then developing their own software from this, what I say my colleague Dave Misheloff calls this matrix. And, just to repeat, that matrix is, the vertical matrix is industries. The horizontal matrix are technology platforms, cloud, data, mobile, social, security, et cetera. They're building companies on top of that matrix. So, it's how you leverage the matrix is going to determine your future. Whether or not you get disrupted, whether your the disruptor or the disruptee. It's not just about, we talked about this at the open. Cloud, SaaS, mobile, social, big data. They're kind of yesterday's news. It's now new artificial intelligence, machine intelligence, deep learning, machine learning, cognitive. We're still trying to figure out the parlance. You could feel the changes coming. I think this matrix idea is very powerful, and how that gets leveraged in organizations ultimately will determine the levels of disruption. But every single industry is at risk. Because every single industry is going digital, digital allows you to traverse industries. We've said it many times today. Amazon went from bookseller to content producer to grocer- >> John: To grocer now, right? >> To maybe high-end retailer. Content company, Apple with Apple Pay and companies getting into healthcare, trying to solve healthcare problems. The future of warfare, you live in the Beltway. The future of warfare and cybersecurity are just coming together. One of the biggest issues I think we face as a country is we have fake news, we're seeing the weaponization of social media, as James Scott said on theCUBE. So, all these things are coming together that I think are going to make the last 10 years look tame. >> Let's just switch over to the currency of AI, data. And we've talked to, Sam Lightstone today was talking about the database querying that they've developed with the Plex product. Some fascinating capabilities now that make it a lot richer, a lot more meaningful, a lot more relevant. And that seems to be, really, an integral step to making that stuff come alive and really making it applicable to improving your business. Because they've come up with some fantastic new ways to squeeze data that's relevant out, and get it out to the user. >> Well, if you think about what I was saying earlier about data as a foundational core and human expertise around it, versus what most companies are, is human expertise with data bolted on or data in silos. What was interesting about Queryplex, I think they called it, is it essentially virtualizes the data. Well, what does that mean? That means i can have data in place, but I can have access to that data, I can democratize that data, make it accessible to people so that they can become data-driven, data is the core. Now, what I don't know, and I don't know enough, just heard about it today, I missed that announcement, I think they announced it a year ago. He mentioned DB2, he mentioned Netezza. Most of the world is not on DB2 and Netezza even though IBM customers are. I think they can get to Hadoop data stores and other data stores, I just don't know how wide that goes, what the standards look like. He joked about the standards as, the great thing about standards is- >> There are a lot of 'em. (laughs) >> There's always another one you can pick if this one fails. And he's right about that. So, that was very interesting. And so, this is again, the question, can traditional companies close that machine learning, machine intelligence, AI gap? Close being, close the gap that the big five have created. And even the small guys, small guys like Uber and Airbnb, and so forth, but even those guys are getting disrupted. The Airbnbs and the Ubers, right? Again, blockchain comes in and you say, "Why do I need a trusted third party called Uber? "Why can't I do this on the blockchain?" I predict you're going to see even those guys get disrupted. And I'll say something else, it's hard to imagine that a Google or a Facebook can be unseated. But I feel like we may be entering an era where this is their peak. Could be wrong, I'm an Apple customer. I don't know, I'm not as enthralled as I used to be. They got trillions in the bank. But is it possible that opensource and blockchain and the citizen developer, the weekend and nighttime developers, can actually attack that engine of growth for the last 10 years, 20 years, and really break that monopoly? The Internet has basically become an oligopoly where five companies, six companies, whatever, 10 companies kind of control things. Is it possible that opensource software, AI, cryptography, all this activity could challenge the status quo? Being in this business as long as I have, things never stay the same. Leaders come, leaders go. >> I just want to say, never say never. You don't know. >> So, it brings it back to IBM, which is interesting to me. It was funny, I was asking Rob Thomas a question about disruption, and I think he misinterpreted it. I think he was thinking that I was saying, "Hey, you're going to get disrupted by all these little guys." IBM's been getting disrupted for years. They know how to reinvent. A lot of people criticize IBM, how many quarters they haven't had growth, blah, blah, blah, but IBM's made some big, big bets on the future. People criticizing Watson, but it's going to be really interesting to see how all this investment that IBM has made is going to pay off. They were early on. People in the Valley like to say, "Well, the Facebooks, and even Amazon, "Google, they got the best AI. "IBM is not there with them." But think about what IBM is trying to do versus what Google is doing. They're very consumer-oriented, solving consumer problems. Consumers have really led the consumerization of IT, that's true, but none of those guys are trying to solve cancer. So IBM is talking about some big, hairy, audacious goals. And I'm not as pessimistic as some others you've seen in the trade press, it's popular to do. So, bringing it back to IBM, I saw IBM as trying to disrupt itself. The challenge IBM has, is it's got a lot of legacy software products that have purchased over the years. And it's got to figure out how to get through those. So, things like Queryplex allow them to create abstraction layers. Things like Bluemix allow them to bring together their hundreds and hundreds and hundreds of SaaS applications. That takes time, but I do see IBM making some big investments to disrupt themselves. They've got a huge analytics business. We've been covering them for quite some time now. They're a leader, if not the leader, in that business. So, their challenge is, "Okay, how do we now "apply all these technologies to help "our customers create innovation?" What I like about the IBM story is they're not out saying, "We're going to go disrupt industries." Silicon Valley has a bifurcated disruption agenda. On the one hand, they're trying to, cloud, and SaaS, and mobile, and social, very disruptive technologies. On the other hand, is Silicon Valley going to disrupt financial services, healthcare, government, education? I think they have plans to do so. Are they going to be able to execute that dual disruption agenda? Or are the consumers of AI and the doers of AI going to be the ones who actually do the disrupting? We'll see, I mean, Uber's obviously disrupted taxis, Silicon Valley company. Is that too much to ask Silicon Valley to do? That's going to be interesting to see. So, my point is, IBM is not trying to disrupt its customers' businesses, and it can point to Amazon trying to do that. Rather, it's saying, "We're going to enable you." So it could be really interesting to see what happens. You're down in DC, Jeff Bezos spent a lot of time there at the Washington Post. >> We just want the headquarters, that's all we want. We just want the headquarters. >> Well, to the point, if you've got such a growing company monopoly, maybe you should set up an HQ2 in DC. >> Three of the 20, right, for a DC base? >> Yeah, he was saying the other day that, maybe we should think about enhancing, he didn't call it social security, but the government, essentially, helping people plan for retirement and the like. I heard that and said, "Whoa, is he basically "telling us he's going to put us all out of jobs?" (both laugh) So, that, if I'm a customer of Amazon's, I'm kind of scary. So, one of the things they should absolutely do is spin out AWS, I think that helps solve that problem. But, back to IBM, Ginni Rometty was very clear at the World of Watson conference, the inaugural one, that we are not out trying to compete with our customers. I would think that resonates to a lot of people. >> Well, to be continued, right? Next month, back with IBM again? Right, three days? >> Yeah, I think third week in March. Monday, Tuesday, Wednesday, theCUBE's going to be there. Next week we're in the Bahamas. This week, actually. >> Not as a group taking vacation. Actually a working expedition. >> No, it's that blockchain conference. Actually, it's this week, what am I saying next week? >> Although I'm happy to volunteer to grip on that shoot, by the way. >> Flying out tomorrow, it's happening fast. >> Well, enjoyed this, always good to spend time with you. And good to spend time with you as well. So, you've been watching theCUBE, machine learning everywhere. Build your ladder to AI. Brought to you by IBM. Have a good one. (techno music)

>> Narrator: From Austin, Texas. It's the CUBE, covering DockerCon 2017. Brought to you by Docker, and support from it's ecosystem partners. >> Hi, I'm Stu Miniman, with my co-host, James Kobielus, who's been digging into all the application development angles. Happy to welcome back to the program, here at DockerCon, Yaron Haviv, who is the co-founder and CTO of iguazio. Yaron, great to see you. >> Thanks. >> How have you been? >> Great, great, been busy traveling a lot. >> We talked about how some of us celebrated Passover recently, I had brisket at home. We had Franklin's Barbecue brisket here. Anthony Bourdain said the only two people that know how to do brisket well, are Franklin's and the Jews. (all laugh) >> So we had Passover, a lot of good food, but also a lot of traveling. I was also in a Kubernetes conference in Europe and here. Prior to that, big data show, so it's a lot of traveling. >> Kubernetes, Docker, Ecosystem. You've been watching this, your company is involved in it. What's your take on the state of the ecosystem, and what do you think of the announcements this week? >> You know, I have also been to the Kubernetes conference, and you see those are still small, relatively small shows. And it's mostly developer focused. What we see is that Kubernetes is taking a lot of share from the others, because most of the guys that adopt are not enterprises yet. It's people that have a large enough infrastructure that they want to use it internally, and Kubernetes is a little more flexible. And on the other end, you see Docker trying to create a greenware-like, shrink wrapped, version of container infrastructure. So we see those two, and there's obviously the Public Cloud with their fully integrated stack. Now, what I notice here in the show, and also when, a couple of weeks ago, in the Kubernetes conference, think about the stack. It has, let's say, 20 components. So someone like Amazon brings the entire 20 components, and it's fully integrated and secure and networking and storage and data services and everything. And here, what you'll see, is a lot of vendors, this guy has those four components, the other guys have those five components, in some cases they actually overlap. So this guy will have three unique components, and two other components, et cetera. And it's very hard to assemble a full blown solution. So as a buyer, how do you decide which components am I going to choose? That's part of the challenge, and also helps serve the cloud guys. >> I remember when I first joined at Wikibon, we talked about, the hyperscale model was you take your team of PhDs, you just architect your application and software. You're the enterprise though, you don't have that talent. So you will spend money to buy that packaged solution. I want to buy it as a service, I want to buy it easy. Where do you see the maturity of this market, and how that fits for, and what can the enterprise consume, how do they do it? Or do they just go to platforms? >> So this is why our positioning was, it was a platform. We are not a component. We are a fully integrated system. We have multi-tendency, we have security, we have data lifecycle management. We integrate with applications, we have our own UI. But it's focused more on the data services. So if you take a dozen Amazon data services, you need to send Dynamo, and others, and object and file. We basically pack all of them, because data is the biggest challenge, as you know. High volubility, versioning, reliability, security. The biggest and toughest challenge is the data. And once you solve that one, the applications, they all become stateless, and that's much easier. There still needs to be a bigger ecosystem around it, which is why we are doing a lot more work with CNCF. And trying to create standards for the different interactions between those components. So when a buyer goes and buys a certain component from one vendor, it doesn't necessarily lock in to that. They can just go and modify it in the future. I think once you solve the data problem, of the persistency, which is sort of the toughest challenge in this environment, the rest of it becomes simpler. >> One of the questions James has been asking this week, is where analytics fits in? I look at your real-time continuous analytics piece, not an application that I heard talked about too much, maybe we can get your viewpoint on it? >> And the relevance is, of course, much of the application development that is going on, the hot stuff, is related to artificial intelligence, on streaming analytics, clearly continuous. >> Which is where we focus on. Some of the things that I try, to work with different communities, it's explained, that right now we have bifurcation, we have the Apache ecosystem, and we have the Docker ecosystem, totally separate ecosystems, and by the way, you know that cloud is where most analytics happen. >> James: Yes. >> So basically, analytics and cloud technology have to converge. This is what we have been trying to pitch, is why do you use YARN, as a scheduler, where I can use Kubernetes, and it's more generic. Because I can schedule any type of work. So this is something that we are trying to push, and all this notion of continuous integration, when we say continuous analytics, it's not just about the real-time aspect, it's also about the continuous development and integration. >> James: Yes. >> So you actually want this notion of server-less function, which is one of the things I like. Also, just immutable code and infrastructure, you want to adopt those notions, so analytics is going to go into real-time, more and more. So that means, unless I have my connected car pipeline that I get streams, and I process it, and I generate insights. What happens if I find a bug in my application, or I just want to enhance it, and create another feature? So I want to be able to just push a new version, of my analytics code into some platforms, hopefully ours. >> You also want to train that new algorithm as well, to make sure it's fit for whatever specific... >> Yeah, but you have to have this notion of continuity, which means all the integrations we did, have to be different, it has to be a lot more atomic. >> Yeah. >> It has to be check-pointed. All those things that I can basically knock down my analytic process, and relaunch it, and it goes seamlessly and continues. And that's not the Apache model, to play around at bootcamp enough, it's a lot more Legacy kind of approach, which I don't connect to too much. >> Yaron, maybe complete out the stack that you're building, how does serverless fit into this also? >> Okay, so basically, we are building all the data engines, we are doing streaming, we are doing objects, files, NoSQL, SQL, for us it's all integrated into the same very high performance engine. We also have built in analytics, so we can build things like joints and aggregations, and all of the computations on the data as it injects, and it could basically present itself as many different things. Now one of the things we get asked from customers, and we demonstrated that in Strata, let's assume I'm throwing an image into this thing, I want to be able to immediately analyze the image, and say if there is a face, if there is something suspicious about the picture, or maybe even simple things, like extract meta-data information, like geolocation of the picture, so I can do something with it. So we had to develop internally, an event driven process, we didn't call it serverless internally, where you throw data, and it immediately launches and triggers a process, which is a Docker container based process. It has high speed message bust integration into our data platform, that immediately invokes and processes that in a very elastic fashion. So if you throw thousands of objects, it elastically generates multiple workers to work on that, and that's also how we design things like DR, and backup internally in our platform to be very flexible, so we can build DR to S3. How do we do it? We basically have serverless functions that know how to convert the updates into a continuous stream of updates, and then they just go and there is a small code that says "Go right to S3". And that allows me a lot flexibility to develop new features. So this is all this notion of data lifecycle management, with every advance in our product, is actually based on serverless functions, we just didn't call it serverless. One of the things that we're working on with the community, is trying to detach that portion from our product, and contribute it as an open-source projects, because it's much faster and much more optimized than what you'll see, including IBM Whisk or Amazon Lambda implementation of that. >> Are you working with the Apache... Are you working in the context of the Apache framework to expose, for example, machine learning pipeline functions as serverless functions? >> So again, Apache is not the right necessarily place to do that. >> You can do them in Spark. >> I do them in Spark and all that, but we do want the Kubernetes environment to deal with all the constriction requirements for that thing. The way that we do, for example, tensorflow integration is we may expose file into tensor float, on one end, to be able to look at the image, and the same time the metadata updates, so what the image contains is exposed to tensorflow as sort of a key value store, or document store. It just updates attributes on the same image. So the way that we work now with healthcare, an MRI image lands and something looks at the MRI image, and senses cancer. Basically, you can mainly attack the same image, with records, which fields say contains cancer by this guy, take picture of this guy. And then, when you want to run a query, and say, you know what, give me all the MRIs pictures that contain query, it now flips and acts like a database, and you just pull all those images. It's a different approach to how to do those things. >> Yaron talked about Docker containers, Kubernetes, serverless, how do virtual machines fit into the environment? >> I had some interesting conversations at Kubernetes with some friends that are high ranked in this industry, without disclosing, do you really need openstack in between bare metal and containers? Because the traditional approach is, Okay, we have bare metal, we need to put virtualization layer for isolation, and then we need to put Kubernetes or Docker. And we figure out that very little amount of risk, actually, in putting, especially with the new security, things around containers and image signing, and what we do, which is authenticating the container, not the infrastructure on data access, network isolation, all those things that eventually can collapse and eliminate virtualization, but not for every application. Some applications which are more traditional Legacy, the application may still require VMs, because it's quite a different philosophy to develop microservices and develop VMs. Apart of what I see here in the show is not everyone internalizes that. People still think in the notion of Here's my lightweight VM, that happen to be called Docker container, and I'm going to give it the volume, and I'm going to create snapshots on that volume, and all that stuff. But if you think about it, what is really microservices? It's about allowing this elasticity, so the same workload can spawn multiple workers, it's the ability to go and create update versions, it's the ability to knock down this container anytime I want, and just kill it and launch it in a different place. You know how Google works, or Amazon or Ebay, or all those guys. You're basically killing containers on purpose, to basically test their system. All this notion that my configuration and my logs and all that stuff, sits inside the container, is not cloud native, and it doesn't allow this elasticity that you want if you're building a Netflix or an Ebay, or a modern enterprise infrastructure. So I think we need to put those two things aside. You have Legacy applications, keep them in the VMs. You have new workloads, you need to think of data, and data integration, and microservices differently on something which is entirely stateless. The image of the container builds from the get. OK? And create a Docker image. And if you want to go to a different image, you just go and recreate, from source, the same image. The data for that image needs to be stored in a data facility like a database or an object or something like that. >> Yaron, final question I have for you is, talk a little about the customers you're interacting with, talk about the people that are here, as you said, there's a spectrum of how far along they are in the thinking. You're pretty advanced in some of your architectural thoughts and opinionated as to where you're going. Where are the customers today, how many of them are ready for the future versus sticking to what they have got? >> So what you mentioned before, part of the key challenge for enterprises is they all want to move into the digital transformation, they all want to be competitive, because some have existential threats, think about even banks, today, where Apple comes with Apple Pay, it kills a lot of the margins they are making from all those small transactions. And now, no one really cares how many branches you have in the bank, because all the Y Generation just goes to their mobile app. Someone like a bank, have to immediately transition and be able to offer premium services, offer better experiences for the mobile application, be able to analyze user behavior, some things that are more strategic. The traditional things that IT deals with like exchange server management, SAP, all those Legacy things will move to the cloud, because there's no real value there. And what you see is more and more enterprises thinking about how do we generate the differentiation, which is more about analyzing data, and being able to provide better service to the customers, and the biggest challenge is they don't know how to do it. Because what the industry tells them, Go to Apache, and take a dozen of projects, and now integrate those and figure out the security problem, and you know what, you want to add Kubernetes, that's from a different story, but let's try and glue this together, and that's extremely complicated. So what we are trying to do is go to those customers, say you know what, we're building a full blown solution, fully integrated, security is baked in, all the different data services, it integrates with things like Kubernetes natively, we actually do the extra mile, we actually build Spark and tensorflow, and the images that contain everything, including support for us, that you can just launch Spark and it connects and works. We want to make life easier for those enterprises to solve those key challenges that they are working on. And this is working extremely well for us, actually the challenge we have, we only have, I think, two sales guys and we have a huge pipeline, and we can't really deliver for most of those projects. >> Good challenges to have sometimes, talk about scaling, which has been one of the themes of the week here. Yaron Haviv, great to catch up with you as always. We'll be back with two days of our coverage here, at DockerCon 2017. You're watching the CUBE. (electronic music)

>> Narrator: Live from San Jose, California in the heart of Silicon Valley, it's theCUBE, covering QuickBooks Connect 2016. Sponsored by Intuit QuickBooks. Now here are your hosts, Jeff Frick and John Walls. >> And welcome back here to San Jose, the Convention Center. We're on theCUBE to continue our coverage of QuickBooks Connect 2016. We're here for the rest of today and onto tomorrow for two days at this great event, third year event, that is now going on with 5,000 attendees. So record attendance, great keynotes this morning, another keynote session coming up, by the way, in just about a half hour or so. We'll have some guests after that and then continue our coverage here tomorrow on theCUBE. Along with Jeff Frick, I am John Walls. We're joined by Yumi Clark who's the SVP of product development at Capital One. And Yumi, thank you for being with us here on theCUBE. >> Thank you very much. >> First time, right? >> Yes. >> On theCUBE. >> Yes, first time. >> So Capital One, what are you doing here? In a good way, of course. But what do you find of interest from a professional standpoint with the small business crowd? >> Yes, so Capital One is here because we want to meet our customers where they are today, and many of our customers are actually here at the show, QuickBooks Connect. Whether they be accountants or small business owners themselves, we are looking to build products for them and solutions for them based off of the pains that they have and the problems that they're having. So we're here to do much of a data gathering exercise and see what we can provide to our users. >> So I assume this is an ongoing process, right? This isn't just a one-time hit. Generally speaking, what do you hear from the people with whom you work or that you're supporting, in terms of their pain points for the services you provide and what you can do from a solutions standpoint? >> Yes, well actually here at QuickBooks Connect we have been doing some informal polls with the people that have been attending, and we often hear these types of things also as we're leading the businesses within the product development space. We're seeing a lot of the people talk about the passions that they have with regards to the business, and oftentimes they start the business because of their passion. They're actually not starting it because they want to start a business itself. Because oftentimes those businesses have a lot of administrivia tied to them in process. That's not what they're doing to start that business. They want to make sure that they're creating something that really speaks to them and speaks to their passions, and because of that, they've created a small business. >> But then, unfortunately, they have to tasks and they have to do accounting and they have to do payroll, they have to pay the vendors, and they have to get up from making whatever they're making and selling whatever they're selling to deal with the reality, and that's really where the opportunity at QuickBooks has done. But part of the thing they're trying to do is build this ecosystem not only to provide the tools, but really to provide other services to enable these folks to be successful. So within the Capital One world, as you look at small businesses as kind of a category, what are some of the unique challenges that they have that you guys are trying to help them with? How do you see the small business world as an opportunity? >> Yes, so in the same way, Capital One is also looking at that ecosystem. First and foremost what we do as a financial institution is provide very competitive savings and checkings and credit cards as part of our plethora of products that we offer. From a savings perspective, we have a 1% cash back, and from a credit card perspective we have a 2% cash back rate so that we're truly competitive from that perspective. In our recent surveys and the research that we've done, we've also seen that many of these small businesses, whether they're here or somewhere else, they have more than two bank accounts in order to run their small business. Also what we see is that they have anywhere between 10 to 12 different applications that they are stitching together to get their financial health of their small business right. Knowing that that's the problem, what we're doing at Capital One is helping them stitch that together. Not only do we have a competitive checking and savings accounts so that they can actually pay their bills and do the invoicing and the payroll, we are also looking at things to help them in future. And most recently in August what we did as Capital One is launch the Spark 401k service. 50% of all Americans either own or work for a small business so it's a huge crowd that needs to be addressed. Even though it's 50%, only 13% of those small businesses are offering some type of retirement benefit. And because of that we saw that as an opportunity and challenge that we can help resolve, and that's why we've launched the Spark 401k service this past August, which is specifically targeted to those small businesses so they can help not only themselves but the employees that work for them think about the future. >> So how has this changed the way you do business? Because you're looking for new products, you're looking for new services, you're looking to be more expansive in the kinds of things that you're offering, right? >> Yumi: Yes. >> But I'm sure the migration has... sometimes it's not natural. You're introducing new concepts to your workforce and to your people and so how's this impacted what Capital One does, in terms of looking to stretch yourself? Basically to create new opportunities for your clients. >> Right. Well, there's two ways that we're addressing the client relationship. One is that we're definitely seeing that digital transformation happen. Most recently in a poll that we took there was about 30% of small businesses were using some type of mobile device, but in the most recent study that we've seen it's about 60%, it's more than doubled in terms of the mobile banking and the mobile device that they're using to run their small business. And because of it we're leaning in to many of the mobile solutions that Capital One can provide so that small businesses can do things anytime, anywhere and any place as they're trying to run their business. 'Cause the reality is is that they're not just sitting in one place nine to five running their business. They're running off, doing other things, they're doing it at home. Also we're exploring different experiments so that if we're meeting the small businesses where they are, trying out different devices and different technologies, I don't know if you've seen some of the announcements that we've made but we're also looking at IoT and some of the Alexa form factors by which you can test and see how is my daily balance, what are the transactions going through and the sort of thing as well. So we're marrying a lot of the technologies that we are seeing and helping small businesses make that transformation themselves where they are today. If they're using one type of device, we'll be helping them with that mobile device. We're helping them with Alexa, for example, as well. And the helping them make that transition. >> So many choices. >> Go ahead, Jeff. >> I was just going to say and then there's now the gig economy, right? >> Yes. >> I wonder if you guys are, I'm sure you're looking at it, how do you see that as being fundamentally different? We were at a thing at the Stanford graduate school the other day and we were talking about the gig economy. At least a small business are thinking about things like retirement and setting aside money for taxes and potentially there's all types of retirement options if you're a small, self-employed person. But then you think of the gig economy, it's a guy doing four hours of week before class to run its Uber, or Postmates or all these kind of little bits and pieces. It doesn't appear from the outside looking in, I have no data, that they're really thinking through what is their total cost? Not only for the insurance and the wear and tear on the car, but then to set aside for taxes, and then are they putting some aside for insurance? Are they putting some aside for retirement? It just feels like that's a whole different kind of category of work and yet it's the one that's growing the most rapidly. >> It is and it isn't, actually. I think that oftentimes financial institutions have been geared more towards companies, business entities and that sort of thing. If we think about the most recent Spark 401k launch that we did, we're looking at companies of one, which are actually gig economy workers, if you really think about it. And then we are able to support those types of employees or businesses as well. The second thing that we're doing in terms of the gig economy is the reality is a lot of these people are, in the same way as I was mentioning before, stitching together their work life. And stitching together their work life means that they're using multiple applications and multiple revenue streams in order to be financially stable. And because of that, one of the pain points that we wanted to address was can we make it easy for these people to stitch together? And that's why we have the aggregation of the top 12 financial institutions within Spark Business so that they can get a complete financial health history of where they are today. >> We've been speaking with different folks from Intuit today and one of the striking conversations we had was about adoption within the accountant community and the cloud migrations, and people with very traditional perspectives or very regimented viewpoints about this is how I do things and the reluctance to change. What are you seeing in terms of digital adoption, what businesses are doing, how willing are they to accept some of these new products, or understanding this is a better mousetrap? And how do you grow that to make them understand this is maximize your efficiency and lower your cost, it's all good. But it's hard to get 'em there. >> Yes. One of the things that we actually see is not solving for the sake of creating a new feature. In the same way that I would feel if I were a small business, just because there's something out there doesn't necessarily mean I want to use it. You have to show the benefit to that small business owner. And if you think about where small businesses have been, they have been going to the bank, but they become more technologically savvy using, for example, mobile deposit capture because that saves them time, and all they have to do is take a picture of the check and it just works to deposit those moneys into a financial institution. And that's what we're providing as part of Capital One. If you show the benefit first, rather than the solution first, I suspect that more people will say, I'll give it a try. And that's what we're seeing in our base as well. We're seeing people saying, I'll give it a try, I am technologically savvy, I am using my mobile device more than I was before, sure, why not, and I'll give it a try. >> John: And that works? >> It has been working for us and we're seeing definitely more people going towards our Spark ecosystem solution, and they're stitching together all of the different applications because they are definitely feeling the pain of trying to do it themselves. And it's really hard to figure out themselves. >> So what's your biggest challenge, then? In terms of, it sounds like adoption, you're working and making progress on that front, you're here surveying your customer base, trying to understand what their needs are. It sounds like everything's great, everything's good, but that isn't always the case, obviously. There are challenges. In your perspective, from your viewpoint, what is it? What's the big hurdle you think that is keeping in the way a progress for you as Capital One and for the small business owner? >> I think really honing in, I think a lot of people often talk about small business owners trying to manage their financial health and their cashflow. That's the reality of running a small business. The question is how you solve that. Is it thinking about the savings and the checking accounts? Is it about thinking about the 401k in the future? Is it about that balance? Is it about tying savings and efficiency? And there's quite a fine line between thinking about just the actual solutions themselves and really offering the benefit. And so that, for us, is kind of the biggest challenge. Meaning that as we test into all these different applications, we need to make sure that we are improving their cashflow and showing them transparency around their financial health. >> It's funny you talk about whether there's a benefit or not and I just think from your customers' point of view, the small businesses, just all these different ways to pay. They want to take that money in and put it in and put it in their Capital One account. Whether it's Google Pay or Apple Pay or they even have Samsung Pay, I don't know why I'd ever want Samsung Pay, and who knows what tomorrow pay is going to be. From your customers' point of view, what do they think of this wave of options that their customers, the end customers, want to have, they think they want to have? They got people pushing these different alternatives down their throat. Are they really necessary? Do we need Samsung Pay along with Apple Pay and Google Pay and I already have credit cards and ATM cards and chip cards and god help us if I pull the 20 out. I went to one restaurant, they wouldn't even take cash. Like, we don't take cash. What, you don't take cash? It's so much more complicated now. There's just so many options coming out. I think of driving through a snowstorm at night with your headlights on. It's just like-- What do you tell 'em? How do they navigate this way? Oh, by the way, I'm still trying to just run my business. >> Right, actually, that's one of the things that we want to do at Capital One. We wanted to give small business owners the personalized delivery of data and looking at what would help them as they're running their small business. Because there are so many choices there, we want to help them make the choices by showing them the data that nudges them towards perhaps you might want this rather than this. That's what we're doing from a short term perspective, and more longer term, what we're also looking at, what is the benefit that we can actually provide? And showing those benefits clearly and transparently to the small business owner. There are a lot of choices out there. >> A lot of choices. Well, Yumi, we've asked you a lot of questions. The one that I think we don't have to ask is what's in your wallet, right? (laughs) We know what's in your wallet. >> Yes, a Venture credit card. (laughs) >> Yumi Clark from Capital One, thank you for joining us here on theCUBE. We appreciate the time. And good luck with the rest of the surveying. I'm sure this is a pretty fertile territory for you in terms of finding out what your customers need, what they want, and what you can do for 'em. >> Thank you so much for having me. >> Thanks. >> Thank you. Back with more on theCUBE here form San Jose in just a minute. (elecronic music)

(upbeat pop music) >> Announcer: Live from San Jose, California. In the heart of Silicon Valley. It's theCUBE, covering QuickBooks Connect 2016! Sponsored by Intuit QuickBooks. (upbeat pop music) Now, here are your hosts, Jeff Frick and John Walls. >> Welcome back here on theCUBE. Along with Jeff Frick, I'm John Walls. As we continue our coverage here at QuickBooks Connect 2016. Gathering here in San Jose at the Convention Center. Third annual gathering with a record crowd of more than 5,000 attendees. (crowd noise) So the show continues to show explosive growth. Which is, I guess you can say a lot about what Intuit's doing, in terms of how it's growing its portfolio, in terms of how it serves the business ... The small business and the medium-size business communities. With us now is Sasan Goodarzi, who is the EVP of the small business group at Intuit. Sasan, good to have you with us-- >> Thank you. >> We appreciate the time. >> Thank you for having me. >> What are the keynote stars today? You were talking about some key things, big things about the company about how we're going to help save time. How we're going to have more accessibility to money. And ultimately what we could do to deliver a better proposition to small business. So talk about that, if you would, a little about that theme on the keynote stage, and how that applies to what you're doing in general with QuickBooks. >> Sure, sure. Well one of the things that our customers have taught us is, that there are three things that are important to them. One is time, so they can actually spend running their business and the product that they're passionate about; versus all the tedious, drudgery things that it takes to run your business. The second is money. It's mind boggling the effort that goes into earning money. But how hard is it for them to actually get access to their money. And then last, but not least, is ways to help them grow their business. They're experts in their industry, but where they need help is ways in which that they can drive growth. And so everything that we do is centered around those three things. And it's what inspires us when we show up to work every single day. So a lot of, obviously, what we talked about today on stage, was just very quick, we call ESPN highlight reels of here's the innovation that's coming your way to either save you time, put more money into your pocket, or help you grow your business, or your practice. >> Sure, okay. >> What's amazing is as I say, as much as they've worked to finally get that sale, a lot of times it seems all the collection side-- >> That's right. >> For small business. A huge issue, getting paid. To do all that work, sell it, have a happy customer and then, don't necessarily get their receivables in line. >> That's right. I know we threw a lot of stats out there this morning. But first of all, 80% of small businesses have some sort of a cash flow issue. And in that context about 65% of them have invoices that are 60 days overdue. And in fact, they live and die by getting paid on time. And so, obviously, the innovations that we talked about on stage today, were how do you get access to those funds right away. >> Jeff: Right, right. >> That's one element of it. The other element is we have all the data of small businesses. And so we know what they're good for. And so we can deliver loans to them on the spot. If they have payables and they want to borrow on the payable to make payroll for the week, or they want to go buy more inventory to grow their business, we can actually fund them very quickly. Literally within minutes. And so those are examples of what we showed on stage today all in service of helping them thrive and achieve their dreams. >> I love to ding into that a little bit, because growth actually exacerbates your cash flow problem if you're not managing it well. And now suddenly you're selling more and you got to buy to fulfill those obligations. But the fact that you almost have a secondary market now for people to be able to borrow money without pulling all their paper together, and trekking down to the bank and hoping they can get it, because you actually have the real data. It's updated (chuckles)-- >> That's right. >> All the time. And it's a different set of data ... Potentially more complete set of data for a lender to actually make that decision, than the stack of paper that they bring down-- >> That's right. >> to the local bank. >> That's right. Well, you know it's interesting. You just said something that triggered a thought. When you think about startups that go out and get VC money ... There's a reason why they have board of directors, 'cause the board of directors what they're looking for is one, do you have a growth plan, but then how do you manage that growth? How do you make sure you have enough money? How much money are you burning per week? And are you going to be able to maintain that growth? Small businesses don't have that. They don't have the board of directors that are actually helping them with some of those decisions. They may not be surrounded by a CFO or a finance expert in the office. And so part of what we're trying to do is just digitize and automate everything so they don't have to worry about that. And secondarily I think to the point you made, helping them with access to money at the point in which they need it. But I think even before we get to that stage, what we're trying to do is help them by being that board of directors without having to have one. Which is to helping them manage their cash flow, their inventory. Because as they're on that growth curve ... One of the main reasons why they go out of business is 'cause they're growing fast, but they're not managing their funds, and they do not have enough money sometimes to make payroll. >> Right. Well we've heard the stat from a couple of different sources but 50% of all small businesses fail in the first five years-- >> That's right. >> of operation. And the use of accounting and accountant, what that could do to increase your odds of being in business for the long term. So certainly you could see where all that is coming in play. You mentioned payments, so we're thinking about Apply Pay. That was one of the announcements-- >> Yes. >> You had. Google Calendar, talking about time. >> Sasan: Yes. >> And then AMEX with the loans. So the power of these partnerships, I'd like to hear from you on that, because, you know, big names, right (chuckles) >> Sasan: Yes, yes. >> That I ... If Jeff or I or anybody watching ran a little mom and pop operation in Morgantown, WV, I've got Apple, and I've got Google, and I've got Intuit on my side. Talk about leveraging that power for small businesses? >> Yes, actually listening to you inspires me around what Intuit is doing for these small businesses. And it starts with our vision of having an open platform. It's less about what we innovate on that platform, but our goal is to bring all of the innovation; whether it's our engineers or engineers outside of our four walls. Bring all of that innovation on our platform, so that in fact we can digitize and automate everything with Google Calendar. So we can go in and we know all of where you spent your time, and help you easily, with one click, invoice your customers. Or, as an example you used, be able to use Apple Pay Touch where you can immediately get paid. But that's because our goal is to have an open platform where we bring all the innovation of the best companies out there to you. So that you can run your business on any device, and you don't have to worry about which application it is, but that we do it all for you. >> I just love the Google Calendar example, because so many great innovations today are basically reassembling stuff that's already out there; leveraging APIs and presenting it in a different way. And so the fact that you're taking advantage of Google Calendar, which so so many people ... You probably know the numbers use ... And then have that drive your billing, have that drive your time management, and then just take advantage of the data that's there, or as Scott said, "Take advantage of the data that's in your phone." >> Sasan: That's right. >> It knows exactly how far you went on that drive to the client. It knows when you left and when you arrived-- >> That's right. >> and when you got home. So the leverage of Cloud platform with APIs, to pull that data in and drive in a seamless integration, it makes (chuckles) it makes too much sense, right? (Sasan laughs) It does, and when you think about someone like Google, where there's a billion people that use Gmail ... >> A billion. >> And most of them are using ... There's a billion people that have Gmail accounts. >> Jeff: Wow. >> And over 60% of our customers use Google Calendar to run their business. And so, it's only intuitive to figure out a way well, how do we automate all of that-- >> Jeff: Right. >> so that the customer doesn't have to use cookbooks for taxes and accounting, then go to Google Calendar to see where they spent their time so they can figure out how to invoice? >> And they type it in, right. >> Just integrate it all together so it's all in one place, yeah. >> How do you all keep focused when your market, your potential market's so big? You've got, I don't know ... I've read, was it 800 million possible businesses, right? Small businesses. >> Sasan: That's right. >> So how do you ... If you look at what would be reasonable growth trajectory and expansion, your plans ... How do you keep your eyes on the target, and how do you determine that target? >> Yeah, that's a great question. Let me start with where you just ended, which is there are 800 million self-employed and small businesses worldwide. And 97 to 8% of 'em actually are not using the Cloud to run their business, or their time. And the way we prioritize is think about the countries that are the biggest opportunity to create virility by those that are using the platform. And so we've prioritized which countries that we're going after, and really doubling down in those countries. And that's where we really are able to focus our efforts in time. 'Cause once we create this, what we call the network effect, the more small businesses and self-employed we get to use the platform, the more we get accountants to be able to see the power of the platform. The more they tell their friends. The more accountants are recommending it, you in essence create this flywheel effect of more and more going to the Cloud. And once we get that flywheel effect going, we'll think about what's that next country that we want to go into. We're not that serial about it, but our biggest focus comes from being clear which countries we're going to play in today, and which countries, for now, we're going to wait 'til we get this network effect going. >> And now you've got this whole new way to work. People that are giving up part of their house or apartment for Airbnb rentals. Or people that are driving in Uber for four hours a couple of days a week. Again, those are all based on systems that are driving that engagement. Do you see that it's just a whole new opportunity, do you see a lot of growth in ... I always forget the technical term for-- >> Sasan: The digamy ... The giga-- >> The gig. >> Sasan: The gig economy. >> The gig economy. >> That's right-- >> Which is a whole new and swelling thing. >> It is. >> And for a lot of those people, they are even less sophisticated on keeping track of their tax withdrawals than the small mom and pop store (chuckles)-- >> Sasan: That's right. >> that's at least been paying their social security for a number of years. >> Sasan: That's right. >> So another huge opportunity for you. >> It absolute is. One of the myths is most self-employed are actually not part of the gig economy. There's the photographer that you may call on to come take pictures of your family, or the landscaper that's a one-person shop. That's 90% of self-employment. About less than 10% is the Airbnbs, the Lyft, and the Ubers of the world. But that number's only going to grow over time. In fact, our view is in this day and age people will work at a company for three to four years at a time. We believe in ten years, people will work for three to four companies in a day. 'Cause they're workers, and they're outsourcing their time to different companies. >> Jeff: Three or four companies-- >> A day. >> Jeff: A day? >> A day. Because in essence, they're self-employed. Now I may work for you and do a job. I may work for you and do a job. That's actually starting to happen today. Except it's a small part of the economy. We believe ten years from now it'll be a huge part of the economy. And that creates a huge opportunity for us, 'cause they're all self-employed. >> Right. >> Before you head out, again, one of the big trend topics, artificial intelligence, machine learning. How do those come into play in your vision for the company's vision, and the products and services that you think you could develop that can be put to use? >> Yeah, in fact we think there are two core competencies that we must have. One is an open platform where we integrate all applications into the platform, whether it's ours or somebody else's. The second is being amazing at leveraging the data, whether it's data from a PayPal app, a Square app our own app. And leveraging artificial intelligence and machine learning, so we can do the work for our customers. So we believe when it comes to data and artificial intelligence, that is actually one of two or three primary core competencies that we are building as a company. And it's something we're not new at. We've been doing this for years. In fact, last year in TurboTax we've reduced the amount of time it took to do your taxes by 40%, by using machine learning. And we're now applying that within QuickBooks. >> I'd like you to reduce my tax liability by about 40%. (Jeff laughs) If we can (chuckles) take care of that and I'm yours. >> Or at least-- >> Well, listen-- >> Or at least get you to the July deadline. (John laughs) >> If you just make less income-- (Jeff laughing) >> That's right. >> I'm sure that's doable. (Sasan laughs) >> If you don't make it, you don't pay it. >> Sasan: That's right (chuckles). >> You mentioned ESPN earlier about the stage and all that. You made top plays today, no doubt about it with the keynotes address. >> Sasan: Oh, thank you-- >> Job very well done. >> Thank you very much. >> Jeff: Cute Kim's (mumbles) coming. >> Sasan: Thank you. >> And thank you (Jeff laughs) for joining us here on theCUBE. We appreciate the time-- >> Thank you, thank you for having me. >> John: You bet. Back with more-- >> Alright, thanks. QuickBooks Connect 2016 here in San Jose. You're watching theCUBE. (upbeat pop music)