>>from the Cube Studios in Palo Alto and Boston. It's the Cube covering empowering the autonomous enterprise brought to you by Oracle Consulting. >>Welcome back to the Cube, everybody. This is a special digital presentation sponsored by Oracle Consulting. We go out to the events, we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of or consulting. Stephanie Trunzo is here. She's the head of transformation and offerings. North America. Stephanie, good to see >>you. Good to see you. >>Okay, so we talked about sort of the mission of Oracle Consulting. Now let's get into it and talk about what some of the customers we're seeing. There's this theme in the industry that Gartner brought about by motor. Like you guys are talking about Tri Motor like, Yeah. So what is that? All of the >>well, two wasn't good enough. >>So we had 1/3. >>So my model I t to speed I t The idea there is. A lot of modern enterprises are struggling with this challenge between the systems of record that they have that are have to be sources of truth. They're often slow to change. There's a lot of rigor around transfer, forming those systems of record. And then on the second side, on the bi model side, there are the systems of interaction or systems of engagement. They're sometimes called, and those systems are things like the applications where there's users, customers at the other end and they need to move at the speed of business. And so the idea of bi modal i t. And what a lot of our clients are struggling with currently is how do you serve both of those needs? At the same time, there's complications in the process is the tools and certainly in the budget. And at the same time, there's kind of looming out there This, you know, threat almost that if you aren't in ai ml data driven world yet, you're going to fall behind. And so our clients are struggling with the fact that they have not yet successfully addressed by motile I t but still have to figure out how to get into this ai space. So our third system hence try model I t is the systems of intelligence. >>The third piece obviously relates to machine intelligence Ai nml it seems like that type of capability would apply to both systems of record and systems of engagement. Is that is that how you're looking? >>Yes, and so the try motile i t concept is kind of three different systems and how they interlock and relate to one another. If you think about systems of record the currency, so to speak, for systems of record or processes. If you think about the currency for systems of interaction, it's the people. It's the users. It's the humans and the system. The currency for the system of intelligence is data to your point. So when you're talking about systems of intelligence, collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward. >>And that's the common thread between all three, and it just seems to me that is ultimately the underpinning of modernization. I wonder what your customers how do they view and how do you view modernization? >>So the awesome thing about being at Oracle is data is our DNA. That's where Oracle started from. That's where we still are today is data underpins everything we dio all of the technology that we build is built on the understanding that it must be data driven. And so when we're looking at all three of those systems and you're looking at it from an Oracle perspective, data is at the heart of even systems of record of even systems of interaction, not only the systems of intelligence. When our clients are looking at modernization, they're trying to figure out a way to kind of leap frogged this story and get the whole way to a place where they're getting intelligence and insights out of their data. They're not just unlocking it. They're not just moving workloads in a lift and shift kind of model. They're doing it because they want to serve the ultimate outcome that they get smarter as a business >>club. Customers want to go from where they are today to some outcome, and I want to spend a $1,000,000,000 they don't want to disrupt their business. They have to make investments clearly. How do they get from point A to point B on that cloud journey? >>So we've built something called the Cloud Evolution Framework. That cloud evolution framework has several different phases and stages, and it's intended to be kind of a skeleton toe have that conversation with clients. Are you thinking about all of the things you need to consider to make a healthy decision that has a real road map behind it? To your point on budget? And this is part of the Tri Motility conversation is they're struggling. I've talked to so many CIOs who are struggling to figure out I right now I'm spending 90% of my spend is on maintenance of systems versus on innovation. So how do I shift that spending story to something that's actually going to move the needle on getting the business ahead? That's going to serve my stakeholders, who are the lines of business in a way that is not additive to my budget but actually a shift of the budget. And so we're looking at from a cloud perspective, helping our clients make that monetary shift. Make the shift of the budget where they're self financing their own innovation by getting smarter and faster on moving their workloads to the cloud. >>Because use this concept and others do as well of the autonomous enterprise, you have autonomous database drill into that get passed the buzzwords. What is the autonomous enterprise and what's Oracle's fit there? >>Yeah, I think one of the big misconceptions when people hear autonomous is that they think it means without people, and that's not right. So autonomous means that you're helping elevate all the parts of the system to their highest value, which means you don't need to worry about security patches. You don't need to worry about repairing things on the database. Those kinds of autonomous things is, is the technology helping heal and serve itself? That doesn't mean you don't need people anymore. What it means is two things you need the experts that can help make sure that you're optimizing the value you get out of the autonomous tooling. But it also means that the humans are now freed up to do different kinds of high value work. So an autonomous enterprise would be one where they're really sort of self actualized in the sense that their technology is feeding itself. It's getting smarter and they're getting insights out of that so that the people in their business are as valuable as they can be. Leveraging the insights from the technology, >>I can see how that trickles into I t. no question about it. You can get the autonomous I T organization trickle into the autonomous enterprise, and I know it's early days, but >>so these kinds of transformations, I believe, are fundamentally across the whole company. And this is true at Oracle as well we have. We have something called Oracle at Oracle, and it's about drinking our own champagne and applying our own technology in house. So it's not just in an I T organization capacity. It's across, you know, HR procurement, legal, every supporting function that you can imagine so that cultural change bleeds out across the entire body of the company. And I believe fully that if you're going after something like an AI mission or an autonomous enterprise, you know, state, which is an evolution that you need to involve everyone in the company in different roles. >>So what's that future state look like? >>I think the future state looks like, ah, place where you're not just getting incremental gains on business processes or task that already exist. Your fundamentally seeing shifts in the way the business runs itself as a result of the technology learning and getting smarter, and the people who were benefiting from that technology, changing the way they operate in the company as well. >>Try model. We watching Stephanie. Thanks so much. >>Absolutely Thanks. >>Thank you for watching you watching the Cube at the special digital presentation. We'll be right back right after this short break.

>>From the cube studios in Palo Alto in Boston. It's the cube covering empowering the autonomous enterprise brought to you by Oracle consulting. >>Welcome back to the cube everybody. This is a special digital presentation sponsored by Oracle consulting. We go out to the events, we extract the signal from the noise and we're going to multiple locations to really try to understand better. The rebirth of Oracle consulting. Stephanie Trunzo is here. She's the head of transformation and offerings at Oracle consulting North America. Stephanie, good to see you. Good to see you. Okay, so we talked about sort of the mission of Oracle consulting. Now let's get into it and talk about what some of the customers are seeing. There's this theme in the industry that Gardner brought up about bi-modal it. You guys are talking about try mode lights, so what is that all about? >>Well, two wasn't good enough, so we had to add a third. So bi-modal it, two-speed it. The idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that are have to be sources of truth. They're often slow to change. Um, there's a lot of rigor around transfer forming those systems of record. And then on the second side, on the bi-modal side, there are the systems of interaction or systems of engagement they're sometimes called. And those systems are things like the applications where there's um, users, customers at the other end and they need to move at the speed of business. And so the idea of bi-modal it and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time, there's complications in the processes, the tools, and certainly in the budget. And at the same time there's kind of looming out there this, you know, threat almost that if you aren't in the AI ML data-driven world yet you're going to fall behind. And so our clients were struggling with the fact that they have not yet successfully addressed by modal it, but still have to figure out how to get into this AI space. So our third system, hence trimodal it is the systems of intelligence. >>This is the third piece that obviously relates to machine intelligence, AI. And ML. It seems like that type of capability would apply to both systems of record and systems of engagement. Is that, is that how you're doing? >>Yes. And so the tri modal it concept is kind of three different systems and how they interlock and relate to one another. If you think about systems of record, the currency, so to speak, for systems of record or processes. If you think about the currency for systems of interaction, it's the people, it's the users, it's the humans and the cysts. The currency for the system of intelligence is data. To your point. So when you're talking about systems of intelligence collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward. >>And that's the common thread between all three. And it just seems to me that is ultimately the underpinning of I wonder what do your customers, how do they view and how do you view modernization? >>So the awesome thing about being at Oracle is data is our DNA. That's where Oracle started from. That's where we still are today is data underpins everything we do. All of the technology that we build is built on the understanding that it must be data driven. And so when we're looking at all three of those systems and you're looking at it from an Oracle perspective, data is at the heart of even systems of record, of even systems of interaction, not only the systems of intelligence. When our clients are looking at modernization, they're trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they're getting intelligence and insights out of their data. They're not just unlocking it, they're not just moving workloads in a lift and shift kind of model. They're doing it because they want to serve the ultimate outcome that they get smarter as a business. >>Talk about cloud. Customers want to go from where they are today to some outcome, some endpoint, and they don't want to spend a zillion dollars and they don't want to disrupt their business. They're going to have to make investments clearly. How do they get from point a to point B on that cloud journey? >>So we've built something called the cloud evolution framework. That cloud evolution framework has several different phases and stages and it's intended to be a kind of a skeleton to have that conversation with clients. Um, are you thinking about all of the things you need to consider to make a healthy decision that has a real roadmap behind it? To your point on budget, and this is part of the tri modal it conversation is they're struggling. I've talked to so many CEOs who are struggling to figure out, I, right now I'm spending, you know, 90% of my spend is on maintenance of systems versus on innovation. So how do I shift that spending story to something that's actually gonna move the needle on getting the business ahead that's going to serve my stakeholders? Who are the lines of business in a way that is, um, not additive to my budget, but actually a shift of the budget. And so we're looking at, from a cloud perspective, helping our clients make that monetary shift, make the shift of the budget where they're self financing their own innovation by getting smarter and faster on moving their workloads. To the, >>you guys use this concept and others do as well of the autonomous enterprise. You have autonomous database. I wonder if we could drill into that path, get past the buzzwords. What is the autonomous enterprise and what's the Oracle's fit there? >>Yeah, I think one of the big misconceptions when people hear autonomous is that they think it means without people. And that's not right. So autonomous means that you're helping elevate all the parts of the system to their highest value, which means you don't need to worry about security patches. You don't need to worry about repairing things on the database. Um, those kinds of autonomous things is, is the technology helping heal and itself? That doesn't mean you don't need people anymore. What it means is two things. You need the experts that can help make sure that you're optimizing the value you get out of the autonomous tooling. But it also means that the humans are now freed up to do different kinds of high value work. So an autonomous enterprise would be one where they're really sort of self actualized in the sense that their technology is feeding itself. It's getting smarter and they're getting insights out of that so that the people in their business are as valuable as they can be. Leveraging the insights from the technical. >>So I can see how that trickles into it. No question about it. Can, can the autonomous it organization trickle into the autonomous enterprise? And I mean, I know it's sort of early days, but how do you see that? >>So the, these kinds of transformations I believe are fundamentally across the whole company. And this is true at Oracle as well. We have, um, we have something called Oracle at Oracle and it's about drinking our own champagne and applying our own technology in house. So it's not just in an it organization capacity, it's across, you know, HR, procurement, legal, every supporting function that you can imagine. Um, so that cultural change bleeds out across the entire body of the company. And I, I believe fully that if you're going after something like an AI mission or an autonomous enterprise, you know, state which is an evolution that you need to involve everyone in the company in different roles. >>So what's that future state look like? >>I think the future state looks like a place where you're not just getting, um, incremental gains on business processes or tasks that already exist. You're fundamentally, um, seeing shifts in the way the business runs itself as a result of the technology learning and getting smarter and the people who are benefiting from that technology changing the way they operate in the company as well. >>Trimodal it will be watching, right. Stephanie, thanks so much. It's great. Thank you for watching. You're watching the cube at the special digital presentation. We'll be right back right after this short break.

>>  Welcome back to theCUBE everybody. This is a special digital presentation sponsored by Oracle Consulting. We go out to the events, we extract the signal from the noise and we're going to multiple locations to really try to understand better the rebirth of Oracle Consulting. Stephanie Trunzo is here. She is the head of transformation and offerings at Oracle consulting North America. Stephanie, good to see you. >> Yeah, good to see you. >> Okay so we talked about sort of the mission of Oracle Consulting, now let's get into it and talk about some of what the customers are seeing. There's this theme in the industry that Gartner brought up about Bimodal IT and you guys are talking about Trimodal IT, so what is that all about? >> Well, two wasn't good enough so we had to add a third. (laughs) So Bimodal IT, two speed IT, the idea there is a lot of modern enterprises are struggling with this challenge between the systems of record that they have that have to be sources of truth. They're often slow to change. There's a lot of rigger around transforming those systems of record. And then on the second side, on the Bimodal side, there are the systems of interaction or systems of engagement, they're sometimes called. And those systems are things like the applications where there's users, customers at the other end. And they need to move at the speed of business. And so the idea of Bimodal IT and what a lot of our clients are struggling with currently is how do you serve both of those needs at the same time? There's complications in the processes, the tools, and certainly in the budget. And at the same time, there's kind of looming out there, this threat almost, that if you aren't in the AI NML data driven world yet, you're going to fall behind. And so our clients are struggling with the fact that they have not yet successfully addressed Bimodal IT, but still have to figure out how to get into this AI space. So our third system, hence Trimodal IT is the systems of intelligence. And that's what we've added. >> So, to make sure I've got the Bimodal right, >> Yeah sure. >> Is that, You've got people who are handling the systems of record you said. And so they have knowledge, they've got tribal knowledge, deep expertise, which may not be widespread. Kids coming out of school don't necessarily have that same expertise. And then there's sort of the systems of engagement kind of the new fun stuff. Did customers in your sense, buy into that? Or did they try to sort of cross-pollinate, as practitioners? >> Yeah they do buy into it. But they're really still struggling with the idea of Bimodal IT without even getting into the third system yet. So they are buying into it. The challenge, it's not even really about buying into it. It's addressing the challenge, because they have to overcome this legacy stuff, that they have in their system in order to address the speed of business. >> So the third piece, obviously relates to machine intelligence, AI, NML. It seems like that type of capability would apply to both systems of record and systems of engagement. Is that how you're looking at it? >> Yes, and so the Trimodal IT concept is kind of three different systems and how they interlock and relate to one another. If you think about systems of record, the currency, so to speak, for system of record are processes. If you think about the currency for systems of interaction it's the people, it's the users, it's the humans. And the currency for the system of intelligence is data, to your point. So when you're talking about systems of intelligence, collecting and leveraging data from all three systems is going to be what fuels your system of intelligence going forward. >> And that's the common thread between all three. And it just seems to me, that is ultimately the underpinning of modernization. I wonder what your customers, how do they view, and how do you view modernization? >> So the awesome thing about being at Oracle is data is our DNA. That's where Oracle started from, that's where we still are today is data underpins everything we do, all of the technology that we build is built on the understanding that it must be data-driven. And so when we're looking at all three of those systems and you're looking at it from an Oracle perspective, data is at the heart of even systems of record. Even systems of interaction, not only the systems of intelligence. When our clients are looking at modernization, they are trying to figure out a way to kind of leapfrog this story and get the whole way to a place where they are getting intelligence and insights out of their data. They're not just unlocking it. They're not just moving workloads in a lift and shift kind of model. They're doing it, because they want to serve the ultimate outcome that they get smarter as a business. >> So data is kind of like raw material, the AI or machine intelligence allows you to take data and create insights, if you will. And then cloud gives you scale and agility and all of those things. So Cloud's again another fundamental piece of, just from an infrastructure standpoint, and I think you guys define Cloud as sort of an experience, not a place. So it includes the on prime workloads, of course. So, talk about Cloud. Customers want to go from where they are today, to some outcome, some end point. And they don't want to spend a zillion dollars. And they don't want to disrupt their business. They are going to have to make investments, clearly. How do they get from point A to point B on that Cloud journey? >> So we've built something called a Cloud evolution framework. That Cloud evolution framework has several different phases and stages. And it's intended to be a skeleton to have that conversation with clients. Are you thinking about all of the things that you need to consider to make a healthy decision that has a real road map behind it. To your point on budget, and this is part of the Trimodal IT conversation is. They're struggling, I've talked to so many CIOs who are struggling to figure out. I right now am spending, 90% of my spend is on maintenance of systems versus on innovation. So how do I shift that spending story to something that is actually going to move the needle on getting the business ahead. That's going to serve my stakeholders, who are the lines of business, in a way that is not additive to my budget. But actually a shift of the budget. So we're looking at it from a Cloud perspective, helping our clients make that monetary shift. Make the shift of the budget where they're self-financing their own innovation by getting smarter and faster on moving their workloads to the Cloud. >> That's interesting, I want to come back to that self-financing. It reminds me of Y2K where you had all these activities going on, and the boom times. And then people wanted to go through an application rationalization exercise so they could self-fund really the innovation. >> Stephanie: Right. >> And when you're in the tenth year of a boom cycle, here. I wonder if there are similar things going on. Is that where the self-funding comes in? >> That's exactly it. So, I kind of use this example as a way of helping people consume and understand this. Marie Kondo, KonMari method is a popular, she wrote a best-selling book. She's on Netflix. The premise of her concept is helping to declutter your life. And her premise is you should hold each object in your hand and say, "Does it bring me joy?" And if it does, I'm going to keep it. And if it doesn't, I'm going to thank it for it's service, and get rid of it. And so we're talking to our clients about something very similar. You said, rationalization exercise and it's precisely the same thing. We're kind of using the KonMari method, if you will, to help our clients make those determinations. What are the things that they still need? What are the things that they can de-commission? What are the things that can stay where they are? And you don't have to do anything with, because they are serving the purpose just fine. >> Yeah, we're kind of hoarders by nature, and creatures of habit, so you have all these applications that nobody's using, but you're still spending maintenance and-- >> Stephanie: Correct. >> Keeping them up and it may not be delivering, and many aren't delivering value to the organization. So you want to double down on those that do. You guys use this concept and other do as well, of the autonomous enterprise. You have the autonomous database, I wonder if we could drill into that. Get passed the buzz words. What is the autonomous enterprise and what is Oracle's fit there? >> Yeah, I think one of the big misconceptions when people here autonomous, is that they think it means without people. And that's not right. (laughs) So, autonomous means that you're helping elevate all the parts of the system to their highest value. Which means, you don't need to worry about security patches. You don't need to worry about repairing things on the database. Those kinds of autonomous things is the technology helping heal and serve itself. That doesn't mean you don't need people anymore. What it means is two things. You need the experts that can help make sure that you're optimizing the value you get out of the autonomous tooling, but it also means that the humans are now freed up to do different kinds of high value work. So, an autonomous enterprise would be one where they're really sort of self-actualized. In the sense that their technology is feeding itself. It's getting smarter, and they're getting insights out of that, so that the people in their business are as valuable as they can be, leveraging the insights from the technology. >> So I can see how that trickles into IT. No questions about it. Can the autonomous IT organization trickle into the autonomous enterprise? And I mean I know it's sort of early days, but how do you see that shaping up? >> So, these kind of transformations, I believe are fundamentally across the whole company. And this is true at Oracle as well. We have something called Oracle@Oracle. And it's about drinking our own champagne and applying our own technology in house. So it's not just in an IT organization capacity. It's across HR, Procurement, Legal, every supporting function you can imagine. So that cultural change bleeds out across the entire body of the company. And I believe fully that if you're going after something like an AI mission or an autonomous enterprise state, which is an evolution that you need to involve everyone in the company in different roles. >> So what's that future state look like? >> I think the future state looks like a place where you're not just getting incremental gains on business processes or tasks that already exist. You're fundamentally seeing shifts in the way the business runs itself, as a result of the technology learning and getting smarter. And the people who are benefiting from that technology changing the way they operate in the company as well. >> So you mentioned the sort of decluttering example before, which I love, I'm getting that book. And are there other examples that inspire you? >> There are. So there was an anecdote, a client told me this story, which is a fantastic story, kind of triggered a thought for me. Told a story about a guy who was retiring. And at his retirement dinner, he told a story that 30 years ago when he started at the company. He remembers his dad teaching him, how to use the application that he then spent his entire career building and maintaining. As I heard that story, and they jokingly said at this point, our only solution is to get him out of retirement or find his son. (laughs) I thought about that, and I thought about 23 and me. You know 23 and me? >> Yes. >> So it's a DNA testing, tells you your heritage, lineage. And we're kind of at a state now, where a lot of our enterprise clients legitimately have these systems of record applications that are generations old, human generations old. So getting into the weeds on what that looks like, I've been telling clients pretty often lately. Institutional knowledge is the enemy, right? It's the enemy of the autonomous enterprise. If you have a challenge where you keep referring to the same name (laughs). If Bob leaves, we're in big trouble. If Sally isn't here anymore, that's a trigger for you to know that that's something you need to pay attention to. Because that institutional knowledge is not getting built into your technology. >> So what do you guys do? Do you put some kind of abstraction layer around that system of record, so that it can be automated? Is that part of what you do? >> Sure. So we're looking at, there's a couple different ways you can go about it. So you can look at the systems of record as a partial move that you do over time to the Cloud. And so you have to be pretty smart about the pattern and how you do that. Moving the workloads, kind of whole, will give you a little bit of that self-financing ability to dig in deeper and start transforming them. >> Okay, Trimodal IT. We'll be watching. (laughs) All right, Stephanie, thanks so much. It was great to see you. >> Absolutely, thanks. >> And thank you for watching. You're watching theCUBE at the special digital presentation. We'll be right back after this short break. (upbeat electronic music)

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS reInvent 2019. Brought to you by Amazon Web Services and Intel along with it's Ecosystem partners. >> Well, welcome back, everyone theCUBE's live coverage in Las Vegas for AWS reInvent. It's theCUBE's 10th year of operations, it's our seventh AWS reInvent and every year, it gets better and better and every year, we've had theCUBE at reInvent, Jerry Chen has been on as a guest. He's a VIP, Jerry Chen, now a general partner at Greylock Tier One, one of the leading global Venture capitals at Silicon Valley. Jerry, you've been on the journey with us the whole time. >> I guess I'm your good luck charm. >> (laughs) Well, keep it going. Keep on changing the game. So, thanks for coming on. >> Jerry: Thanks for having me. >> So, now that you're a seasoned partner now at Greylock. You got a lot of investments under your belt. How's it going? >> It's great, I mean look, every single year, I look around the landscape thinking, "What else could be coming? "What if we surprise this year?" What's the new trends? What both macro-trends, also company trends, like, who's going to buy who, who's going to go public? Every year, it just gets busier and busier and bigger and bigger. >> All these new categories are emerging with this new architecture. I call it Cloud 2.0, maybe next gen Cloud, whatever you want to call it, it's clear visibility now into the fact that DevOps is working, Cloud operations, large scale operations with Cloud is certainly a great value proposition. You're seeing now multiple databases, pick the tool, I think Jassy got that right in his keynote, I believe that, but now the data equation comes over the top. So, you got DevOps infrastructure as code, you got data now looking like it's going to go down that same path of data as code where developers don't have to deal with all the different nuances of how data's stored, how it's handled, where is it, warm or cold or at glacier. So, developers still don't have that yet today. Seems to be an area of Amazon. What's your take on all this? >> I think you saw, so what drove DevOps? Speed, right? It's basically how developers shows you operations, merging of two groups. So, we're seeing the same trend DataOps, right? How data engineers and data scientists can now have the same speeds developers had for the past 10 years, DataOps. So, A, what does that mean? Give me the menu of what I want like, Goldilocks, too big, too small, just right. Too hot, too cold, just right. Like, give me the storage tier, the data tier, the size I want, the temperature I want and the speed I want. So, you're seeing DataOps give the same kind of Goldilocks treatment as developers. >> And on terms of like Cloud evolution again, you've seen the movie from the beginning at VM where now through Amazon, seventh year. What jumps out at you, what do you look at as squinting through the trend lines and the fashion of the features, it still seems to be the same old game, compute memory storage and software. >> Well I mean, compute memory storage, there's an atomic building blocks of a compute, right? So, regardless of services these high level frameworks, deep down, you still have compute networking and storage. So, that's the building blocks but I think we're seeing 10th year of reInvent this kind of, it's not one size fits all but this really big fat long tail, small instances, micro-instances, server lists, big instances for like jumbo VMs, bare metal, right? So, you're seeing not one architecture but folks can kind of pick and choose buy compute by the drip, the drop or buy compute by the whole VM or whole server full. >> And a lot of people are like, the builders love that. Amazon owns the builder market. I mean, if anyone who's doing a startup, they pretty much start on Amazon. It's the most robust, you pick your tools, you build, but Steve Malaney was just on before us says, "Enterprise don't want power tools, "they're going to cut their hand off." (laughs) Right so, Microsoft's been winning with this approach of consumable Cloud and it's a nice card to play because they're not yet there with capabilities with Amazon, so it's a good call, they got an Enterprise sales force. Microsoft playing a different game than AWS because they have to. >> Sure I mean, what's football now, you have a running game, you need a passing game, right? So, if you can't beat them with the running game, you go with a passing game and so, Amazon has kind of like the fundamental building blocks or power tools for the builders. There's a large segment of population out there that don't want that level of building blocks but they want us a little bit more prescriptive. Microsoft's been around Enterprise for many many years, they understand prescriptive tools and architectures. So, you're going to become a little bit more prefab, if you will. Here's how you can actually construct the right application, ML apps, AI apps, et cetera. Let me give you the building blocks at a higher level abstraction. >> So, I want to get your take on value creations. >> Jerry: Sure. >> So, if it's still early (mumbles), it's took a lot more growth, you start to see Jassy even admit that in his keynotes that he said quote, "There are two types "of developers and customers. "People want the building blocks "or people who want solutions." Or prefab or some sort of more consumable. >> More prescriptive, yeah. >> So, I think Amazon's going to start going that way but that being said, there's still opportunities for startups. You're an investor, you invest in startups. Where do you see opportunities? If you're looking at the startup landscape, what is the playbook? How should you advise startups? Because ya know, have the best team or whatever but you look at Amazon, it's like, okay, they got large scale. >> Jerry: Yeah. >> I'm going to be a little nervous. Are they going to eat my lunch? Do I take advantage of them? Do I draft off them? There are wide spaces as vertical market's exploding that are available. What's your view on how startups should attack the wealth creation opportunity value creation? >> There, I mean, Amazon's creating a new market, right? So, you look at their list of many services. There's just like 175 services out there, which is basically too many for any one company to win every single service. So, but you look at that menu of services, each one of those services themselves can be a startup or a collection of services can be a startup. So, I look at that as a roadmap for opportunity of companies can actually go in and create value around AI, around data, around security, around observability because Amazon's not going to naturally win all of those markets. What they do have is distribution, right? They have a lot of developer mind share. So, if you're a startup, you play one or three themes. So like, one is how do I pick one area and go deep for IP, right? Like, cheaper, better, faster, own some IP and though, they're going to execute better and that's doable over and over again in different markets. Number two is, we talked about this before, there's not going to be a one Cloud wins all, Amazon's clearly in the lead, they have won most of the Cloud, so far, but it'll be a multi-Cloud world, it'll be On Premise world. So, how do I play a multi-Cloud world, is another angle, so, go deep in IP, go multi-Cloud. Number three is this end to end solution, kind of prescriptive. Amazon can get you 80% of the way there, 70% of the way there but if you're like, an AI developer, you're a CMO, you're a marketing developer, you kind of want this end to end solution. So, how can I put together a full suite of tools from beginning to end that can give me a product that's a better experience. So, either I have something that's a deeper IP play a seam between multiple Clouds or give it end to end solutions around a problem and solve that one problem for our customer. >> And in most cases, the underlay is Amazon or Azure. >> Or Google or Alley Cloud or On Premises. Not going to wait any time soon, right? And so, how do I create a single fabric, if you will that looks similar? >> I want to riff with you in real time here on theCUBE around data. So, data scale is obviously a big discussion that's starting to happen now, data tsunami, we've heard that for years. So, there's two scale benefits, horizontal scale with data and then vertical specialism, vertical scale or ya know, using AI machine learning in apps, having data, so, how do you view that? What's your reaction to the notion of creating the horizontal scale value and vertical specialism value? >> Both are a great place for startups, right? They're not mutually exclusive but I think if you go horizontal, the amount of data being created by your applications, your infrastructure, your sensors, time stories data, ridiculously large amount, right? And that's not going away any time soon. I recently did investment in ChronoSphere, 'cause you guys covered over at CUBEcon a few weeks ago, that's talking about metrics and observability data, time stories data. So, they're going to handle that horizontal amount of data, petabytes and petabytes, how can we quarry this quickly, deeply with a lot of insight? That's one play, right? Cheaper, better, faster at scale. The next play, like you said, is vertical. It's how do I own data or slice the data with more contacts than I know I was going to have? We talked about the virtual cycle of data, right? Just the system of intelligence, as well. If I own a set of data, be it healthcare, government or self-driving car data, that no one else has, I can build a solution end to end and go deep and so either pick a lane or pick a geography, you can go either way. It's hard to do both, though. >> It's hard for startup. >> For a startup. >> Any big company. >> Very few companies can do two things well, startups especially, succeed by doing one thing very well. >> I think my observation is that I think looking at Amazon, is that they want the horizontal and they're leaving offers on the table for our startups, the vertical. >> Yeah, if you look at their strategy, the lower level Amazon gets, the more open-sourced, the more ubiquitous you try to be for containers, server lists, networking, S3, basic sub straits, so, horizontal horizontal, low price. As you get higher up from like, deep mind like, AI technologies, perception, prediction, they're getting a little bit more specialized, right? As you see these solutions around retail, healthcare, voice, so, the higher up in the stack, they can build more narrow solutions because like any startup of any product, you need the right wedge. What's the right wedge in the customers? At the base level of developers, building blocks, ubiquitous. For solutions marketing, healthcare, financial services, retail, how do I find a fine point wedge? >> So, the old Venture business was all enamored with consumers over the years and then, maybe four years ago, Enterprise got hot. We were lowly Enterprise guys where no one-- >> Enterprise has been hot forever in my mind, John but maybe-- >> Well, first of all, we've been hot on Enterprise, we love Enterprise but then all of a sudden, it just seemed like, oh my God, people had an awakening like, and there's real value to be had. The IT spend has been trillions and the stats are roughly 20 or so percent, yet to move to the Cloud or this new next gen architecture that you're investing companies in. So, a big market... that's an investment thesis. So, a huge enterprise market, Steve Malaney of Aviation called it a thousand foot wave. So, there's going to be a massive enterprise money... big bag of money on the table. (laughs) A lot of re-transformations, lot of reborn on the Cloud, lot of action. What's your take on that? Do you see it the same way because look how they're getting in big time, Goldman Sachs on stage here. It's a lot of cash. How do you think it's going to be deployed and who's going to be fighting for it? >> Well, I think, we talked about this in the past. When you look to make an investment, as a startup founder or as a VC, you want to pick a wave bigger than you, bigger than your competitors. Right so, on the consumer side, ya know, the classic example, your Instagram fighting Facebook and photo sharing, you pick the mobile first wave, iPhone wave, right, the first mobile native photo sharing. If you're fighting Enterprise infrastructure, you pick the Cloud data wave, right? You pick the big data wave, you pick the AI waves. So, first as a founder startup, I'm looking for these macro-waves that I see not going away any time soon. So, moving from BaaS data to streaming real time data. That's a wave that's happening, that's inevitable. Dollars are floating from slower BaaS data bases to streaming real time analytics. So, Rocksett, one of the investors we talked about, they're riding that wave from going BaaS to real time, how to do analytics and sequel on real time data. Likewise, time servers, you're going from like, ya know, BaaS data, slow data to massive amounts of time storage data, Chronosphere, playing that wave. So, I think you have to look for these macro-waves of Cloud, which anyone knows but then, you pick these small wavelettes, if that's a word, like a wavelettes or a smaller wave within a wave that says, "Okay, I'm going to "pick this one trend." Ride it as a startup, ride it as an investor and because that's going to be more powerful than my competitors. >> And then, get inside the wave or inside the tornado, whatever metaphor. >> We're going to torch the metaphors but yeah, ride that wave. >> All right, Jerry, great to have you on. Seven years of CUBE action. Great to have you on, congratulations, you're VIP, you've been with us the whole time. >> Congratulations to you, theCUBE, the entire staff here. It's amazing to watch your business grow in the past seven years, as well. >> And we soft launch our CUBE 365, search it, it's on Amazon's marketplace. >> Jerry: Amazing. >> SaaS, our first SaaS offering. >> I love it, I mean-- >> John: No Venture funding. (laughs) Ya know, we're going to be out there. Ya know, maybe let you in on the deal. >> But now, like you broadcast the deal to the rest of the market. >> (laughs) Jerry, great to have you on. Again, great to watch your career at Greylock. Always happy to have ya on, great commentary, awesome time, Jerry Chen, Venture partner, general partner of Greylock. So keep coverage, breaking down the commentary, extracting the signal from the noise here at reInvent 2019, I'm John Furrier, back with more after this short break. (energetic electronic music)