(upbeat music) >> Welcome to theCUBE's coverage of HPE Discover 2021. I'm Lisa Martin. Robert Christiansen joins me, one of our alumni the VP of Strategy in the Office of the CTO at HPE. Robert, it's great to see you, welcome back to the program. >> It's nice being here, Lisa. Thank you so much for having me. >> So here we are still in this virtual world. Things are opening up a little bit, which is nice but one of the things I'm excited to talk to you about today is Edge to Cloud from the customer's perspective. Obviously, that's why HPE does what it does for its customers. So let's talk about some of the things that you see from your perspective, with respect to data. We can't have a Cube conversation without talking about data, there's more and more of it, value but getting access to it quickly, getting access to it in real-time and often cases to make data-driven decisions is a challenging thing to do. Talk to me about what you see from the customer's lens. >> Well, the customer at a very highest level from the board level on down they're saying, "Hey, what is our data strategy? How are we going to put the value of data in place? Are we going to have it manifest its value in an internal fashion where it makes us run better as an organization? Can we get cost improvements? Can we move quicker with that? And then can we monetize that data if it's like very specific to an industry like healthcare or pharma or something like that? Can we expose that data to the rest of the world and give them access into what we call like data sets?" And there's a lot of that going on right now too. So we're seeing these two different angles about how they're going to manage and control that data. And you were talking about, and you mentioned it, you know the Edge related focus around that. You know, the Edges where business is done is where people actually do the transaction whether it's in a healthcare like in a hospital or a manufacturing facility et cetera. And then, but that data that they're using at that location is really important to make a decision at that location. They can't send it back to a Cloud. They can't send it back to someplace, wait for a decision to happen and then shoot it back again and say, "Hey, stop the production line because we found a defect." You need to act at that moment which the clients are saying, "Hey, can you improve my reliability? Can you give me better SLS? Can you improve the quality of my products? Can you improve healthcare in a hospital by immediate decisions?" And that is a data problem. And that requires the movement of compute and networking and storage and fundamentally the core piece of HPE's world. But in addition to that, the software necessary to take the action on that data when they detect that there's some action that needs to be taken. >> And I mentioned a minute ago, you know real-time and we've learned in the last 15 months plus. One of the things we learned is for a lot of cases, access to real-time data is no longer a nice to have. It's really going to be something, an element that separates those that succeed versus those that aren't as competitive. But I want to talk about data from a consumption perspective consumers, producers, obviously, meeting to ensure that the data consumers have what they need, what is it? What is your thought when you talk with customers, the consumers versus the producers? >> Yeah, that's a great question, Lisa. One of the key fundamental areas that HPE and the Office of the CTO has really been focused on over the last six months is something that we call data spaces and that is putting in place a platform, a set of services that connect data consumers with data producers. And when you think about that, that really isn't nothing new. I mean, you could go all the way back, if you've been around for a while remember the company called TRW and they used to have credit reporting, and they used to sell that stuff. And then it moved into Experian and those things. But you've got Bloomberg and next LexisNexis and all these companies that sell data. And they've been doing it, but it's very siloed. And so the explosion of data, the valuableness the value of the data for the consumers of it has put the producers in a position where they can't readily be discovered. And whether it be a private source of data like an IoT device and an industrial control, or a set of data that might say, "Hey, here's credit card for our data on a certain geography." Those sets need to be discovered, curated, and be made available to those who would want that. You know, for example, the folks that want to know how IoT device is working inside an industrial control or a company who's trying to lower their fraud rates on credit card transactions, like in stadiums or something like that. And so this discoverability in this space, or what you just talked about is such a core piece of what we're working on right now. And we haven't, our strategy is not only to just work on what HPE has to bring that and manifest that to the marketplace. But more importantly, how are we working with our partners to really bridge that gap and bring that next generation of services to those clients that can make those connections. >> So connecting and facilitating collaboration, absolutely key, as well as that seamless flow of data sharing without constraints. How are customers working with HPE and some of your partners to be able to create a data strategy, launch it, and start gleaning value from data faster than they can before? (Robert chuckles) >> This is the big question because it's a maturity curve. Organizations are in various states of what we call data maturity or data management maturity. They can be in very early stages. You know what we consider, you know, they just more worried about just maintaining the lights on DR strategies and make sure that data doesn't go away versus all the way through a whole cycle where they're actually governing it and putting it into what I call those discoverable buckets that are made available. And there's a whole life cycle about that. And so we see a big opportunity here for our A&PS and other professional services organizations to help people get up that maturity curve. But they also have to have the foundational tools necessary to make that happen. This is really where the Ezmeral product line or software applications really shines being able to give that undercarriage that's necessary to help that data maturity and the growth of that client to meet those data needs. And we see the data fabric being a key element to that, for that distributed model, allowing people to get access and availability to have a highly redundant, highly durable data fabric and then to build applications specifically as data-intensive applications on top of that with the Ezmeral platform all the way into our GreenLake solutions. So it's quite a journey here, Lisa. I want to just, point to the fact that HPE has done a really, really good job of positioning itself for the explosion of all of these data-intensive AI/ML workloads that are making their way into every single conversation every single enterprise to this day that wants to take advantage of the value of the data they have and to augment that data through other sources. >> One, when you think about data-intensive applications the first one that pops into my mind is Uber. And it's one of those applications that we just expect. We kind of think of as a taxi service when really it's logistics and transportation, but all of the data on the backend that it is organizing to find the ride for me at my location to take me where I'm going. The explosion of data-intensive applications is great but there's also so much more demand from consumers whether we're in business or we're consuming in our personal lives. >> It's so true and that's a very popular example. And you know, you think about the real-time necessity of what's the traffic patterns at the time I order my thing. Is it going to route me the right way? That's a very real consumer facing one, but if we click into our clients and where HPE very much is like the backbone of the global economy. We provide probably one third of the compute for the global economy and it's a staggering stat if you really think about it. Our clients, I was just talking with a client here earlier, very, very large financial services company. And they have 1200 data sets that have been selling to their clients globally. And a lot of these clients want to augment that data with their existing real-time data to come up with a solution. And so they merge it and they can determine some value through a model, an AI model. And so we're working hand-in-hand with them right now to give them that backbone so that they can deliver data sets into these other systems and then make sure they get controlled and secured. So that the company we're working with, our client has a deep sense of security that that data set is not going to find itself out into the wild somewhere. And uncontrolled for a number of reasons, from security and governance mind. But the number of use cases, Lisa are as infinite as the number of opportunities for people see value in business today. >> When you're talking about 1200 data sets that a company is selling, and of course there are many, many data sets that many types of companies consume. How do you work with them to ensure that they don't just proliferate silos, but that they get more of a unified data repository that they can act on? >> Yeah, that's a great question. A key tenant of the strategy at HPE is Open-source. So we believe in a hybrid, multi-Cloud environment meaning that as long as we all agree that we are going to standardize on Open-source technologies and APIs, we will be able to write and build applications that can natively run on any abstract platform. So for example, it's very important that we containerize, for example, and we use storage and data tools that adhere to Open standards. So if you think about that, if you write a Spark application you want that Spark application potentially to run on any of the hyperscalers, the Amazon's or the Microsoft to GCPS, or you want it to run on-premises and specifically like on HPE equipment. But the idea here is I consider one of our clients right now. I mean, think about that. One of our clients specifically ask that question that you just said. They said, "Hey, we are building out this platform, this next generation platform. And we don't want the lock-in. We want to be, we want to create that environment where that data and the data framework." So they use very specific Open -source data frameworks and they open, they use very specific application frameworks the software from the Open-source community. We were able to meet that through the Ezmeral platform. Give them a very high availability, five nines high availability, redundant, redundant geographically to geographic data centers to give them that security that they're looking for. And because of that, it's opened so many other doors for us to walk in with a Cloud strategy that is an alternative, not just the one bet to public Cloud but you haven't other opportunity to bring a Cloud strategy on-premises that is compatible with Cloud-native activities that are going on in the public Cloud. And this is at the heart of HPE strategy. I think it's just, it's been paying off. It continues to pay off. We just keep investing and keep moving down that path. I think we're going to be doing really well. >> It sounds to me that the strategy that HP is developing is highly collaborative and synergistic with your customers. Talk to me a little bit about that, especially in the last year, as we've seen a massive acceleration in digital transformation about the rapid pivot to work from home, the necessity to collaborate electronically. Talk to me a little bit about that yin and yang with HPE and its customers in terms of your strategy. >> Yeah, well, I think when COVID hit one of the very first things that just took off with VDI. Rohit Dixon and I were talking on a podcast we had earlier around the work from home strategy that was implemented almost immediately. Well, we had it already in the can, we already were doing it for many clients already but it went from like a three priority to a 12, 10 being the max. Super, super charged up on how do we get work from home secured, work from home applications and stuff in the hands of people doing, you know, when data sensitivity is super important, VDI kicks in that's on that side. But then if you start looking at the digital transformation that has to happen in the supply chain that's going on right now. The opening up of our economies it's been various starts and stops if you look around the globe. The supply chains have absolutely gone under a huge amount of pressure, because, unlike in the United States, everybody just wants everything now because things are starting to open up. I was talking to a meat packing company and a restaurant business a little while ago. And they said, "Everybody wants to order the barbecue. Now we can't get the meat for the barbecues 'cause everybody's going to the barbecues." And so the supply, this is a multi-billion dollar industry supplying meat to all of the rest of the countries and stuff like that. And so they don't have optics into that supply chain today. So they're immediately having to go through a digitization process, the transformation in something as what you would call as low tech as delivering meat. So no industry is immune, none anywhere in this whole process. And it will continue to evolve as we exit and change how we live our life going into these next couple of years. I think it's going to be phenomenal just to watch. >> Yeah, it's one of the things I call a COVID catalyst some of the silver linings that have come out of this 'cause I wouldn't have thought of the meatpacking industry as a technology field as well, but now thanks to you, I will. Last question for you. When customers in this dynamic world in which we're still living talk about Edge to Cloud are they working with you to develop a Cloud initiatives, Cloud mandates, Cloud everywhere? And if so, how do you help them start? >> Yeah, that's a great question. So again, it's like back into the data model, everybody has a different degree or a starting point that they will engage us with a strategy but specifically with what you're talking about. Almost everybody already has a Cloud strategy. So they may be at different maturity levels with that Cloud strategy. And there's almost always a Cloud group. Now, historically HPE has not had much of a foot in the Cloud group because they never really historically looked at us says that HPE is a Cloud company. But what's happened over the last couple of years with the acceleration of the acceptance of Cloud on-premises and GreenLake, specifically, and the introduction of Ezmeral and the Cloud-native infrastructure services and past layer stuff that's coming up through the Ezmeral product into our clients. It's immediately opened the door for conversations around Cloud that is available for what is staying on-premises which is in excess of 70% of the applications today. Now, if you were to take that now and extend that into the Edge conversation, what if you were able to take a smaller form factor of a GreenLake Cloud and push it more closer to an Edge location while still giving the similar capabilities, Cloud-native functions that you had before? When we're provocative with clients in that sense they suddenly open up and see the art of the possible. And so this is where we are really, really breaking down a set of paradigms of what's possible by introducing, you know, not just from the Silicon all the way up but the set of services all the way to the top of stack to the actual application that they're going to be running. And we say, "Hey, we can offer it to you in as a pay as you go model, we can get you the consumption models that are necessary, that lets you buy at the same way as the Cloud offers it. But more importantly, we'll be able to run it for you and provide you an abstraction out of that model. So you don't have to send your people out into the field to do these things. We have the software, the tools, and the systems necessary to manage it for you." But the last part is I want to be really really focused on when clients are writing that application for the Edge that matters. They are putting it into new Cloud-native architectures containers, microservices, they're using solid pipelines development pipelines, they've implemented what they call their DevOps or their DataOps practices in field, in country, if you would say. That's where we shine. And so we had a really, really good conversation start there. And so how we start that is we arrive with a set of blueprints to help them establish what that roadmap looks like. And then our professional services staff, or A&PS groups around the globe are really really set up well to help them take that trip. >> Wow, that's outstanding, Robert. We could have a whole conversation on HPE's transformation. Internet itself that was my first job in tech was at Hewlett Packard back in the day. But this has been really interesting, really getting it your vision of the customer's experience and the customer's perspective from the Office of the CTO. Great to talk to you, Robert. Thank you for sharing all that you did. This could have been a Part 2 conversation. >> Well, I'm hopeful then that we'll do Part 3 and 4 here as the months go by. So I look forward to seeing you again, Lisa. >> Deal, that's a deal. All right. >> All right. >> For Robert Christiansen, I'm Lisa Martin. You're watching theCUBE's coverage of HPE Discover 2021. (upbeat music)

(upbeat music) >> Welcome to theCUBE's coverage of HPE Discover 2021. I'm Lisa Martin. Robert Christiansen joins me, one of our alumni the VP of Strategy in the Office of the CTO at HPE. Robert, it's great to see you, welcome back to the program. >> It's nice being here, Lisa. Thank you so much for having me. >> So here we are still in this virtual world. Things are opening up a little bit, which is nice but one of the things I'm excited to talk to you about today is Edge to Cloud from the customer's perspective. Obviously, that's why HPE does what it does for its customers. So let's talk about some of the things that you see from your perspective, with respect to data. We can't have a Cube conversation without talking about data, there's more and more of it, value but getting access to it quickly, getting access to it in real-time and often cases to make data-driven decisions is a challenging thing to do. Talk to me about what you see from the customer's lens. >> Well, the customer at a very highest level from the board level on down they're saying, "Hey, what is our data strategy? How are we going to put the value of data in place? Are we going to have it manifest its value in an internal fashion where it makes us run better as an organization? Can we get cost improvements? Can we move quicker with that? And then can we monetize that data if it's like very specific to an industry like healthcare or pharma or something like that? Can we expose that data to the rest of the world and give them access into what we call like data sets?" And there's a lot of that going on right now too. So we're seeing these two different angles about how they're going to manage and control that data. And you were talking about, and you mentioned it, you know the Edge related focus around that. You know, the Edges where business is done is where people actually do the transaction whether it's in a healthcare like in a hospital or a manufacturing facility et cetera. And then, but that data that they're using at that location is really important to make a decision at that location. They can't send it back to a Cloud. They can't send it back to someplace, wait for a decision to happen and then shoot it back again and say, "Hey, stop the production line because we found a defect." You need to act at that moment which the clients are saying, "Hey, can you improve my reliability? Can you give me better SLS? Can you improve the quality of my products? Can you improve healthcare in a hospital by immediate decisions?" And that is a data problem. And that requires the movement of compute and networking and storage and fundamentally the core piece of HPE's world. But in addition to that, the software necessary to take the action on that data when they detect that there's some action that needs to be taken. >> And I mentioned a minute ago, you know real-time and we've learned in the last 15 months plus. One of the things we learned is for a lot of cases, access to real-time data is no longer a nice to have. It's really going to be something, an element that separates those that succeed versus those that aren't as competitive. But I want to talk about data from a consumption perspective consumers, producers, obviously, meeting to ensure that the data consumers have what they need, what is it? What is your thought when you talk with customers, the consumers versus the producers? >> Yeah, that's a great question, Lisa. One of the key fundamental areas that HPE and the Office of the CTO has really been focused on over the last six months is something that we call data spaces and that is putting in place a platform, a set of services that connect data consumers with data producers. And when you think about that, that really isn't nothing new. I mean, you could go all the way back, if you've been around for a while remember the company called TRW and they used to have credit reporting, and they used to sell that stuff. And then it moved into Experian and those things. But you've got Bloomberg and next LexisNexis and all these companies that sell data. And they've been doing it, but it's very siloed. And so the explosion of data, the valuableness the value of the data for the consumers of it has put the producers in a position where they can't readily be discovered. And whether it be a private source of data like an IoT device and an industrial control, or a set of data that might say, "Hey, here's credit card for our data on a certain geography." Those sets need to be discovered, curated, and be made available to those who would want that. You know, for example, the folks that want to know how IoT device is working inside an industrial control or a company who's trying to lower their fraud rates on credit card transactions, like in stadiums or something like that. And so this discoverability in this space, or what you just talked about is such a core piece of what we're working on right now. And we haven't, our strategy is not only to just work on what HPE has to bring that and manifest that to the marketplace. But more importantly, how are we working with our partners to really bridge that gap and bring that next generation of services to those clients that can make those connections. >> So connecting and facilitating collaboration, absolutely key, as well as that seamless flow of data sharing without constraints. How are customers working with HPE and some of your partners to be able to create a data strategy, launch it, and start gleaning value from data faster than they can before? (Robert chuckles) >> This is the big question because it's a maturity curve. Organizations are in various states of what we call data maturity or data management maturity. They can be in very early stages. You know what we consider, you know, they just more worried about just maintaining the lights on DR strategies and make sure that data doesn't go away versus all the way through a whole cycle where they're actually governing it and putting it into what I call those discoverable buckets that are made available. And there's a whole life cycle about that. And so we see a big opportunity here for our A&PS and other professional services organizations to help people get up that maturity curve. But they also have to have the foundational tools necessary to make that happen. This is really where the Ezmeral product line or software applications really shines being able to give that undercarriage that's necessary to help that data maturity and the growth of that client to meet those data needs. And we see the data fabric being a key element to that, for that distributed model, allowing people to get access and availability to have a highly redundant, highly durable data fabric and then to build applications specifically as data-intensive applications on top of that with the Ezmeral platform all the way into our GreenLake solutions. So it's quite a journey here, Lisa. I want to just, point to the fact that HPE has done a really, really good job of positioning itself for the explosion of all of these data-intensive AI/ML workloads that are making their way into every single conversation every single enterprise to this day that wants to take advantage of the value of the data they have and to augment that data through other sources. >> One, when you think about data-intensive applications the first one that pops into my mind is Uber. And it's one of those applications that we just expect. We kind of think of as a taxi service when really it's logistics and transportation, but all of the data on the backend that it is organizing to find the ride for me at my location to take me where I'm going. The explosion of data-intensive applications is great but there's also so much more demand from consumers whether we're in business or we're consuming in our personal lives. >> It's so true and that's a very popular example. And you know, you think about the real-time necessity of what's the traffic patterns at the time I order my thing. Is it going to route me the right way? That's a very real consumer facing one, but if we click into our clients and where HPE very much is like the backbone of the global economy. We provide probably one third of the compute for the global economy and it's a staggering stat if you really think about it. Our clients, I was just talking with a client here earlier, very, very large financial services company. And they have 1200 data sets that have been selling to their clients globally. And a lot of these clients want to augment that data with their existing real-time data to come up with a solution. And so they merge it and they can determine some value through a model, an AI model. And so we're working hand-in-hand with them right now to give them that backbone so that they can deliver data sets into these other systems and then make sure they get controlled and secured. So that the company we're working with, our client has a deep sense of security that that data set is not going to find itself out into the wild somewhere. And uncontrolled for a number of reasons, from security and governance mind. But the number of use cases, Lisa are as infinite as the number of opportunities for people see value in business today. >> When you're talking about 1200 data sets that a company is selling, and of course there are many, many data sets that many types of companies consume. How do you work with them to ensure that they don't just proliferate silos, but that they get more of a unified data repository that they can act on? >> Yeah, that's a great question. A key tenant of the strategy at HPE is Open-source. So we believe in a hybrid, multi-Cloud environment meaning that as long as we all agree that we are going to standardize on Open-source technologies and APIs, we will be able to write and build applications that can natively run on any abstract platform. So for example, it's very important that we containerize, for example, and we use storage and data tools that adhere to Open standards. So if you think about that, if you write a Spark application you want that Spark application potentially to run on any of the hyperscalers, the Amazon's or the Microsoft to GCPS, or you want it to run on-premises and specifically like on HPE equipment. But the idea here is I consider one of our clients right now. I mean, think about that. One of our clients specifically ask that question that you just said. They said, "Hey, we are building out this platform, this next generation platform. And we don't want the lock-in. We want to be, we want to create that environment where that data and the data framework." So they use very specific Open -source data frameworks and they open, they use very specific application frameworks the software from the Open-source community. We were able to meet that through the Ezmeral platform. Give them a very high availability, five nines high availability, redundant, redundant geographically to geographic data centers to give them that security that they're looking for. And because of that, it's opened so many other doors for us to walk in with a Cloud strategy that is an alternative, not just the one bet to public Cloud but you haven't other opportunity to bring a Cloud strategy on-premises that is compatible with Cloud-native activities that are going on in the public Cloud. And this is at the heart of HPE strategy. I think it's just, it's been paying off. It continues to pay off. We just keep investing and keep moving down that path. I think we're going to be doing really well. >> It sounds to me that the strategy that HP is developing is highly collaborative and synergistic with your customers. Talk to me a little bit about that, especially in the last year, as we've seen a massive acceleration in digital transformation about the rapid pivot to work from home, the necessity to collaborate electronically. Talk to me a little bit about that yin and yang with HPE and its customers in terms of your strategy. >> Yeah, well, I think when COVID hit one of the very first things that just took off with VDI. Rohit Dixon and I were talking on a podcast we had earlier around the work from home strategy that was implemented almost immediately. Well, we had it already in the can, we already were doing it for many clients already but it went from like a three priority to a 12, 10 being the max. Super, super charged up on how do we get work from home secured, work from home applications and stuff in the hands of people doing, you know, when data sensitivity is super important, VDI kicks in that's on that side. But then if you start looking at the digital transformation that has to happen in the supply chain that's going on right now. The opening up of our economies it's been various starts and stops if you look around the globe. The supply chains have absolutely gone under a huge amount of pressure, because, unlike in the United States, everybody just wants everything now because things are starting to open up. I was talking to a meat packing company and a restaurant business a little while ago. And they said, "Everybody wants to order the barbecue. Now we can't get the meat for the barbecues 'cause everybody's going to the barbecues." And so the supply, this is a multi-billion dollar industry supplying meat to all of the rest of the countries and stuff like that. And so they don't have optics into that supply chain today. So they're immediately having to go through a digitization process, the transformation in something as what you would call as low tech as delivering meat. So no industry is immune, none anywhere in this whole process. And it will continue to evolve as we exit and change how we live our life going into these next couple of years. I think it's going to be phenomenal just to watch. >> Yeah, it's one of the things I call a COVID catalyst some of the silver linings that have come out of this 'cause I wouldn't have thought of the meatpacking industry as a technology field as well, but now thanks to you, I will. Last question for you. When customers in this dynamic world in which we're still living talk about Edge to Cloud are they working with you to develop a Cloud initiatives, Cloud mandates, Cloud everywhere? And if so, how do you help them start? >> Yeah, that's a great question. So again, it's like back into the data model, everybody has a different degree or a starting point that they will engage us with a strategy but specifically with what you're talking about. Almost everybody already has a Cloud strategy. So they may be at different maturity levels with that Cloud strategy. And there's almost always a Cloud group. Now, historically HPE has not had much of a foot in the Cloud group because they never really historically looked at us says that HPE is a Cloud company. But what's happened over the last couple of years with the acceleration of the acceptance of Cloud on-premises and GreenLake, specifically, and the introduction of Ezmeral and the Cloud-native infrastructure services and past layer stuff that's coming up through the Ezmeral product into our clients. It's immediately opened the door for conversations around Cloud that is available for what is staying on-premises which is in excess of 70% of the applications today. Now, if you were to take that now and extend that into the Edge conversation, what if you were able to take a smaller form factor of a GreenLake Cloud and push it more closer to an Edge location while still giving the similar capabilities, Cloud-native functions that you had before? When we're provocative with clients in that sense they suddenly open up and see the art of the possible. And so this is where we are really, really breaking down a set of paradigms of what's possible by introducing, you know, not just from the Silicon all the way up but the set of services all the way to the top of stack to the actual application that they're going to be running. And we say, "Hey, we can offer it to you in as a pay as you go model, we can get you the consumption models that are necessary, that lets you buy at the same way as the Cloud offers it. But more importantly, we'll be able to run it for you and provide you an abstraction out of that model. So you don't have to send your people out into the field to do these things. We have the software, the tools, and the systems necessary to manage it for you." But the last part is I want to be really really focused on when clients are writing that application for the Edge that matters. They are putting it into new Cloud-native architectures containers, microservices, they're using solid pipelines development pipelines, they've implemented what they call their DevOps or their DataOps practices in field, in country, if you would say. That's where we shine. And so we had a really, really good conversation start there. And so how we start that is we arrive with a set of blueprints to help them establish what that roadmap looks like. And then our professional services staff, or A&PS groups around the globe are really really set up well to help them take that trip. >> Wow, that's outstanding, Robert. We could have a whole conversation on HPE's transformation. Internet itself that was my first job in tech was at Hewlett Packard back in the day. But this has been really interesting, really getting it your vision of the customer's experience and the customer's perspective from the Office of the CTO. Great to talk to you, Robert. Thank you for sharing all that you did. This could have been a Part 2 conversation. >> Well, I'm hopeful then that we'll do Part 3 and 4 here as the months go by. So I look forward to seeing you again, Lisa. >> Deal, that's a deal. All right. >> All right. >> For Robert Christiansen, I'm Lisa Martin. You're watching theCUBE's coverage of HPE Discover 2021. (upbeat music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante snowflake's eye-popping ipo this week has the industry buzzing we have had dozens and dozens of inbound pr from firms trying to hook us offering perspectives on the snowflake ipo so they can pitch us on their latest and greatest product people are pumped and why not an event like this doesn't happen very often hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll give you our take on the snowflake ipo and address the many questions that we've been getting on the topic i'm also going to discuss at the end of this segment an angle for getting in on the ground floor and investments which is not for the faint of heart but it's something that i believe is worth talking about now let's first talk about the hottest ipo in software industry history first i want to say congratulations to the many people at snowflake you know the big hitters yeah they're all the news slootman mooglia spicer buffett benioff even scarpelli interestingly you know you don't hear much about the founders they're quite humble and we're going to talk about that in some future episodes but they created snowflake they had the vision and the smarts to bring in operators that could get the company to this point so awesome for them but you know i'm especially happy for the rank and file and the many snowflake people where an event like this it really can be life-changing versus the billionaires on the leaderboard so fantastic for you okay but let's get into the madness as you know by now snowflake ipod at a price of 120. now unless you knew a guy he paid around 245 at the open that's if you got in otherwise you bought at a higher price so you kind of just held your nose and made the trade i guess you know but snowflakes value it went from 33 billion to more than 80 billion in a matter of minutes now there's a lot of finger pointing going on this is this issue that people are claiming that it was underpriced and snowflake left four billion dollars on the table please stop that's just crazy to me snowflakes balance sheet is in great shape thanks to this offering and you know i'm not sure jamming later stage investors even more would have been the right thing to do this was a small float i think it was around 10 percent of the company so you would expect a sharp uptick on day one i had predicted a doubling to a 66 billion dollar valuation and it ended up around 70. now the big question that we now get is is this a fair valuation and can snowflake grow into its value we'll address this in more detail but the short answer is snowflake is overvalued in my opinion right now but it can grow into its valuation and of course as always they're going to be challenges now the other comment we get is yeah but the company is losing tons of money and i say no kidding that's why they're so valuable we've been saying for years that the street right now is rewarding growth because they understand that to compete in software you need to have massive scale so i'm not worried in the least about snowflakes bottom line not yet eventually i'm going to pay much closer attention to operating cash flow but right now i want to see growth i want to see them grow into their valuation now the other common question we get is should i buy when should i buy what are the risks and can snowflake compete with the biggest cloud vendors i'll say this before we get into it and i've said before look it's it's very rare that you're not going to get better buying opportunities than day one of an ipo and i think in this case you will i remember back in 2015 it was i think it was the first calendar for quarter and servicenow missed its earnings and the stock got hit and we had the opportunity to interview frank slootman then ceo of servicenow right after that and i think it's instructive to hear what he said let's listen roll the clip well yeah i think that a lot of the high-flying cloud companies and obviously we're one of them you know we're we're priced to perfection right um and that's that's not an easy place to be for uh for for anybody and you know we're not really focused on that it's it's this is a marathon you know every quarter is one mile marker you can't get too excited about you know one versus the other we're really pacing ourselves we're building you know an enterprise that's going to be here for for a long time you know and after that we saw the stock drop as low as 50 today servicenow is a 450 stock so my point is that snowflake like servicenow is going to be priced to perfection and there will be bumps in the road possibly macro factors or other and if you're a believer you'll have opportunities to get in so be patient now finally i'm going to make some comments later but i'll give you the bumper sticker right now i mean i calculated the weighted average price that the insiders paid on the the s1 that they paid for snowflake and it came out to around six dollars a share and i heard somebody say on tv it was five dollars but my weighted average math got me to six dollars regardless on day one of the ipo the insiders made a 50x return on their investment if you bought on day one you're probably losing some money or maybe about even and there are some ground floor opportunities that exist that are complicated and may be risky but if you're young and motivated or older and have some time to research i think you'll be interested in what i have to say later on all right let's compare snowflake to some other companies on a valuation basis this ought to be interesting so this chart shows some high flyers as compared to snowflake we show the company the trailing 12-month revenue the market cap at the close of the 16th which is the day that snowflake ipod and then we calculate and sort the data on the revenue multiple of the trailing 12 months and the last column is the year-on-year growth rate of the last quarter and i used trailing 12 months because it's simple and it's easy to understand and it makes the revenue multiple bigger so it's more dramatic and many prefer to use a forward revenue uh but that's why i put the growth rate there you can pick your own projected revenue growth and and do the math yourself so let's start with snowflake 400 million dollars in revenue and that's based on a newish pricing model of consumption not a sas subscription that locks you in for a year or two years or three years i love this model because it's true cloud and i've talked about it a while so for a while so i'm not going to dwell on it today but you can see the trailing 12-month revenue multiple is massive and the growth rate is 120 which is very very impressive for a company this size zoom we put zoom in the chart just because why not and and the growth grade is sick so so who knows how that correlates to the revenue multiple but as you can see snowflake actually tops the zoom frothiness on that metric now maybe zoom is undervalued i should take that back let's see i think crowdstrike is really interesting here and as a company that we've been following and talking about quite a bit in my last security breaking analysis they were at a 65 x trailing 12-month revenue multiple and you see how that's jumped since they reported and they beat expectations but they're similar in size to snowflake with a slower growth rate in a lower revenue multiple so there's some correlation between that growth rate and the revenue multiple sort of now snowflake pulled back on day two it was down early uh this morning as you would expect with both the market being off and maybe some profit taking you know if you got in an allocation at 120 why not take some profits and play with house money so snowflake's value is hovering today it actually bounced back is hovering today you're just under 70 billion and that that brings the revenue multiple down a bit but it's still very elevated now if you project 2x growth let's say 100 for next year and the stock stays in some kind of range which i think it likely will you could see snowflake coming down to crowdstrike revenue multiples in 12 months it'll depend of course on snowflakes earnings reports which i'm sure are going to beat estimates for the next several quarters and if if it's growing faster than these others at that time it should command a premium you know wherever the market prices market's going to go up it's going to go down but we'll look at all these companies i think on a relative basis snowflakes still should command a premium at higher growth rates so you can see also in this chart you've got shopify awesome mongodb twilio servicenow and their respective growth rates shopify incredibly impressive [ __ ] and twilio as well servicenow is like the old dog in this mix so that's kind of interesting now the other big question we get is can snowflake grow in to its valuation this is a chart we shared with you a bit ago and it talks to snowflake's total available market and its expansion opportunity there tam expansion this is something we saw slootman execute at servicenow when everybody underestimated that company's value and i'll briefly explain here look snowflake is disrupting the traditional data warehouse and data lake markets data lake spending is relatively small it's under 2 billion but data lakes they're inexpensive and that's what made them attractive the edw market however the enterprise data warehouse market is it's much much larger now traditional edws they're they're big they're slow they're cumbersome they're expensive and they're complicated but they've been operationalized and are critical for companies reporting and basic analytics but they've failed to live up to their promise of the 360 degree view of the customer and real-time analytics you know i had a customer tell me a while ago that my data warehouse it's like a snake swallowing a basketball he gave me example where a change in a regulation this was a financial company it would occur and it would force a change in the data model in their data warehouse and they'd have to ingest all this new data and the data warehouse choked and every time intel came out with a new processor they'd rush out they'd throw more compute at the problem he called this chasing the chips now what snowflake did was to envision a cloud native world where you could bring compute to massive data volumes on an elastic basis and only pay for what you use sounds so simple but technically snowflakes founders and those innovations of that innovation of separating compute from storage to leverage the flexibility of the cloud it really was profound and clearly based on this week's performance was the right call now i'll come back to this in a bit now where we think snowflake is going is to build a data cloud and and you can see this in the chart where your data can be ingested and accessed to perform near real-time analytics with machine learning and ai and snowflake's advantage as we've discussed in the past is that it runs on any cloud and it can ingest data from a variety of sources now there are some challenges here we're not saying that snowflake is going to participate in all these use cases that we show however with its resources now we expect snowflake to create new capabilities organically and then do tuck-in acquisitions that will allow it to attack many more more use cases in adjacent markets and so you look at this chart and the third layer if that's 60 billion it means snowflake needs to extend into the fourth layer because its valuation is already over 60 billion it's not going to get 100 market share so we call this next layer automated decision making this is where real time analytics and systems are making decisions for humans and acting in real time now clearly data is going to be a pretty critical part of this equation now at this point it's unclear that snowflake has the capability to go after this space as much of the data in this area is probably going to live at the edge but snowflake is betting on becoming a data data layer across clouds and presumably at the edge and as you can see this market is enormous so there's no lack of tam in our view for snowflakes that brings us to the other big question around competition everybody's talking about this look a lot of the investment thesis behind snowflakes snowflake is that slootman and his army including cfo mike scarpelli and what they did at servicenow will be repeated scarpelli is this operational guru he keeps the engine running you know with very very tight controls and you know what it's a pretty good bet snoopman and scarpelli and their team i'm not denying that but i will tell you that snowflake's competition is much more capable than what servicenow faced in its early days now here's a picture of some of the key competitors this is one of our favorites the xy graph and on the vertical axis is net score or spending momentum that is etr's version of velocity based on their quarterly surveys now i'm showing july survey october is in the works it's in the field as i speak on the horizontal axis is market share or pervasiveness in the data set so it's a proxy for market share it's it's based on mentions not dollars and and that's why microsoft is so far to the right because they're huge and they're everywhere and they get a lot of mentions the more relevant data to us is the position of snowflake it remains one of the highest net scores in the entire etr survey based not just the database sector aw aws is its biggest competitor because most of snowflake's business runs on aws but google bigquery you can see there is is technically the most capable relative to snowflake because it's a true cloud native database built from the ground up whereas aws took a database that was built for on-prem par excel and brilliantly really made it work in the cloud by re-architecting many of the pieces but it still has legacy parts to it now here's oracle oracle's huge it's slow growth overall but it's making investments in r d we've talked about that a lot and that's going to allow it to hold on to its customers huge base and you can see teradata and cloud era cloudera is a proxy for data lakes which are low cost as i said and cloudera which acquired hortonworks is credited with the commercialization of that whole big datum and hadoop movement and then teradata is in there as well which of course they've been around forever now there are a zillion other database players we've heard a lot of them from a lot of them this week is on that inbound pr that i talked about but these are the ones that we wanted to focus on today the bottom line is we expect snowflakes vertical axis spending momentum to remain elevated and we think it will continue to steadily move to the right now let's drill into this data a bit more here we break down the components of etr's net score and this is specifically for snowflake over time now remember lime green is new adoptions the forest green is spending more relative to last year than more five percent more uh than last year or or greater gray is flat spending the pink is less spending and the bright red is we're leaving the platform the line up top that's netscore which subtracts the red from the green is an indicator of spending velocity the yellow line at the bottom is market market share or pervasiveness in the survey based on mentions now note the the blue text there that's etr's number one takeaway on snowflake two h-20 spending intentions on snowflake continue to trend robustly mostly characterized by high customer acquisition and expansion rates new adoptions market share among all customers is simultaneously growing impressive let's now look at snowflake against the competition in fortune 500 customers now here we show net score or again spending momentum over time for some of the key competitors and you can see snowflakes net score has actually increased since the april survey again this is the july survey this was taken the april survey was taken at the height of the us lockdown so snowflake's net score is actually higher in the fortune 500 than it was overall which is a good proxy for spend because fortune 500 spends more google mongodb and microsoft also also show meaningful momentum growth since the april survey you know notably aws has come off its elevated levels from last october and april it's still strong but that's something that we're going to continue to watch finally let's look at snowflakes market share or pervasiveness within the big three cloud vendors again this is a cut on the fortune 500 and you can see there are 125 respondents within the big three cloud and the fortune 500 and 21 snowflake respondents within that base of 125 and you can see the steady and consistent growth of share not huge ends but enough to give some confidence in the data now again note the etr callout but this trend is occurring despite the fact that each of the big three cloud vendors has its own competitive offering okay but i want to stress this is not a layup for snowflake as i've said this is not servicenow part two it's a different situation so let's talk about that look the competition here is not bmc which was servicenow's target as much as i love the folks at bmc we're talking here about aws microsoft and google amazon with redshift is dialed into this i've said often that they have copycatted snowflake in many cases and last fall at re invent we heard andy jassy make a big deal about separating compute from storage and he took a kind of a swipe at snowflake without mentioning them by name but let's listen to what andy jassy had had to say and then we'll come back and talk about it play the clip then what we did is because we have nitro like i was talking about earlier we built unique instances that have very fast bandwidth so that if you actually need some of those data from s3 for a query it moves much faster than if you just had to leave it there with without that high speed bandwidth instance and so with ra3s you get to separate your storage from your compute if it turns out by the way on your local ssds that you're not using all the ssd on that local ssd you only pay for what you use so a pretty significant enhancement for customers using redshift at the same time if you think about the prevailing way that people are thinking about separating storage from compute letting people scale separately that way as well as how you're going to do this large-scale compute where you move the storage to the a bunch of awaiting compute nodes there are some issues with this that you got to think about the first is think about how much data you're going to have at the scale that we're at but then just fast forward a few years think about how much data you're going to actually have to move over the network to get to the compute and we so look first of all jassy is awesome he stands up at these events for like reinvent for two hours and it connects trends and business to technology he's got a very deep understanding of the tech he's amazing however what aws has done in separating compute and storage is good but it's not as elegant architecturally as snowflake aws essentially has tiered the storage off the cluster to lower the overall costs but you really you can't turn off the compute completely with snowflake they've truly separated compute and storage and the reason is that redshift is great but it's built on an on-prem architecture that was originally an on-prem architecture that they had to redo so when jassy talks about moving the data to compute what he's really saying is our architecture is such that we had to do this workaround which is actually quite clever but this whole narrative about the prevailing ways to separate compute from storage that's snowflake and moving the data's use the word data's plural to the compute it really doesn't apply to snowflake because they'll just move the compute to the data thank you hadoop for that profound concept now does this mean snowflake is going to cakewalk over redshift not at all aws is going to continue to innovate so snowflake had better keep moving fast multi-cloud new workloads adjacent markets tam expansion etc etc etc microsoft they're huge but as usual there's not a lot to say you know about them they're everywhere they put out 1.0 products they eventually get them right because with their heft they get mulligans that they turn into pars or birdies but i think snowflake is going to bring some innovations to azure and that they're going to get good traction there in my opinion now google bigquery is interesting by all accounts it gets very high technical marks google's playing the long game and i would expect that snowflake is going to have a harder time competing in google cloud than it does within aws and what i'm predicting for azure but we'll see the last point here is that many are talking about the convergence of analytic and operational and transaction databases and the thinking is this doesn't necessarily bode well for specialists like snowflake and i would say a couple of things here first is that while it's definitely true you're not seeing snowflake positioning today as responding at the point of transaction to say for instance influence and order in real time and this may have implications at the edge it's going to have a lot of real-time inferencing but we've learned there are a lot of ways to skin a cat and we see integration layers and innovative approaches emerging in the cloud that could address this gap and present opportunities for snowflake now the other thing i'd say is you know maybe that thinking misses something altogether with the idea of snowflake in that third data layer that we showed you in our tam chart that data as a service layer or data cloud which is maybe a giant opportunity that they are uniquely positioned to address because they're cloud agnostic they've got the vision and they've got the architecture to allow them to very simply ingest data and then serve it up to businesses nonetheless we're going to see this battle continue between what i've often talked about these integrated suites and converged databases in the case of oracle converged pipelines in the case of the cloud guys versus the best of breed players like snowflake we talk about this all the time and there really isn't one single answer it's really horses for courses and customer preferences okay well you know i know you've been waiting for for me to tell you about the angles on ground floor investing and you probably think this is going to be crazy but bear with me and i got to caution you this is a bit tongue-in-cheek and it's one big buyer beware but as i said the insiders on snowflake had a 50x return on day one you probably didn't so i want to talk about the confluence of software engineering crypto cryptography and game theory powered by the underlying value of blockchain and we're talking here about innovations around a new internet in a distributed web or d-web where many distributed computers come together to form one computer that guarantees trust between two or more users for a variety of use cases not just financial store like bitcoin but that too and the motivation behind this is the fact that a small number of companies say five or six today control the internet and have essentially co-opted the major protocols like tcp http smtp pop3 etc etc and these people that we're showing here on this chart they're working on these new innovations there are many of them but i just name a few here olaf carlson we he started poly chain capital to invest in core infrastructure around these new computing paradigms this gentleman mark nadal is someone who's working on new d apps tim berners-lee who invented the internet he's got a project called solid at mit and it emphasizes data ownership and privacy and of course satoshi got it all started when she invented bitcoin and created the notion of fractional shares and by the way the folks at andreessen horowitz are actively making bets in this space so you know maybe this is not so crazy but here's the premise if you're a little guy and you wanted to invest in snowflake you couldn't until late in the game if you wanted to invest in the lamp stack directly in the late 90s there was no way to do that you had to wait for red hat to go public or to get a piece of the linux action but in this world that we're talking about here there are opportunities that are not mainstream and often they're based yes on cryptocurrencies again it's dangerous there are scams and and losers but if you do your homework there are actually vehicles for you to get in on the ground floor and you know some of these innovations are going to take off you could get a 50x or 100 bagger but you have to do your research and there's no guarantee that these innovations are going to be able to take on the big internet giants but there are people really smart technologists and software engineers that are young they're mission driven and they're forming a collective voice against a dystopian future because they want to level the playing field on the internet and this may be the disruptive force that challenges today's giants and if your game i would take a look at the space and see if it's worth throwing a few dollars at okay a little tangent from snowflake but i wanted to put that out there snowflake wow closes its first trading week as a company worth 66 billion dollars roughly the same as goldman sachs worth more than vmware and the list goes on i mean what's what's more is there to say other than remember these episodes are all available as podcasts so please subscribe i publish weekly on wikibon.com and siliconangle.com so please check that out and please comment on my linkedin post or feel free to email me at david.velante at siliconangle.com this is dave vellante for the cube insights powered by etr thanks for watching everyone we'll see you next time you

>> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the CloudNative Computing Foundation, and Ecosystem Partners. >> Hi and welcome back to theCUBE's coverage of KubeCon, CloudNativeCon 2020 in Europe, of course the virtual edition. I'm Stu Miniman and happy to welcome back to the program one of the keynote speakers, he's also a board member of the CNCF, Vijoy Pandey who is the vice president and chief technology officer for Cloud at Cisco. Vijoy, nice to see you and thanks so much for joining us. >> Thank you Stu, and nice to see you again. It's a strange setting to be in but as long as we are both health, everything is good. >> Yeah, it's still a, we still get to be together a little bit even though while we're apart, we love the engagement and interaction that we normally get through the community but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Network, Please Evolve", been watching that journey. But why don't we start it first, you know, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so that, yeah let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports into Chuck. The role, the charter for this team, this new team, is to incubate the next bets for Cisco. And, if you can imagine, it's natural for Cisco to start with bets which are closer to its core business, but the charter for this group is to mover further and further out from Cisco's core business and takes this core into newer markets, into newer products, and newer businesses. I am running the engineering and research for that group. And, again, the whole deal behind this is to be a little bit nimble, to be a little startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast and you throw out 80% of those and concentrate on the 20% that make sense to take forward as a venture. >> Interesting. So it reminds me a little bit, but different, I remember John Chambers a number of years back talking about various adjacencies, trying to grow those next, you know, multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for, you know, driving innovation, giving engineering 20% of their time to work on things. Give us a little bit of insight. What's kind of an example of a bet that you might be looking at in the space? Bring us inside a little bit. >> Well that's actually a good question and I think a little bit of that comparison is, are those conversations that taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets. And, yes, my previous employer, I mean Google X actually goes pretty far out when it comes to incubations. The core business being primarily around ads, now Google Cloud as well, but you have things like Verily and Calico and others which are pretty far out from where Google started. And the way we are looking at these things within Cisco is, it's a new muscle for Cisco so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to go-to-market alignment or business alignment. So while the first bets that we are taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure's code, but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I talked a lot about this in the past couple of keynotes where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, whatever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets that we are going after is around connecting and securing API endpoints wherever they happen to be of whatever type they happen to be. And so API networking, or app networking, is one big bet that we're going after. Our other big bet is around API security and that has a bunch of other connotations to it where we think about security moving from runtime security where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security which is only under the developer pipeline and higher up in the stack. So those are two big bets that we're going after and as you can see, they're pretty close to Cisco's core business but also very differentiated from where Cisco is today. And once when you prove some of these bets out, you can walk further and further away or a few degrees away from Cisco's core as it exists today. >> All right, well Vijoy, I mentioned you're also on the board for the CNCF, maybe let's talk a little bit about open source. How does that play into what you're looking at for emerging technologies and these bets, you know, so many companies, that's an integral piece, and we've watched, you know really, the maturation of Cisco's journey, participating in these open source environments. So help us tie in where Cisco is when it comes to open source. >> So, yeah, so I think we've been pretty deeply involved in open source in our past. We've been deeply involved in Linux foundational networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack. We are big supporters of OpenStack. We have a couple of products that are on the OpenStack offering. And as you all know, we've been involved in CNCF right from the get go as a foundational member. We brought NSM as a project. It's sandbox currently. We're hoping to move it forward. But even beyond that, I mean we are big users of open source. You know a lot of us has offerings that we have from Cisco and you would not know this if you're not inside of Cisco, but Webex, for example, is a big, big user of linger D right from the get go from version 1.0. But we don't talk about it, which is sad. I think for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise site. We use Kubernetes very deeply in our security platforms. So we are pretty deep users internally in all our SAS products. But we want to press the accelerator and accelerate this whole journey towards open source quite a bit moving forward as part of ET&I, Emerging Tech and Incubation as well. So you will see more of us in open source forums, not just the NCF but very recently we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative and we actually are big believers in handling data in ethical and privacy preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health and we will be working very closely with Dan and the foundational companies there to, not just bring open source, but also evangelize and use what comes out of that forum. >> All right. Well, Vijoy, I think it's time for us to dig into your keynote. We've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on, and big focus you talked about was SD-WAN. Of course anybody that been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling Multicloud, so help us, you know, help explain to our audience a little bit, you know, what do you mean when you talk about things like CloudNative, SD-WAN, and how that helps people really enable their applications in the modern environment? >> Yeah, so, well we we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actual data connectivity across to your enterprise or branch and SD-WAN came in and changed the game there. But I think SD-WAN as it exists today is application-alaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM, or network service mesh, has actually helped us simplify operational complexities, simplify the ticketing and process hell that any developer needs to go through just to get a multicloud, multicluster app up and running. So the keynote actually talked about bringing those two things together where we've talked about using NSM in the past, in chapter one and chapter two, ah chapter two, no this is chapter three and at some point I would like to stop the chapters. I don't want this to be like, like an encyclopedia of networking (mumbling) But we are at chapter three and we are talking about how you can take the same consumption models that I talked about in chapter two which is just adding a simple annotation in your CRD and extending that notion of multicloud, multicluster wires within the components of our application but extending it all the way down to the user in an enterprise. And as you saw an example, Gavin Russom is trying to give a keynote holographically and he's suffering from SD-WAN being application alaware. And using this construct of a simple annotation, we can actually make SD-WAN CloudNative. We can make it application-aware, and we can guarantee the SLOs that Gavin is looking for in terms of 3D video, in terms of file access or audio just to make sure that he's successful and Ross doesn't come in and take his place. >> Well I expect Gavin will do something to mess things up on his own even if the technology works flawly. You know, Vijoy the modernization journey that customers are on is a neverending story. I understand the chapters need to end on the current volume that you're working on. But, you know, we'd love to get your view point. You talk about things like service mesh. It's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the the kind of real challenges but opportunities that they see in today's CloudNative space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree and we are seeing a lot of that happening where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've got linger D, you've got various proprietary notions around control planes like App Mesh from Amazon. There's Console which is an open source project But not part of (mumbles) today. So there's a whole bunch of service meshes in terms of control planes coming in on volumes becoming a de facto side car data plane, whatever you would like to call it, de facto standard there which is good for the community I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment. And that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for. Like API Gate was in the past. And those functions are actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of some service meshes is here to stay. And so some work has to be done in bringing these things together and that's something that we are trying to focus in on all as well because that's something that our customers are asking for. >> Yeah, actually you connected for me something I wanted to get your viewpoint on. Dial back you know 10, 15 years ago and everybody would say, "Ah, you know, I really want to have single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, you know, not that long before this event, Google had their Google Cloud show talking about the partnership that you have with Cisco with Google. They have Anthos. You look at Azure has Arc. You know, VMware has Tanzu. Everybody's talking about, really, kind of this multicluster management type of solution out there. And just want to get your viewpoint on this Vijoy is to, you know, how are we doing on the management plane and what do you think we need to do as a industry as a whole to make things better for customers? >> Yeah, but I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all of these things together. And I think the SMI apropos from Microsoft is bang on on that front where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes. As you saw in the SD-WAN and also going back in the Google discussion that you just, or Google conference that we just offered It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a CloudNative environment in the keynote. But I think the bigger problem here is how do we manage this complexity of disparate stacks, whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And, single pane of glass is over loaded as a term because it brings in these notions of big, monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, you know, the API economy should be able to help on these, you know, multi, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco and congratulations on the new role. >> Thank you Stu. It was a pleasure to be here. >> All right, and stay tuned for much more coverage of theCUBE at KubeCon, CloudNativeCon. I'm Stu Miniman and thanks for watching. (light digital music)

(upbeat music) >> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation, and the ecosystem partners. >> Hi, and welcome back to theCUBE's coverage of KubeCon + CloudNativeCon 2020 in Europe, of course, the virtual edition. I'm Stu Miniman, and happy to welcome you back to the program. One of the keynote speakers is also a board member of the CNCF, Vijoy Pandey, who is the Vice President and Chief Technology Officer for Cloud at Cisco. Vijoy, nice to see you, thanks so much for joining us. >> Hi there, Stu, so nice to see you again. It's a strange setting to be in, but as long as we are both healthy, everything's good. >> Yeah, we still get to be together a little bit even though while we're apart. We love the the engagement and interaction that we normally get to the community, but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Networking, Please Evolve". I've been watching that journey. But why don't we start at first, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports on to Chuck. The charter for the team, this new team, is to incubate the next bets for Cisco. And if you can imagine, it's natural for Cisco to start with bets which are closer to its core business. But the charter for this group is to move further and further out from Cisco's core business and take Cisco into newer markets, into newer products, and newer businesses. I'm running the engineering and resource for that group. And again, the whole deal behind this is to be a little bit nimble, to be a little bit, to startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast, and you throw out 80% of those, and concentrate on the 20% that makes sense to take forward as a venture. >> Interesting. So it reminds me a little bit but different, I remember John Chambers, a number of years back, talking about various adjacencies trying to grow those next multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for driving innovation, giving engineers 20% of their time to work on things, maybe give us a little bit insight, what's kind of an example of a bet that you might be looking at in this space, bring us in tight a little bit. >> Well, that's actually a good question. And I think a little bit of that comparison is all those conversations are taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets? And yes, my previous employer, I mean, Google X actually goes pretty far out when it comes to incubations, the core business being primarily around ads, now Google Cloud as well. But you have things like Verily and Calico, and others, which are pretty far out from where Google started. And the way we're looking at the these things within Cisco is, it's a new muscle for Cisco, so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to, go to market alignment or business alignment. So one of the first bets that we're taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure as code but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I've talked a lot about this in the past couple of keynotes, where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, wherever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets, that we're going after is around connecting and securing API endpoints, wherever they happen to be, of whatever type they happen to be. And so API networking or app networking is one big bet that we're going after. Another big bet is around API security. And that has a bunch of other connotations to it, where we think about security moving from runtime security, where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security, which is earlier in the development pipeline, and higher up in the stack. So those are two big bets that we're going after. And as you can see, they're pretty close to Cisco's core business, but also are very differentiated from where Cisco is today. And once you prove some of these bets out, you can walk further and further away, or a few degrees away from Cisco's core. >> All right, Vijoy, why don't you give us the update about how Cisco is leveraging and participating in open source? >> So I think we've been pretty, deeply involved in open source in our past. We've been deeply involved in Linux Foundation Networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack, we have been supporters of OpenStack. We have a couple of products that are around the OpenStack offering. And as you all know, we've been involved in CNCF, right from the get-go, as a foundation member. We brought NSM as a project. I had Sandbox currently, but we're hoping to move it forward. But even beyond that, I mean, we are big users of open source, a lot of those has offerings that we have from Cisco, and you will not know this if you're not inside of Cisco. But Webex, for example, is a big, big user of Linkerd, right from the get-go, from version 1.0, but we don't talk about it, which is sad. I think, for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise side. We use Kubernetes very deeply in our security platforms. So we're pretty good, pretty deep users internally in our SaaS products. But we want to press the accelerator and accelerate this whole journey towards open source, quite a bit moving forward as part of ET&I, Emerging Tech and Incubation, as well. So you will see more of us in open source forums, not just CNCF, but very recently, we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative, and we actually are big believers in handling data in ethical and privacy-preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health, and we will be working very closely with Dan and foundational companies that do not just bring open source but also evangelize and use what comes out of that forum. >> All right, well, Vijoy, I think it's time for us to dig into your keynote. We've we've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on. And big focus you talked about was SD-WAN. Of course, anybody that's been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling multi-cloud. So help explain to our audience a little bit, what do you mean when you talk about things like Cloud Native SD-WAN and how that helps people really enable their applications in the modern environment? >> Yes, well, I mean, we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actually get your connectivity across to your enterprise or branch. And SD-WAN came in and changed the game there, but I think SD-WAN, as it exists today, is application-unaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM or Network Service Mesh has actually helped us simplify operational complexities, simplify the ticketing and process health that any developer needs to go through just to get a multi-cloud, multi-cluster app up and running. So the keynote actually talked about bringing those two things together, where we've talked about using NSM in the past in chapter one and chapter two. And I know this is chapter three, and at some point, I would like to stop the chapters. I don't want this like an encyclopedia of "Networking, Please Evolve". But we are at chapter three, and we are talking about how you can take the same consumption models that I talked about in chapter two, which is just adding a simple annotation in your CRD, and extending that notion of multi-cloud, multi-cluster wires within the components of our application, but extending it all the way down to the user in an enterprise. And as we saw an example, Gavin Belson is trying to give a keynote holographically and he's suffering from SD-WAN being application-unaware. And using this construct of a simple annotation, we can actually make SD-WAN cloud native, we can make it application-aware, and we can guarantee the SLOs, that Gavin is looking for, in terms of 3D video, in terms of file access for audio, just to make sure that he's successful and Ross doesn't come in and take his place. >> Well, I expect Gavin will do something to mess things up on his own even if the technology works flawlessly. Vijoy, the modernization journey that customers are on is a never-ending story. I understand the chapters need to end on the current volume that you're working on, but we'd love to get your viewpoint. You talk about things like service mesh, it's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the kind of real challenges but opportunities that they see in today's cloud native space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree, and we are seeing a lot of that happening, where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've Linkerd, you've got various proprietary notions around control planes like App Mesh, from Amazon, there's Consul, which is an open source project, but not part of CNCF today. So there's a whole bunch of service meshes in terms of control planes coming in. Envoy is becoming a de facto sidecar data plane, whatever you would like to call it, de facto standard there, which is good for the community, I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment, and that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for, like API gateways in the past, and those functions actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of service meshes is here to stay. And so some work has to be done in bringing these things together. And that's something that we are trying to focus in on as well. Because that's something that our customers are asking for. >> Yeah, actually, you connected for me something I wanted to get your viewpoint on, go dial back, 10, 15 years ago, and everybody would say, "Oh, I really want to have a single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, not that long before this event, Google had their Google Cloud Show, talking about the partnership that you have with, Cisco with Google. They have Anthos, you look at Azure has Arc, VMware has Tanzu. Everybody's talking about really the kind of this multi-cluster management type of solution out there, and just want to get your viewpoint on this Vijoy as to how are we doing on the management plane, and what do you think we need to do as an industry as a whole to make things better for customers? >> Yeah, I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers. Because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all these things together? I think the SMI proposal from Microsoft is bang on on that front, where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes as you saw in the SD-WAN announcement back in the Google discussion that we just, Google conference that you just referred. It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a cloud native environment in the keynote. But I think the bigger problem here is how do we manage this complexity of this pallet stacks? Whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And single pane of glass is overloaded as a term, because it brings in these notions of big monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. And I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, the API economy should be able to help on these, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco, and congratulations on the new role. >> Thank you, Stu. It was a pleasure to be here. >> All right, and stay tuned for lots more coverage of theCUBE at KubeCon + CloudNativeCon. I'm Stu Miniman. Thanks for watching. (upbeat music)

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

>>live from Seattle, Washington. It's the booth covering smartsheet engaged 2019. Brought to you by smartsheet. >>Welcome back, everyone to the cubes. Live coverage of smart. She engaged here in Seattle. I'm your host, Rebecca Night, along with my co host, Jeff. Rick. We're joined by Anna Griffin. She is the CMO of smartsheet. Thanks so much for coming on the Q. Thank you, guys for having me appreciate it. So you were your pretty new to this company joined in April. I'd love to hear, but you've also had an illustrious career in marketing. You've worked several big names, including Apple and Nortel and and Saturn. And you've also worked for Land's end and a whole bunch of different varied career. What attracted you to smart? She You know, it >>was interesting when I first got the call about smartsheet. I had never heard of it, and the way that it was positioned to me was super intriguing. I realized it was one of those a category that's just not established, but a category that has the potential to be the next big thing. And we're not even the potential. I mean, it will be the next big thing and you know, I met with that was intriguing. But, you know, I met with the executive team and it was a perfect combination of a killer product, but a killer company. I can't tell you how special the leadership of this company is and their authenticity and their passion and their drive and their belief. It's so contagious. There's no way you would not want to be a part of it. So on, then, the privilege to be able to tell this company's story I feel like it is the best kept story not only in Seattle, potentially the world on I plan to tell the story and and what a gift. But what a great opportunity is. A marketer toe have this type of opportunity. >>Well, we're gonna get into how you're going to tell the story, okay, a little bit later, but so now you've been here a few months. It is your first ever engaged What? What does he what are your impressions? >>Well, I wish I had been thio previous engaged to have something to compare it to. But the fact that this conference has doubled in size 4000 customers here and it's only its third show. I will tell you in the industry who have worked, you know, managing events teams for many, many, many years. Not a lot of conferences grow at this size, and Soto have 4000 customers here who are zealots. They are their passion for the product and what it's doing and what it's doing for there. Not only their companies, but their own personal careers. There isn't an empowerment story through their mouse that will just inspire you. So it's It's incredible. The energy here is really, really especially. >>Feel it, too. Way See >>it a lot of the smaller conferences early days. That's why they're fun to be. Here were last year, when those 2000 it was adjacent to the to the office across the across the water. Exactly, but it is a really passion community, and you know, Thio here, literal, literal cheers and claps at features. It's great. It's like copy paste from one road to the other because it's clearly something that means something these people and that they have asked for and the company is delivered and really demonstrates, is listening to engage these crazy people. It's a great asset >>wave. That listening thing is huge, and I feel like that's one of the things. And I think it's why there is a CMO now. Why get the privilege to be the first CMO is because the customers said way need more awareness of this company. We need our our executives. We need lines of business leaders. We need i t to know who you are and the magic of what you do. We need awareness is gonna make it that much easier for us to get much wider adoption across these companies. If people know who you are and they know you know what you're capable of. So listening. That is one of the number one things we've heard. It's like awareness. They wanted awareness, so because >>it'll help make them >>more successful. So I think that was the >>catalyst for OK, let's get achieve, Marty. Officer, Let's go build that about you. What are you gonna do? What were some of your top priority is to tell the story and to build brand awareness. Yeah, well, um well, you're the first thing >>was to really kind of Titan are positioning again. It's a great great products make great brands, and this is a great product company. But man were starting to do so much more than just killer products were really getting into this enablement this, right, transforming companies. And so I wanted to make sure we're positioned properly. And we're really positioning mawr in a more transformative altitude and the capabilities of what we could do. You know, we have found we've spent way too much time talking about technology versus people versus what technology and people are going to do together. And that is the magic of what Smartsheet does. It really takes a platform, a common platform that basically integrates with the tech investments. And you've >>already made with the systems of record that you already have pools that data out and then allows >>the people I work with that data all in a common really time application. And when >>you can marry >>those two things together, that tech and people, that's when one plus one equals three. And so we call that that three is what we really call achievement again, like >>everybody in our space >>is work work, work, task management, project management, the capability of smart shit. Yeah, we do all that too. But when you're playing that transformative altitude, we're in Ebeling achievement and it enterprise wide level and achievement, like what your business can achieve. But this is the more special part, and this is where I get excited. Did you feel to tell this story is the achievement happens at a personal level to like again? I'm telling you when I talk to customers and I see what they're doing right, you don't understand. You have changed my career. I'm doing more strategic work. I am. I am seeing differently in my company. I champion this, like all of a sudden I am leading big teams. I went from this to this, and there they're empowerment is so big and so really that last mile of digital transformation is cultural transformation. And that's what this product does. And so job one was position. That's properly so we can tell that type of story and really put our solutions in that kind of light because that's what it does on then job to is to launch the campaign launches to the world. So we just launched two weeks ago and it's a slow roll. I mean, we have hundreds of assets it in place. So if I love seeing us on television, you know I love seeing is deeply in digital. I love some of the new interesting things that that we can do in media. But when our customers are saying that you know they're seeing it, a CMO like you gonna get a high from it. Yeah, So it's fun job to launch the campaign, >>and the campaign is, well, we call the campaign can do you know we're positioning >>the brand as the platform for enterprise achievement. Number one Smart sheet is a platform, I think a lot of people, you know as it's grown. I mean, it truly is a platform, and it really is enterprise strong and wide. It's skills which is important, but its scales So everybody and a company can align organizational alignment to truly achieve something bigger aligned organizations do not fill. And so that's the That's the power. But I digress. >>No question that way >>you know, one of the great legs of your of your go to market strategy and your lead Jen is your licensing formula, which enables me as the Spartan sheet licensee to engage lots of people many outside my own, not by my own team, but my own company. And let them have access to this tool. What a smart, smart waiver. Whoever came up with that licensing strategy? What a great way to introduce the opportunity to use this transformational tool to ongoing and broad audience. Yes, >>your table is so exciting. >>When I was in the interview process and I was riding on a plane and clearly I had met with the company and I heard somebody in front of me was a consultant, one of the consulting firms who had met a complete stranger on the plane. And somehow Smartsheet came up that she was going you got Oh, my gosh, Smartsheet. >>This is like she was going. This is the best kept secret. We're using it with all of our clients. We heard about it through one of our clients That wasn't one of them. We'll use it like Oh, my gosh, this is the game changer. I'm like putting my here in between the wayward I put my hand in as it did You just say smart shape. Literally six people on the airplane, random people like, Oh, my gosh, we use it to. It was the >>most surreal experience, and that was when I knew, like, Okay, I've got to be a part of this Coast special. Did a lot of people are now just getting that sensation of what this thing is capable of. >>And, well, it's funny to your personal achievement story. Reminds me of any time you know you got a new software company and whether you know, center Deloitte or even why, when those guys come in, they're making a big bet right there. Some new partner's gonna bet. Bet their career on this new technology. We've heard from a number of people how betting their career internally with smartsheet has changed their position in the company. Yes, we find that today a couple of times so clearly you know it. It is an enablement platform for someone to, you know, grab on to the to the rocket ship and ride this Marchi wave thio new and bigger, better things, >>but but also her point about just even just participating in the technology. And then they're able to, as you said, work on more strategic work, be able to do more things in their jobs that have been catapulted them to new job. So it's not even necessarily betting on smartsheet and bringing in smart cheat. But it is just just using smart sheet and then therefore they have more brain time. Yes, yes, oh, engagement we're talking about, >>right, right? You know, it is because we've been talking a lot about you know, some of the really scary statistics about how disengaged people are at work and how many people are ready to quit their job. And, you know, they've got all these blocks. Is menial roadblocks in their day to day existence that are that are negatively impacting their ability to want to do their job or but actually just want to be there anymore. And so it's It's like it seems, maybe to the outside, looking in some of these things by seem low value, but they're actually tremendous value if you're removing these roadblocks so I could get my job done >>totally and love your job, you love >>your job. But know that the work that you do matters and I think so many people have lost that feeling like there's something about working and I don't know if it's the corporate world, but it has become such a grind and that rare opportunity. We feel like I love what I do, and I know that it matters like it's a gift and this is a platform that enables bad in people. And so I think that's when the fascinating things I've been spending a lot of time on the road with customers and I was at a very big multi national, big global agricultural company. And, um, Singer, Actually, I'm watching WAY Bet with probably 200 different Just what I would call power users across seven different you know, roll types like from I t toe hsc thio, you name it. And, um, every single one of them is like art. We're doing more like we are empowered, like the engagement, the employee engagement in that company, through the roof because every single person felt like were hurt. I have ownership, you know. I'm doing work. I'm taking it to a new level. And so you know, sure, there is a Thanh of operational efficiencies that are gonna come out of working with smart shape, But I think the one to watch is what's gonna happen when your workforce is truly engaged and taking ownership of the work. >>Those were the good. Those are the companies that are >>going to have a higher retention they're gonna have >>They're going to see >>something in that in that talent area. So this is more than just We're getting more work done and return on investment of our our our systems like you're going to see you know, what happens when your when your employees are empowered. >>Well, the word you didn't use his innovation that I firmly believe everyone wants more innovation, their company. >>But how do you do >>it? One of those? I think it's really simple. Lever on that is you just get more people more access to more data and then the ability to do something about it and open it up to all the smart people that see problem to different prisons in different opportunities. And that's where you start to get in. A leverage is amazing talent that you already have inside your four walls. >>But what is interesting about >>innovation is I think sometimes the world so over rotates that innovation is gonna be that next killer line of code, or it's going to be and they forget that the power of practical innovation like it's that Siri's of small collected things at out up, allowing your entire, you know, employee population to feel like they have the power to innovate us. That every person in the company has the power because the power practical innovation can lead to something Justus biggest the big already >>Dev Ops has shown that that's a better way anyway, right in software development, with the grand idea with the market development plan and the product development plan in the three year build cycle that's does not win against constant religious narrative improvement. Improvement, improvement, improvement, improvement. Yes, >>indeed. So you and you said this earlier and I saw it on your Lincoln to the last mile of digital transformation is cultural transformation. Yes. How do you describe the culture at smart shape now that we've done talked about the evangelical customers Yeah, about with in smartsheet itself, it's, um it's pretty >>special. Know what you're gonna say? Of course. And see if I was >>gonna say special. But it is. It is rare >>when people everyone comes to work with this belief like this true belief that they are. They have the power to influence something and touch something that's going to do something great for other people. And I think that's what is the most special is they? They're not just doing it for themselves. They know they're doing it for others, like they know they love these guys. Every single person in the company loves that customer like the love ability, They love the customer and they feel like they've got to do their best work. So their customer, I can do something great >>with it. You know, they really understand that. >>And that's Ah, it's an incredible place to wanna work when you, when you feel that way but toe love your customers. I think that's why our customers love us back and to be loved. You must first love >>and because they love you know, it's it's rare. Well, congratulations. It sounds like it's a great role and you're in the right place. And I can't talk to you next year and hear more about can do and and all of the wonderful things you're doing. Thank you. Thank you, guys. I'm Rebecca Knight. That wraps up the cubes. Interviews. Stay tuned for our rap of engaged 2019 you're watching the Cube

>> Live from New York, it's The Cube, covering The Cube New York City 2018 brought to you by SiliconAngle Media and its Ecosystem partners. >> Okay, welcome back everyone, here live in New York City for Cube NYC, formally Big Data NYC, now called CubeNYC. The topic has moved beyond big data. It's about cloud, it's about data, it's also about potentially blockchain in the future. I'm John Furrier, Dave Vellante. We're happy to have a special guest here, Arun Murthy. He's the cofounder and chief product officer of Hortonworks, been in the Ecosystem from the beginning, at Yahoo, already been on the Cube many times, but great to see you, thanks for coming in, >> My pleasure, >> appreciate it. >> thanks for having me. >> Super smart to have you on here, because a lot of people have been squinting through the noise of the market place. You guys have been now for a few years on this data plan idea, so you guys have actually launched Hadoop with Cloudera, they were first. You came after, Yahoo became second, two big players. Evolved it quickly, you guys saw early on that this is bigger than Hadoop. And now, all the conversations on what you guys have been talking about three years ago. Give us the update, what's the product update? How is the hybrids a big part of that, what's the story? >> We started off being the Hadoop company, and Rob, our CEO who was here on Cube, a couple of hours ago, he calls it sort of the phase one of the company, where it were Hadoop company. Very quickly realized we had to help enterprises manage the entire life cycle data, all the way from the edge to the data center, to the cloud, and between, right. So which is why we did acquisition of YARN, we've been talking about it, which kind of became the basis of our Hot marks Data flow product. And then as we went through the phase of that journey it was quickly obvious to us that enterprises had to manage data and applications in a hybrid manner right which is both on prem And public load and increasingly Edge, which is really very we spend a lot of time these days With IOT and everything from autonomous cars to video monitoring to all these aspects coming in. Which is why we wanted to get to the data plan architecture it allows to get you to a consistent security governance model. There's a lot of, I'll call it a lot of, a lot of fight about Cloud being insecure and so on, I don't think there's anything inherently insecure about the Cloud. The issue that we see is lack of skills and our enterprises know how to manage the data on-prem they know how to do LDAP, groups, and curb rows, and AAD, and what have you, they just don't have the skill sets yet to be able to do it on the public load, which leads to mistakes occasionally. >> Um-hm. >> And Data breaches and so on. So we recognize really early that part of data plan was to get that consistent security in governance models, so you don't have to worry about how you set up IMRL's on Amazon versus LDAP on-prem versus something else on Google. >> It's operating consistency. >> It's operating, exactly. I've talked about this in the past. So getting that Data plan was that journey, and this week at Charlotte work week we announced was we wanted to take that step further we've been able to kind of allow enterprise to manage this hybrid architecture on prem, multiple public loads. >> And the Edge. >> In a connected manner, the issue we saw early on and it's something we've been working on for a long while. Is that we've been able to connect the architectures Hadoop when it started it was more of an on premise architecture right, and I was there in 2005, 2006 when it started, Hadoop's started was bought on the world wide web we had a gigabyte of ethernet and I was up to the rack. From the rack on we had only eight gigs up to the rack so if you have a 2000 or cluster your dealing with eight gigs of connection. >> Bottleneck >> Huge bottleneck, fast forward today, you have at least ten if not one hundred gigabits. Moving to one hundred to a terabyte architecture, for that standpoint, and then what's happening is everything in that world, if you had the opportunity to read things on the assumptions we have in Hadoop. And then the good news is that when Cloud came along Cloud already had decoupled storage and architecture, storage and compute architectures. As we've sort of helped customers navigate the two worlds, with data plan, it's been a journey that's been reasonably successful and I think we have an opportunity to kind of provide identical consistent architectures both on prem and on Cloud. So it's almost like we took Hadoop and adapted it to Cloud. I think we can adapt the Cloud architecture back on prem, too to have consistent architectures. >> So talk about the Cloud native architecture. So you have a post that just got published. Cloud native architecture for big data and the data center. No, Cloud native architecture to big data in the data center. That's hyrid, explain the hybrid model, how do you define that? >> Like I said, for us it's really important to be able to have consistent architectures, consistent security, consistent governance, consistent way to manage data, and consistent way to actually to double up and port applications. So portability for data is important, which is why having security and governance consistently is a key. And then portability for the applications themselves are important, which is why we are so excited to kind of be, kind of first to embrace the whole containerize the ecosystem initiative. We've announced the open hybrid architecture initiative which is about decoupling storage and compute and then leveraging containers for all the big data apps, for the entire ecosystem. And this is where we are really excited to be working with both IBM and Redhat especially Redhat given their sort of investments in Kubernetes and open ship. We see that much like you'll have S3 and EC2, S3 for storage, EC2 for compute, and same thing with ADLS and azure compute. You'll actually have the next gen HDFS and Kubernetives. So is this a massive architectural rewrite, or is it more sort of management around the core. >> Great question. So part of it is evolution of the architecture. We have to get, whether it's Spark or Kafka or any of these open source projects, we need to do some evolution in the architecture, to make them work in the ecosystem, in the containerized world. So we are containerizing every one of the 28 animals 30 animals, in the zoo, right. That's a lot of work, we are kind of you know, sort of do it, we've done it in the past. Along with your point it's not enough to just have the architecture, you need to have a consistent fabric to be able to manage and operate it, which is really where the data plan comes in again. That was really the point of data plane all the time, this is a multi-roadmap, you know when we sit down we are thinking about what we'll do in 22, and 23. But we really have to execute on a multi-roadmap. >> And Data plane was a lynch pin. >> Well it was just like the sharp edge of the sword. Right, it was the tip of the sphere, but really the idea was always that we have to get data plan in to kind of get that hybrid product out there. And then we can sort of get to a inter generational data plan which would work with the next generation of the big data ecosystem itself. >> Do you see Kubernetes and things like Kubernetes, you've got STO a few service meshes up the stack, >> Absolutely are going to play a pretty instrumental role around orchestrating work loads and providing new stateless and stateful application with data, so now data you've got more data being generated there. So this is a new dynamic, it sounds like that's a fit for what you guys are doing. >> Which is something we've seen for awhile now. Like containers are something we've tracked for a long time and really excited to see Docker and RedHat. All the work that they are doing with Redhat containers. Get the security and so on. It's the maturing of that ecosystem. And now, the ability to port, build and port applications. And the really cool part for me is that, we will definitely see Kubenetes and open shift, and prem but even if you look at the Cloud the really nice part is that each of the Cloud providers themselves, provide a Kubenesos. Whether it's GKE on Google or Fargate on Amazon or AKS on Microsoft, we will be able to take identical architectures and leverage them. When we containerize high mark aft or spark we will be able to do this with kubernetes on spark with open shift and there will be open shift on leg which is available in the public cloud but also GKE and Fargate and AKS. >> What's interesting about the Redhat relationship is that I think you guys are smart to do this, is by partnering with Redhat you can, customers can run their workloads, analytical workloads, in the same production environment that Redhat is in. But with kind of differentiation if you will. >> Exactly with data plane. >> Data plane is just a wonderful thing there. So again good move there. Now around the ecosystem. Who else are you partnering with? what else do you see out there? who is in your world that is important? >> You know again our friends at IBM, that we've had a long relationship with them. We are doing a lot of work with IBM to integrate, data plane and also ICPD, which is the IBM Cloud plane for data, which brings along all of the IBM ecosystem. Whether it's DBT or IGC information governance catalogs, all that kind of were back in this world. What we also believe this will give a flip to is the whole continued standardization of security and governance. So you guys remember the old dpi, it caused a bit of a flutter, a few years ago. (anxious laughing) >> We know how that turned out. >> What we did was we kind of said, old DPI was based on the old distributions, now it's DPI's turn to be more about merit and governance. So we are collaborating with IBM on DPI more on merit and governance, because again we see that as being very critical in this sort of multi-Cloud, on prem edge world. >> Well the narrative, was always why do you need it, but it's clear that these three companies have succeeded dramatically, when you look at the financials, there has been statements made about IBM's contribution to seven figure deals to you guys. We had Redhat on and you guys are birds of a feather. [Murhty] Exactly. >> It certainly worked for you three, which presumably means it confers value to your customers. >> Which is really important, right from a customer standpoint, what is something we really focus on is that the benefit of the bargain is that now they understand that some of their key vendor partners that's us and Ibm and Redhat, we have a shared roadmap so now they can be much more sure about the fact that they can go to containers and kubernetes and so on and so on. Because all of the tools that they depend on are and all the partners they depend on are working together. >> So they can place bets. >> So they can place bets, and the important thing is that they can place longer term bets. Not a quarter bet, we hear about customers talking about building the next gen data centers, with kubernetes in mind. >> They have too. >> They have too, right and it's more than just building machines up, because what happens is with this world we talked about things like networking the way you do networking in this world with kubernetes, is different than you do before. So now they have to place longer term bets and they can do this now with the guarantee that the three of us will work together to deliver on the architecture. >> Well Arun, great to have you on the Cube, great to see you, final question for you, as you guys have a good long plan which is very cool. Short term customers are realizing, the set-up phase is over, okay now they're in usage mode. So the data has got to deliver value, so there is a real pressure for ROI, we would give people a little bit of a pass earlier on because set-up everything, set-up the data legs, do all this stuff, get it all operationalized, but now, with the AI and the machine learning front and center that's a signal that people want to start putting this to work. What have you seen customers gravitate to from the product side? Where are they going, is it the streaming is it the Kafka, is it the, what products are they gravitating to? >> Yeah definitely, I look at these in my role, in terms of use cases, right, we are certainly seeing a continued push towards the real-time analytics space. Which is why we place a longer-term bet on HDF and Kafka and so on. What's been really heartening kind of back to your sentiment, is we are seeing a lot of push right now on security garments. That's why we introduced for GDPR, we introduced a bunch of cable readies and data plane, with DSS and James Cornelius wrote about this earlier in the year, we are seeing customers really push us for key aspects like GDPR. This is a reflection for me of the fact of the maturing of the ecosystem, it means that it's no longer something on the side that you play with, it's something that's more, the whole ecosystem is now more a system of record instead of a system of augmentation, so that is really heartening but also brings a sharper focus and more sort of responsibility on our shoulders. >> Awesome, well congratulations, you guys have stock prices at a 52-week high. Congratulations. >> Those things take care of themselves. >> Good products, and stock prices take care of themselves. >> Okay the Cube coverage here in New York City, I'm John Vellante, stay with us for more live coverage all things data happening here in New York City. We will be right back after this short break. 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(bright music) >> Hello everyone, welcome to a special Cube Conversation here, in the Palo Alto studios, for theCUBE, I'm John Furrier, the founder of SiliconeANGLE Media and theCUBE, and cohost of theCUBE. My next guest is Adrian Scott, who is the CEO of Soma Capital and Head of Technology of decent.bet. You can get the idea of that going to be all about, but, industry legend-- >> Yeah. >> Star of the big screen, good to see you, thanks for comin' in. >> Thank you John, it's great to see you. >> I'm glad I wanted to talk to you, because I know you've been doing a lot of traveling, you've been living in Panama, and overseas, outside the US, mainly around the work you've been doing on the crypto side, obviously Blockchain and with the start of decent.bet, lot of great stuff, but congratulations on a successful initial coin offering! >> Thank you. >> Great stuff, but you're also notable in the industry, initial investor in Napster, our generation, first P2P, the first renegade, you know, break down the movie business, but the beginning of what we're now seeing as that decentralized revolution. But you've seen many waves of innovation. You've seen 'em come and go. But this one in particular, Blockchain, decentralized internet, decentralized applications, crypto. Pretty awesome, and lot of young guns are coming in, a lot of older, experienced, alpha entrepreneurs are coming in like yourself, and, we're lookin' at it too. What's your take on it? I mean, how do you talk people that are like, "Well, hey, this is just a scam on the ICS site, "is this real, is it a bubble?" Share your vision on what this is all about, this whole mega-trend, crypto, decentralized. >> And I'll also add, in addition to what you mentioned, the other neat thing here is just the global nature of it. Because we're so used to being Silicon Valley-centric, and having to dig around for funding here, and also, looking only at talent that would move here, whereas with this whole new industry, it's very global, there's global teams, international teams, and, some of the Silicon Valley folks are just struggling to stay relevant, and stay in the game, so that's a fascinating aspect to this new revolution as well. >> And also, the thing I love about this market, it's very efficient, it takes away inefficiencies, in venture capital right now, and private equity being disrupted, that's where the arbitrage is, hence the ICO bubble, but, there is real, legit opportunities, you have Soma Capital, you're an investment fund, that you're doing token investments on. The global nature is interesting, I want to just ask here about this, because, my view is, it changes valuation, it changes valuation mechanisms, it changes the makeup of the venture architecture, it makes up on how people recruit teams, the technology used, and with open source, I mean, this is a first-time view at a new landscape. You can't take a pattern match, model, to this, your thoughts. >> Agree completely, and the efficiency you mentioned, applied to teams, and surfacing engineering talent, and the mathematical minds that can handle crypto internationally, the formation of teams internationally online is actually something special as well, so, with Decent Bet, our team, our founding team includes folks from the US, Panama, Australia, as well, who met up, in a Facebook chat group! And that's how they initially connected, and they didn't know each other physically, before this connection online, and that led to this project, Decent Bet, and ICO, and so on. So it's-- >> You created value from essentially a digital workforce, but, I mean, it reminds me of, like in the old days, you'd chat, and it wasn't a lot of face-to-face, but then now there's video gaming culture, you know, you come in, "Hey, you want to play a game," people don't even know each other, and get a visual, and also an immersive experience with each other. This is now the application for entrepreneurial equations, so this kind of gaming, the game is startups! So how are you looking at this, and how are you investing in it, what are some of the things, and what can people learn from what we're seeing in this new game-ified, if you will, you know, world of starting companies? >> I think one of the things you alluded to there has really become visible, which is the importance of video, as a medium, and I'm still, absorbing and adjusting to that myself. For example, we do video communications, we do conversations at Decent Bet, of the founding team, and, it really connects to the community, and it's so important, and I'm still absorbing it, like I mentioned, 'cause I'm just so used to publishing articles that are very clearly written, and detailed, and so on. We just did an AMA video, an Ask Me Anything video, in Las Vegas, with the executive team, and it went for 80 minutes, answering the questions, that the community had all submitted! And I just try and imagine that five years ago, it's new way of relating-- >> 'Cause there was no blogging, link back, the only thing you could do in blogging. >> Yeah. >> And then write a perfect blog post, or white paper. >> Exactly. >> And that was who you were. >> Yeah. >> Not anymore, it's more community driven. >> Exactly, and that video as a piece of it, has become so, so important, as a way of communicating the character of the team, and-- >> Before we get into decent.bet, I want to drill those, I think it's a great use case, and again, congratulations on great work there. I want to ask you about something that I've been fascinated with, because I obviously, our generation, we grew up on open source when it was second-class citizen, now it runs the whole world, as first-tier, first-class citizen in software world. The role of the community was really important in software development, 'cause that kept a, it kept a balance, there was governance, was consensus, these are words that you hear in the crypto world. And now, whether it's content and or ICO, the role of the community, and certainly, areas that's out of control in the ICO site, people are cracking down on certainly, like you see Facebook and Twitter trying to do something, but you can't stop the wisdom of the crowd. The role of the community in this crypto, decentralized market, ICOs and whatnot, is super important. Can you share your thoughts, and color commentary on why the community's so important, how do you deal with it (laughs), any best practices, either through scar tissue, or successes, share your thoughts on this. >> Oh yeah, it's totally become a factor, and it's 24/7, right? So, when you are running a crypto project, you need your community management team to be there, in the community channels, 24/7, you need to have somebody there, and they need to be at a certain level that they can handle the challenging questions! And we've definitely had moments where, we have people who try to create FUD, potentially, you know, and bring up stuff, and bring it up again later and whatnot, and we need to be proactive, so when questions come up, we were there to be able to explain, "Okay, here's where you can see this on the Blockchain. "You can verify it yourself." And sometimes, it happens when the team is just about to get on a plane (laughs), and be out of internet communication for a while, so, it's a real challenge, and there's been the voice of experience, on that. >> So talk about how you guys connect, because obviously, being connected is important with community access, but also, with connection, increases the service area for hacks, are you guys carrying five burner phones each, how do you handle email, how have you guys dealt with the whole, you know, there is a lot of online activity, certainly, people trying to do some spear phishing, or whatever tactics there are. Telegram has been littered with a lot of spoofing, and what not, so, all this is going on, that you got to have access communication. But there's a safety component that could have really big impacts to these businesses, that aren't tokeners, because, hacking can be easy if you don't protect yourself. >> We really like Signal app, as a communications medium, there's a new one, starting to grow now, called Threema, which is pretty interesting. Telegram, is just a real challenge, and it's unfortunate, because it's now become this metric. >> How many people are active on your channels-- >> That investors like to look at the size of the Telegram group, but we don't actually have a Telegram group for Decent Bet. And we've used Slack, we are going to be rolling out a internally hosted Slack replacement soon based on Rocket.Chat, we really like Rocket.Chat. As you mentioned, there are spear phishing, we do see that, and, one of the nice things is, a few years ago, you had trouble convincing a team to take security seriously! But you know, when you have team members who may have lost $10,000 in a hack-- >> Or more! >> Or more, you know, there's no question that this needs to be a priority, and everybody buys in on it. So that is one net positive out of this. >> Well let's talk about Decent Bet, fascinating use case, it's in the gaming area, gaming as in like betting, my friend Paul Martino invested I think in DraftKings, one of those other companies, I forget which one it was. In the US, there was regulatory issues, but, you know, outside the US where I think you guys are, there's not as much issue. Perfect use case for tokens, in my opinion. So, take a minute to explain Decent Bet, what you guys are all about, and talk about the journey of conception, when you guys conceived it, to ICO. >> Yeah. Decent Bet was founded about a year ago, by the CEO Jedidiah Taylor, who developed an interesting idea, and plan, so, the neat thing about Decent Bet is, first of all, you have all the benefits of the Ethereum Blockchain, in terms of verifying, transactions, and verifying the house's take. Additionally, what Decent Bet does is distributes all the profits of the casino back to the token-holders. 95% goes as proportionally, and then 5% is awarded in a lottery, so there's no profit for any Decent Bet entity, it all goes back to the tokenholders. So you use the token to play, by gambling, but you can also use your token to convert into house shares, for a quarter, and participate in-- >> So the house always wins, that a good model, right? >> Yes. >> You could become the house, through the tokens. >> Exactly, so, the motto we use is our house is your house (laughs). >> Don't bet against the house. >> Yeah. >> Alright so, I love the gambling aspect of it, I think that's going to be a winner. Tech-involved, ICO process bumps, learnings, things you could share with folks? >> Yeah, so, on the technology, one of the neat things we are doing is, we do offer a slots game, which is a primary component of online gambling, and casinos, a pretty dominant piece of the action. But, if you are going to do a simple slots game on the Blockchain, and wait around for blocks to be mined, you're not going to have a great experience. 'Cause you're going to be waiting around, more than you're going to be clicking that button. So, what we use is a technology called state channels, which allows us to do a session, kind of on a side channel, so to speak, and through this state channel, at the end of the session, you post back the results. So you get the verifiability of the Blockchain, but without the delay. So that's a major difference. >> That's off chain, right? >> Yeah. >> Or the on chain is off chain. >> It's kind of-- >> So you're managing the league, to see the chain, so you still experience, and then get to preserve it on the chain. >> Exactly-- >> Okay. >> In terms of the ICO experience, we initiated the ICO end of September, ran for a month, raised more than 52,000 Ether, so very productive ICO process, but with actually some interesting details, so, the ICO structure limited the amount that a particular address could purchase, in the first phases, to 10,000 worth, and then 20,000 dollars worth, with the idea of getting the tokens into the hand of, of people who are going to potentially use them for betting, not just-- >> The more the merrier for you, not, no one taking down allocations, big players. >> Exactly. >> Or whales. >> Not just for the whales, take all, kind of thing. So, that was a interesting structure, and-- >> And that worked well? >> Yeah! >> Alright, talk about the dynamic of post-ICO, because now you guys are building, can you give an update on the state of where you guys are at with the product, availability, how that's going, 'cause obviously you raised the capital through the ICO, democratize it if you will through clever mechanism, which is cool, thanks for sharing that, now what happens? Now, what's going on? >> Yeah, I mean, I think we're doing pretty well in terms of hitting milestones, and showing progress compared to a lot of projects, we released our test net, with slots, and then sportsbook, at the beginning of January, and mid-January, for sportsbook. And, we also did some upgrades with our wallet, we released that, for some enhanced usability, and handling during high peaks on the Ether network, Ethereum network. And then, also, our moving to main net. So we did some newer versions of the test net-- >> When did the main net come in? >> Main net is coming out end of April, and we're on track with that. >> Great, awesome. Congratulations, congratulations on a great job, 52,000 Ether, great raise there, and awesome opportunity. Soma Capital. >> Mm-hmm. >> You're investing now, what do you look for for deals, there's more money chasing good deals now, as we can see, has been a flight to quality obviously. Great global landscape still, what are you looking for? And advice to folks who are looking to do a token, sale, what's your-- >> Big thing we look for are real projects, so (laughs), and they're not that many out there, so we do look for a real use case that makes sense, because, there's a lot of folks out there just sticking Blockchain tag onto anything. And it's not just-- >> Like Kodak for instance. >> Yeah. >> Kodak's the prime example. >> Yes. There are projects out there doing interesting things, Guardium is doing some neat things in terms of 911 response, and opening that up, and creating an alternative to government services. There's WorkCoin, which is-- >> Do you invest in Guardium? >> Yeah, in Guardium, yeah. >> I interviewed them in Puerto Rico. >> Okay, great. >> Great project. >> So very interesting, I was recently giving a talk at a university in Guatemala, and, the students there at business school, it really resonated, the message there, to them, about okay, government 911 is maybe not the ultimate solution for getting help when you need it. >> Well I think, there's a lot of this AI for a good concept, going to Blockchain for good, because, you're seeing a lot of these easy, low-hanging fruit applications around these old structural intuitions. And that's where the action is, right, I mean, do you agree? >> Yeah, yes. And the other thing we're looking at is not just Blockchain. So I really like talking about the field more as crypto, and, I have a little video I did on calling it kind of decentralized, crypto-enabled applications, or platforms. So, beyond Blockchain, we have DAGs, Directed Acyclic Graphs, one interesting-- >> Like Hashgraph. >> Yeah, Ha-- >> Hashgraph's a DAG, isn't it? It's kind of a DAG, Hashgraph? >> Yeah, so, I'm not a huge fan of Hashgraph, one that I do like is called Guld, G-U-L-D, which is, again, thinking beyond the Blockchain. 'Cause we get so tied into Blockchain, Blockchain, Blockchain-- >> What does beyond the Blockchain mean to you? Thinking beyond the Blockchain, what does that mean to you? >> So, the proof of work process, the mining process, the creating new blocks process, is one way of doing things. But we have all these other things going on in crypto, like the signing process, and so on, and so, you can use those in a DAG, a different architecture than just this mining new blocks, you know, mental model. And so, that can be used for different use cases, for publishing, for group consensus, and so on. And so, Guld is an example of a project where it looks like there is something real there, and that's a very interesting product. >> Advice for folks that are looking at tokeneries, because, again, we've said this on theCUBE many times, people know, I'm beating this drum, you got the startups, that see an opportunity, which is fantastic, and then on the end of the spectrum, you got the, "Oh, shit, we're out of business, "let's pivot, throw the Hail Mary, put Blockchain on it, "crypto, and get an ICO, and get some going." And then you've got these growth companies that are, either self funded and or growing, that have decentralized kind of feel to it, it has an architecture that's compatible with tokenization. >> Yeah. >> So we see those three categories. Do you agree, am I missing anything? In terms of the profile? And which ones do you like? >> Well, I think one thing that we need to look at, in each of those cases, is decentralization actually happening, in the project? And are people actually thinking about decentralization. Because, it can be scary for a traditional company! Because, if it truly becomes decentralized, you're not controlling it anymore. And so, that is-- >> If you're based on control, then it's incompatible. >> And that's the real Hail Mary, right? (laughs) When you give up that control, if you give it up, so, we have examples coming out, where, you know, Ripple is running just a few nodes, Neo's running a few more, and you know, things that are not really decentralized, and they're saying, "Well, we're going to be," (laughs) you know? >> Will they ever? >> Is it going to be in the future-- >> Yeah, that's always the question, will they ever be? They've already made their money, well certainly Ripple's done well, but, I mean, what's the incentive to go-- >> Yeah. >> Decentralized. >> Yeah, so if, if you are creating a new project, the benefit from this architecture, beyond the money, is to think about it in that decentralized way, and figure out token economics that work, in that context, in that paradigm! And that's really where the challenge is, but also really where some of the benefits can rise, because, that is what enables truly new ways of doing things. >> Talk about the dynamic, because I actually, I live in Silicon Valley, I've been here 19 years, going on 20, you know, I moved from the east coast, and basically, if you weren't here, this is where the action is. If you're in the sports of tech, this is where all the athletes are. That's now changed, as you mentioned earlier, when we started, it's everywhere. Now, also there's jurisdictional issues, I mean the US, one guy's told me, the US is turning into Europe, all these regulations, it's not as much free capital as you think, and then, we certainly know that. With FCC, and others are putting the clamp down. But, structuring the token, is a concern, right? Or consideration. >> Yes. >> And a concern, so, you know, US entrepreneur, what should they do in your opinion, and if someone's outside the US, what do they do? What's the play book, or, not play book, what's the best path right now? >> Leave the US (laughs). Move out of the US. >> Tell that, wife and four kids. See you later. Yeah, but that's real legit, that's-- >> Come and check out Panama, one of my friends is building a Blockchain incubator, crypto-incubator, I mean I think if you're-- >> What's it like to move out of the United States, I know you just recently went to Panama for this, but, what's it like? Is it scary down there, I mean, is it entrepreneurially friendly? What's the vibe, what's the scene like, take a minute to explain that. >> So I've actually been out there 12 years now, in Panama. One of the neat things, you want a place that has an international outlook, international perspectives, so, you want to think in terms of a Dubai, a Singapore, a Hong Kong. And so, Panama has some aspects of that, it's not perfect, but it does have that international perspective thanks to the Canal! So it has, you know, a hundred years! (laughs) >> It also has the Panama papers, which is a negative blowback for those guys, so it's a safe place to do commerce, in your opinion? >> Um, it is a nice geographic base to do international commerce. >> Got it. >> So, you don't necessarily want to rely on the local jurisdiction, but, in terms of a geographic base, that is US time zone, US dollar, no hurricanes, it's a very interesting place. >> Puerto Rico's got the hurricanes, we know that. >> Yeah. >> Final thoughts, just overall perspective, you've been around the block, we've been around the block, both of us have, I mean, I kind of have these pinch me almost like, "Damn, this is great time, "I wish I was 22," I mean, do you have those? What's it like, how you explain this environment? If people ask you, "Hey, what was it like in the old days?" You know, when you have to provision all your own stack, and do all the stuff, it's pretty interesting right now. What's your thoughts? >> Yeah, I mean, I think we're going through an interesting moment right now, where, we are getting to a point where the forces of centralization are coming against the forces of decentralization, and that includes from the regulatory, as well as the business side, and so, I think it is important, as we look where to dedicate our efforts to, to really find ways to increase the decentralization as a factor that encourages creativity, and entrepreneurship. >> Yeah, it really is a personal, I think it's a great environment. Decent.bet, bet, make your bets, any updates on how to get tokens, what people can expect, a quick plug-in for Decent. >> Yeah, check out our website, we've got links to exchanges, the token is currently listed on Cryptotopia, HitBTC, and a couple other exchanges, and, yeah! Please check out the test net, please check out the white paper, and just learn about how this protocol works, this platform works. I think it is very inspiring, as a structure. >> Adrian Scott here, inside theCUBE, Soma Capital, also experienced entrepreneur himself, technologist, and has been through the ICO process, head of technology at decent.net, we'll be checkin' it out, it's theCUBE Conversation, I'm John Furrier, here in Palo Alto, California. Thanks for watching. (bright music)

(uptempo techno music) >> Announcer: Live from Washington, D.C, it's CUBE Conversations with John Furrier. >> Hello there and welcome to this special CUBE Conversations here in Washington, D.C. We're getting all the stories, we're at the Halcyon House here with Kate Goodall who is the Co-Founder and CEO of Halcyon for a CUBE Conversation. Thanks for joining me today. >> My pleasure. >> So talk about Halcyon and your mission. You're doing something really important here in societal entrepreneurship. It's a non-profit, it's a really interesting mission. You're having an impact. Talk about what you guys are doing. >> Yeah, we believe in the power of human creativity and the power of compassion to change the world for the better. And by that I mean that we take some incredible change makers with really bold ideas about how they can affect societal change through business and art, and we give them a number of supports including a free place to live in this very expensive city, a fantastic mentor, an office, a community around them, money, and we don't take equity in their ventures. >> And this house that we're here is a mansion in Washington, D.C. Talk about the story about this house and this residence. >> Yeah, it's got very revolutionary roots. It was built by Benjamin Stoddert who was the first Secretary of the Navy during the Revolutionary War. And from then it exchanged hands several times. One of them was a relative of Mark Twain. And he is responsible for most of its 30,000 square feet. And then lastly, it was in the hands of the Dreyfus family before it was bought by Dr. Kuno who is my co-founder and the chair of Halcyon. >> And the Halcyon mission, you guys have a unique formula. Talk about how the fellowships, how do you guys select the ventures, what's the program? They live here. >> Yeah. >> It's a residence. >> Yeah. >> So it's interesting. >> Yeah, we give them three things, everything thing breaks down into three things. Space, community, and access. We believe that if you give people not only physical space, which is important because we have to remember that not everyone has a parents' basement they can live in and friends and family they can go get money from. So it democratizes the playing field to just be able to select people with the best ideas and the most talent and not the best drive. But also head space. What does it mean when you give someone with a brilliant idea five months to just work on their idea? Then community is very, very important. There's a lot of atrocious analogies for entrepreneurship. People compare it to staring into the abyss or chewing glass or... It creates a lot of emotions, lots of ups and downs. So having a built in community, which we have here is very important. Then lastly access, and by that I mean there are not only investors, but these days governments, philanthropists, others that are seeking solutions to some of these very hairy 21st century problems. They want access to these ideas. And if we do our job correctly, we're creating a bridge for these entrepreneurs to those people as well. >> Yeah entrepreneurship certainly is hard. And it's even harder when you're trying to crack the code on societal problems. >> Kate: Yes. >> And so this kind of brings up an interesting trend that we've been seeing emerging really rapidly in the past few years with cloud computing and other... Big data, internet of things technologies on a global scale, is the societal entrepreneurship model where you're accelerating opening up new ways to democratize, crowd source, fund, and change the game and reimagine philanthropy, policy, education, diversity, all in one. >> Yeah. >> You guys are kind of doing that here. It really is a ground zero here in Washington, D.C because of the access and the ecosystem of governments and everything's here. So you're seeing this building up in Washington, D.C. Talk about this new force, this new driving force of change called societal entrepreneurship. >> Yeah so it's, we believe it's definitely one way to really change the game. It's a way to use business principles to attack some of these enormous social problems. Many would argue that philanthropy and perhaps government have failed at some of this recently. Philanthropy was originally designed to solve problems, not to become a charity machine. And certainly, the government finds it hard to do some of those things today as well. And so figuring out how to really attack some of these enormous, hairy 21st century problems using these business principles so that their solutions can also be scaled effectively is absolutely what we're trying to approach. >> It's interesting, you see the old guard, the old ways of doing things, policy, people just checking boxes, philanthropy a big donor kind of model. And then now with cloud computing, new things are emerging. In your mind, what's changed the most now from just even 5, 10 years ago? What's the big difference in today's culture and today's environment in the world and Washington, D.C? >> Oh my gosh, so many things I could talk about. One of the reasons I think that social enterprise really came into being, partially is because there was recession and millennials didn't have jobs. So they had to create them and they created them in a new model. They created them in a way that gave them satisfaction beyond just getting a paycheck. The Jobs Act gave foundations the ability to invest in for profits and gave us crowd sourcing and crowd funding. And these things have really made some of this cross sectoral pollenization possible for the first time. I think people genuinely are frustrated that this amazing pace of change and Internet of Things and all of this stuff still hasn't solved some of these big problems. So there's so many forces at play. And I think one thing that I'll also point to because as I explained to you, I'm an archeologist and historian by training, and if you look over the course of human history, any time when you've had rapid change in technologies or you've had vast inequalities in terms of wealth, you end up with a depression or a war, or both. And I really believe that the power of social entrepreneurship can, for once, maybe let the gas out of the balloon a little bit more gently, and I think that's something really great to be optimistic about. >> How do you see that happening? I mean, we're a connected society now. >> Yeah. >> We have our mobile devices. >> Yeah, yeah. >> We have our things on our body, Internet of Things. It's all there, is that how you see it? How do you see the relief coming so we don't have a war or a depression? >> Yeah, I think that's the point, we have tremendous power now, right? To just in our hands, to be able solve some of these problems. Human ingenuity is a great thing. I think creativity and compassion are going to be the things that machines replicate last. And so we support that wholeheartedly. And I think maybe we can talk about some examples of some of our ventures, right, and what they're doing because I think that's the best way to paint. What does this mean, what is it? One of our current fellows, Ryan Soscia has created JDoe which is a way to anonymously unite victims of sexual assaults so that they can take legal action. It has a business model, but it's been proven that victims of assault are much more effective when they go as a group instead of alone. So it's a really brilliant way to use technology. Another one from our past cohort, Brandon Anderson is using a chat bot, Raheem AI to collect better data on policing. And then is working with police departments to use that data so that they can have better community relations. So these are both very relevant and timely issues that we're approaching in a non-partisan way using technology to solve. One more I'll give in our current cohort. Pilleve, which is a company that's thinking about the Internet of Things and how it can solve for the opiate crisis. They've created a pill bottle that connects to your phone or your family's phone and can give data and control over medication so that you can really start to attack addiction. >> Kate, talk about the power of we capital, what you've been doing with women's networking in Washington DC. >> Yeah. >> Because it's not just the women in tech inclusion issue, there's a lot of disparity we've been covering certainly at Silicon Angle, but there's really a lot of powerful women and talented folks, whether it's creative or on the business side or technical side, where the societal problems, these are products that are used by the entire population and so there's an effort to have more women involved in not just designing products, but actually being part of these new re-imagined solutions and technologies. >> Yeah. >> How important do you see that here, and what are some of the hurdles and successes that you've had here? >> I agree with that analysis completely. And I'm biased, but I think that Washington is an amazing city for some incredibly smart women. And when we created Halcyon, we created a committee that was diverse and reflective of the diversity we wanted to see how cohorts. So diverse by any factor. Age, gender, race, sexual orientation and what's that resulted in happily is a housing community that has 52% of our ventures founded or co-founded by women, and 58% of our ventures founded by a person of color. But then when we looked around, the investor base didn't exactly reflect our fellows. So we started to think about how we could engender and cultivate investors that were also diverse. And one of the ways to do that was to create a group of women in D.C. that wanted to fund social impact, leaning women led ventures, and it's called the WE Capital. It's led by Dr. Kuno, who is my co-founder and chair at Halcyon, and Sheila Johnson who was one of the founders of BET and has now founded Salamander Resorts. And there's 13 other remarkable women in that contingent and they're all paying it back. But and a very smart way that gets them market rate returns. >> This is interesting, the community paying forward has been the ethos of very robust and successful communities Silicon Valley here in Washington, D.C. How do you scale that? How do you go global with this? Because now you have a global model. Silicon Valley D.C. and all around world where you now have different communities coming together, all the same mission potentially. How do you blend it all in? How do you take that to the next level? >> That's a good question. We're gradually building what I call a kind Army. Just this amazing community that has ripple effects. We don't feel that we have to own or control this in anyway. Just over 3 1/2 years, we've had 55 ventures come through here. They've raised nearly $40 million dollars. Impacted half a million people around the world in a positive way. They've created nearly 500 jobs. You start to see the exponential growth even just as we sit here in this building. But I do think that's a long way to go in terms of people understanding this social societal entrepreneurship. People have different definitions for it and it's a long way to go in term terms of government and philanthropy really being able to understand it. Because in some ways as I mentioned, they lost touch with who their customers are. >> Okay and I've always been saying in Silicon Valley and on my Facebook page and also on theCube that SiliconValley doesn't get D.C. They try to come in waves around. You don't get it and they're impatient, I would say if I categorize. They get D.C. but I don't think they have the patience for it. It's a new culture here. Also the pace of change is accelerating in D.C. but it's a formula for D.C. What is the secret to be successful in Washington, D.C if you're a tech entrepreneur or investor or someone from Silicon Valley or not from here? >> We do get the advantage of being able to see who does that well and who doesn't. And tech is obviously leading ahead of policy. Policy is trailing tech and I think that can understandably make policymakers nervous. They've got a lot of understanding to do to be able to make some policy decisions. And these tech solutions are very complicated so the people in tech that I see being successful around policy of those that will take the time to really sit down and pick through a problem with policy maker and help them to understand it. Policy makers are actually very smart but they're dealing with a lot. >> John: So education. >> Education, education absolutely. You can't come in here >> Patience. >> And be impatient that they're not getting it. But I think that's going to essential. We've got to figure out how to talk each other and how to talk across different languages, different domain, different sectors and creates some better intersectionality. >> So what's next for Halcyon? What's the vision? What's your vision of how this will go forward? Obviously you've got a great model, batches coming through cohorts, and you have demo days here. I noticed your set up downstairs for a demo day so it's very robust, classic incubator, accelerator model with the residences leading it there. What's next? Where do you go from here? >> We don't take equity in any of our ventures but we are thinking about creating a fund, because so many of our ventures are performing exceptionally well. And we're actually going to be launching a festival that really takes the power of creativity and compassion, and art and technology here in D.C. and that will be in June. And we're hoping it that way, we can reach a wide audience, and that's going to be very exciting. The long term vision really is how can we harness the power of compassionate and creativity to solve 21st century problems, and how can we do that at scale? >> The classic disruption model is gate keepers start being disrupted by the new guard as Andy Jassy would say in Amazon. These a new creative as well. I did a panel at Sundance a few weeks ago where we talked about this creative where democratization is happening at artist level, and the government maker level. And that seems to be happening across all industries. A new creative is developing. What's your view of the digital impact? Because artistry can be sculptures and painting and whatnot to classic artistry or film making but now tech's involved, digital. >> Yeah. >> It's coming together. Is the vision how you see art and science coming together? >> Yeah, artists are fantastic disrupters. Sometimes they don't even need to paint a picture. They just use their ability as an artist to do things other people can't. And that's why they're awfully fun to be round. I think that you're absolutely right. I point to Dee Rees as an great example, who didn't get her funding for her film Mudbound through the the Hollywood machine, instead she went straight to Netflix and now she's getting an Oscar. That's a new way of doing things. We have one of our fellows, DeShuna who created kweliTV which is Netflix for the African diaspora because Netflix just doesn't have the kind of black filmmaking that she wants to see. So yeah I absolutely see people using digital to do different kinds of disrupting including on the outside of things. We have another program, the Arts Lab. Very similar to this but working with excellent artists who are thinking about social justice. One of the artist, Georgia Os-acs is doing a project called Two Future Women. And she's collecting letters that women are writing to other women 19 years from now. They're being archived by the museums in D.C. and will be displayed on the eve of the Women's March. Wouldn't it be great to know what the suffragette were thinking? And that all requires technology to be able to successfully collect those, disseminate them, archive them et cetera. >> So New channels to the market place breaking down the barriers for the gate keeper seems to be the trend. How is that happening in your world, in D.C and in philanthropy? You're now creating a new model of entrepreneurship. >> Yes, yes. >> Not just philanthropy, hey nice job or policy check box, it's real change. >> And arguably a new model for philanthropy because very rarely is philanthropy so immersive where we're literally taking these people and we're in the living with them for five months, and giving them all of these supports. And I think it's also a new model and that it's risk taking. It's not a safe and secured, metric based, proven solutions. It's some of these centers are going to fail and I think that that's okay. That's just testing and trying and finding the best and moving forward. I was going to make another point. >> You guys are changing the world obviously, I made a comment on Facebook, we're saving the world at the same time because you mentioned you can actually get ahead of some of these trends with this gap. Whether it's inequity, inequality or however these gaps are causing even war or depression as history points out. Now you have an opportunity to use, not just diagnostic capability but predictive and prescriptive mechanisms. What are some of those things that someone could see and connect the dots around an example of something that's prescriptive. Say wait, wow, time out. We've got something going on over there as a problem space we can solve with a solution. What are some examples that you see playing out where this model could work? >> I'm not sure I quite understand the question. >> If you had the ability to use technology to solve some societal problems, what are some examples that you're seeing here in your incubator that are pointing to this new trend? >> Yeah, I think that our fellows are fantastic examples of that. Many of them are tech enabled whether or not they're using apps or the cloud or just a new actual technology product. One of our fellows is using, he's created a new product that disrupts the vestibular system so that you don't feel motion sickness. Now this is actually a product that is obviously very valuable for just everyday people, who are going to be in driver-less cars trying to do their work. But it turns out very useful for the military and very useful for people who are trying to create virtual reality. 40% of people can not put a virtual reality headset on and not feel nauseous. So I do think that it is tech's job to solve some of the problems that we haven't been able to solve yet. In many ways, the internet and the Internet of Things is our biggest leap forward since fire. Now how are we going to use it to create the disruption that fire did? Fire allowed us to eat more things, grow bigger then start to farm and and I think that we haven't even hit the cusp of what the internet can do yet. It can do way more things and deliver products to our doorsteps. >> Next up at the wheel, you get fired-- >> Right, what's is the tech wheel? I think it's going to be really-- >> Personal question for you, what is the big learnings that you've had over the past few years? (mumbles) say well I didn't expect that to happen or wow, that was super awesome or a failure or a success? What was your big learnings that you've come out-- >> Oh my gosh, do you have an hour? We've learnt how not to do and how to do mentorship very well. You can't take mentorship lightly. This is human chemistry we're talking about and even if you think you've got the perfect match on paper, it may not work. We have certainly learned a lot about how it is really important to have investors that reflect entrepreneurs because to your very point, that work is going to take everyone to create technologies that work for everyone. It also creates and builds even investors who look like everyone because otherwise there is an inherent bias. Really good people have inherent bias and that needs to be solved for. Because I straddle both art and entrepreneurship in my role. These some really interesting things that I've noticed in terms of how entrepreneurs see the world as infinite resource and artist see it as very finite. And how some of our systemic problems are reflected almost identically in both fields. This is an interesting statistic. 5% of venture capital goes to women, we know that and 1% to African Americans, 0.01% to Black women. In the museum world, in museums in the western hemisphere, 5% of their art collection is women artists, 1% is African American artists. That's not a coincidence, that's a clear picture of how power structures have evolved to make certain types of decisions about who should get capital, who is worth collecting, and we're definitely solving for that. >> And certainly having a lens on that and exposing that-- >> Kate: Absolutely. >> Is the way to-- >> It's very important. >> Talk about artistry, one of the things we've been talking about in the software and in the tech business is the role of artistry and craft. And that we see that swinging back with cloud computing. I would say to the craft out a software development but you're seeing these integrated solutions where craftsmanship and art are coming together. We're seeing examples, certainly in Asia, in China we're seeing examples where the development world, the technical world has come together with artistry world to create these new solutions. So you've got creative and you've got technical coming together. That's what you're doing. >> Yeah, no absolutely. >> What's the success formula? Is there one? Is it right brain, left brain, what's the-- >> I don't know. We've just got this bubbly caldron of creativity and we're pulling stuff out of it as we go, but I think it's important for us not to forget about art. Art has been at the forefront of every social change, every movement. If it does its job, it's of the moment and it tells us a lot about ourselves. But there's also that important thing about art with technology, and with consumer products. The reason that the iPhone was so successful is because it's a thing of beauty, and everyone is in awe of it. So design is critical, it's absolutely critical when you're thinking about scale or consumer products or tech that works. >> And having a good taste for a good art is also a skill. >> Yeah. >> Knowing what's beautiful. >> Of course. >> Tech guys love to have that skill. >> You could argue that that's getting democratized and disrupted as well. >> Kate, thanks so much for spending some time here. >> My pleasure, this is fun. >> Cube Conversation, Kate Goodall, co-founder and CEO of Halcyon here in Washington, D.C. Changing the world, societal entrepreneurship. A lot of great actions. This is theCube coverage. Thanks for watching. (uptempo techno music)

>> Announcer: Live from Las Vegas. It's theCUBE covering VMworld 2017, brought to you by VMware and its ecosystem partners. >> Okay, welcome back, everyone. Live here at VMworld 2017 day three wrap-up. We're going to wrap up the whole show. I'm John Furrier with Dave Vellante, Stu Miniman, Keith Townsend. Cube, set, two sets of coverage. Guys, great job, we have Justin Warren as well, John Troyer, Lisa Martin. Great team, guys, amazing. Three days, a lot of content, wall-to-wall coverage. Double barrel shotgun of Cube content. Amazing. What's left in the tank? Let's get this done. Dave, your thoughts as VMworld comes down to a close. >> Well, so I missed VMworld last year as you know, 'cause I was doing another show. Pat was giving me a lot of grief for that. But if I go back two years ago, two years ago VMware was shrinking. Its license revenue was in decline. Its cloud strategy was in continued disarray. Customers were kind of, you know, losing a lot of faith. >> John: Ecosystem was in turmoil. >> And the world thought that Amazon was going to completely destroy this company. Fast forward two years later, license growth, you know, 12-13%, the company's growing. It's nearly eight billion dollars, three billion dollars of operating cash, big stock buybacks, clarity on the cloud and, I think, and I'd love for Keith's opinion on this, a recognition of the customers that "I can't just throw everything in the cloud." Okay, that's one thing, but what I can do is try to bring the cloud model to my data, and AW, I mean Amazon, sorry, VMware is going to be a partner in doing that. And I think those have all been tailwinds along with some product cycles and some >> John: And Dell Technologies buying out from the federation which was taking on water. Let's not forget. Let's not forget about the federation EMC owned VMware and that was bought by Dell. >> People talk about the Dell discount. I'm not seeing the Dell discount right now. >> What is a Dell discount? What does that mean? >> The Dell discount is because Dell owns VMware, just like when EMC owned VMware, it somehow shackles them and depresses the value. Michael obviously doesn't agree. >> So product focus as well has been not diminished at all. The products are front and center. They still got the sessions. Guys, on the product side, what's your view? >> Strong product offering. I really love the message they want. A lot of the response from the community was like, "Pat is feeling energized." He has this shadow of what is going to happen post-acquisition. Is there going to be a Dell discount? You know what? VMware, you know, famously, five years ago, Pat was onstage. He said he's going to double down on virtualization. He jettisoned Pivotal, and we were all wondering, "What is he doing?" Proved over the long run he was right. Last year, this year, he's doubled down, not on just virtualization, but on this concept of SDDC. And it's finally starting to pay off. We're seeing consistently this concept of VCF. VMware cloud foundation on premises, off prem, and even in AWS, ironically. You know, three or four years ago, we were like, well, is OpenStack going to eat VMware's lunch? VMware has turned the tables and become that OpenStack layer, that consistent cloud layer, at least for that legacy type of way to do IT. Taking your internal data center processes and moving them to the cloud consistently across their vCAN network in the AWS. >> So if I get this right, you're basically saying that VMware essentially went from a position where they're twisting in the wind at all levels, turmoil in every department, every, house is on fire, to pulling one major bold bet, grab it out of the hat, kicking ass, taking names, Pat Gelsinger and team made good calls. >> You know what, I'm not a fan of calling what VMware's SDDC thing a private cloud. I don't think it's true private cloud. It is valuable to the infrastructure, but it's not private cloud, but customers love the message. Take what I'm doing now, check an easy box, move it into AWS or vCAN and it's resonating. >> Well certainly, Stu just gave you the eye dagger, 'cause Stu, the true private cloud report from Wikibon, which has been going viral at the show, been the talk of the show, everyone has been talking about it, Wikibon's true private cloud report. People love that, too, because the message is simple, take care of business at home, called the on prem. Yeah, change the operating model, that's going to take some time. >> So, my thought on this is, for years, we were talking about the stack wars. Lately, we've been talking about the cloud wars, and for the last few years, when I talked to the partner ecosystem, they were shrinking their booths. They were looking for alternatives. Remember Cisco? Aw geez, flaying anything but VMware. Let's see if we can do this. You know, IBM who was a big VMware partner. Well, they got rid of X86. Where are they going to part with VMware? On and on, HPE going closer with Microsoft. Even Dell, pre-acquisition, how much deeper they going to go with Microsoft? Now, you know, John, we've been talking on theCUBE for a while. You know, there's Microsoft. Their stack, their partnerships, their application, where they're putting it. Amazon, huge elephant in the room, when they made the deal it was like, oh well, you know, Pat's on his way out the door, and he's kind of, you know, pulling one over on Dell before he leaves. Now, I think we understand a little bit better where this fits in that portfolio of the Dell family. Open source, still something we beat on Pat and EMC before that. They're not really open source. They've got a proprietary software alternative that their partners seem excited about. They've really fumbled around with their cloud strategy for a year. They've got one that seems to be going well. We'll see, 4,500 service provider partners, the Amazon thing. We will still see where revenue comes. >> Stu, that's a good point. Pat Gelsinger was kicking ass as a CEO now, but his channels on his job many times, so props to Pat. He made some good calls, stayed on course, held the line on the direction, did not cave at all, him and his team, they did it. There's been some turnover as we know in VMware. I'll see the results. I'll clear the scoreboard. They're winning. Question I'll put to you guys right now. Impact of Andy Jassy from AWS here on day one. How much of an impact was that? He made some statements. And the question I want to ask you, in addition to the impact, is he said, "This is not an optical deal." Most companies make optical illusional deals, make it look like they're all in, and they don't really deliver. So one, impact of Jassy being here and two, who was he talking about? >> Dave: Well >> Where's the Barney deal? >> Well, so okay, first thing is I saw, I've always seen that AWS deal from Andy Jassy's perspective as TAM expansion. Big part of a CEO's job is, I've got to expand my TAM, especially when you see the growth of AWS, and it's slowing down a little bit, even though it's still impressive. He's got to expand his TAM. Well, how does AWS do that? Look to 500,000 VMware customers. So that's number one. Barney deal? There are a lot of Barney deals out there. I mean, most... >> What are you referring to, 'cause Google came on the stage the next day. I was getting tweets saying "Azure?" Stu, guys, who's the deal? Who was Andy Jassy talking about when he was looking at the VMware customers saying, essentially, this is not, implying others are? >> I'm not sure that he was necessarily throwing shade at anyone specifically. What there was is there was 18 months from when this deal went through, a lot of work. This was a lot of engineering work. Talk to the cloud foundation team, talk to the VSAN team. The amount of work to actually integrate, because we know Amazon actually has an extensive engineering team. They hyper-optimize what they're doing, so this is not some white box that I just slapped VMware on and said the BIOS, you know, it works and everything where I still am a little concerned if I'm, you know, a VMware employee as customers, I talked to some customers that really excited about this, the Lighthouse customers. They say it's going to get my team that loves their vCenter. They love everything, it's going to help them move faster. Then, you're talking to, "Oh there's these services they're going to be able to use." I'm like well, how much are they going to realize oh hey, this is great, and the VMware sales reps are just going to get eaten by the lion while the customer goes off. >> And so the impact's big then, you're saying, but you won't answer the question of who he's referring to. You don't think he's referring to anyone. Keith, what do you think? >> Let's look at, I like the comment about how difficult the integration was. Last year when I read, it said something like, wait, hold on what, the AWS, who is notorious about controlling their message, what I thought was funny is that Andy didn't use the term private cloud, he didn't use the term VMware cloud, he, VMware infrastructure and AWS, which is a massive engineering effort. So from that, I question whether or not they could execute upon that, but Andy Jassy being onstage on Monday showed the commitment that we're going to make these other services work, the total addressable market of 500,000 additional customers. You don't do this for bare metal servers. >> John: VMware has 500,000 customers? >> Yeah. That's the total addressable market, but that's not where AWS is going to grow by halting physical servers, by selling more Lambda, selling more CDN, selling more PAS, is the key, and where VMware and AWS relationship his weak is in that true integration between the two hybrid IT environments. So when you say, "Where's the barney deals?" the barney deals are, I think it's across the industry. Unless you're getting fully in bed and committed to make that level of investment >> No but engineering resources, this comes back down to what, the new kind of engagement between biz dev deals look like. You need to have that kind of level. >> I have no problem pointing to the Nutanix Google deal, anything that people are doing with Azure, no one's partnered at this level. >> Okay, Azure is a good one too, because I've heard from startups that have been enticed by the dollars, 'cause Microsoft's been sprinkling some cash on, who have left to go back to AWS, because of technical reasons, reverse proxies, basically software clued just to basically make stuff work. >> Well, so, where do we, how much do we know about the IBM VMware relationship? Because I mean IBM's >> Pat brought it up today. >> Soft layer hosting, right? They've got a lot more experience with VMware, IBM has said, I think they're shipping, they've been shipping for quite some time. So there's an example of engineering that had already largely been done, that's actually delivering value for customers. Pat probably brought it up because it's a great distribution channel for him. And I think Keith's right on. AWS doesn't speak in terms of VMs. They talk in terms of cloud services, like Lambda, database services, middleware, PAS layers, that's really where they're going to hook people in this community into their platform. >> Okay, so here's a question to end the segment as we wrap up the show, because this is kind of where it's all going. To me, my big epiphany was the following. Andy Jassy, statesman, Harvard MBA, now CEO of AWS, ticking names, ticking this, huge accomplishments, he's done great in his career, he's only getting better. And then Sam Ramji, great developer chops, knows software ecosystems, not Andy Jassy in terms of the title, but in terms of status, still a solid guy. Two contrasting positions, running the biggest cloud today, to Google brainpower, okay? So you're looking at that and you're saying, "Hmm, where is this going to go?" So the question on the table is, what does it take for someone to be successful in today's IT environment? Does IT need to be smarter in business or does need to be more smarter in IT, or both, and does Google have enough IQ in IT to actually make the products fast enough or are they at risk? >> Well I'll take the customer point of view, and you know, we always talk about people, process, technology. The technology is maturing, and it's maturing pretty quickly, but maybe still not quite to the point where the true private cloud vision is where we need it to be, but what's going to slow that down is the people and process side is going to take a lot longer. Stu, you made a comment yesterday, VMware's moving at the pace of the CIO. >> It's Keith's line, he's been using all week. >> Okay, great line and Robin Matlock heard that today, course marketing CMO said, "And the CIO needs to move faster." (men laugh) Well guess what? They can't. I thought that was just a perfect testament >> But that is exactly the dilemma isn't it? >> It really is, and this stuff is hard. And cloud doesn't necessarily make it any easier, (laughs) if anything, it makes it more complex, 'cause it's a completely new business model. >> But remember the old term, forklift upgrade? Okay, you don't have forklift upgrades anymore, you have rip and replace, whatever word you want to use. >> Stu: Now we have lift and shift. >> Lift and shift, rip and replace, lift and shift. Is Google, and this is my challenge to Sam, I didn't have time to ask him this question, I'll certainly do one on one next time I see him. Is Google smart enough with IQ in IT, certainly we know they're smart enough, but do they have enough IQ in IT to really make the transformation, or are they betting on a rip and replace version of a cloud? >> So John, no doubt Google's smart, and they built amazing things that, the ripple that Google has through the industry is phenomenal. They spin off whole industries based on what they're doing. Google played a very different game than Amazon is, you know, when you talk to customers and how they're first getting onto Google, you know, data's really important, analytics of course. Couple of years ago Google was saying, "Oh, we're just going to be that data analytics cloud," now of course they're trying to be a big player. Amazon, the company, remember, Amazon isn't just AWS. Andy Jassy fits into Jeff Bazer's great plans. You know, I'd love to hear, when we go to reinvent, what's happening in Whole Foods that's impacted by AWS. They are everywhere, they are, you know, Walmart did. >> How about TAM expansion, my wife's checking Amazon even more. >> But this is really interesting right, because Walmart's now using its muscle to say, "Hey, you going to do business "with AWS" >> Absolutely >> "And Whole Foods? "You're not doing business with us." So the point being that digital business is allowing companies to traverse industries and now you're seeing it in really interesting competitive lashbacks. >> So Capital One was onstage, I say something that over the past couple of years been controversial, no one believes me, but I believe this is what needs to happen. Capital One claimed that it's a technology company, they're not a bank. Well I want to bank with a bank, that' a whole 'nother conversation. But technology is just a tool to get your job done, and just like we had bookkeepers that knew Excel and then eventually Excel just became a part of your toolkit. AI, I talked to Chuck Hollis of Oracle about this on the podcast the other day. AI is just going to be a business toolkit that a business user uses. To the question, business users will become smarter at using technology. The cloud providers that enables the business user to have the least amount of friction to use that technology, to solve business challenges will win. The question is, is that Google or Andy Jassy, who has done it with Amazon, or some other cloud provider that's eating their own dog food. >> Okay guys, let's wrap this up. Let's go around the table, one word, two words, how do you wrap up VMware's position vis a vis as they go forward? >> VMware's on fire, I think the data center's on fire, the ecosystem is reforming around the cloud. And there's a lot of momentum right now, I mean I'm wondering, okay, what's going to happen to derail this, but right now the fundamentals look very good. >> Relevant, John. >> Yeah. >> Cool and relevant again. It's right, you know, cool, we can all argue, you know, look, I like what I heard with Amazon, it was better than I was expecting coming in. You know, getting in there, they talked about serverless, they talked about edge computing, something I actually had a couple really good conversations ticking to, partners doing IoT, and customers looking at that. If they can be relevant, not just in the data center, but in the cloud, and even at the edge, VMware's going to have a good life going forward. >> Yeah, and I'll wrap it up, you stole my word relevant, so I'll say, I'll a little bit further than relevant, VMware is still the leader in enterprise infrastructure software. They're not letting that lead go. >> But just on that, the last thing, they're an infrastructure software company. I think they showed how they can be more than that in the future. >> And my take is, smart strategy playing out, now people are starting to realize the long game that Pat's been playing. It's showing up in the financial results, and there's clarity, and you can see the game playing out, you're starting to see there where they're going to position, so good job, guys, that's a wrap. Want to thank our sponsors. Without sponsors theCUBE would not be able to come for the three days of wall-to-wall coverage provided to the community. We get great support from the folks on Twitter, we get support from the folks who watch the videos, want to thank you for watching, and also the sponsors, VMware, Hewlett Packard Enterprises, Dell EMC, IBM, OVH, CenturyLink, Datrium, Densify, Druva, Hitachi, INFINIDAT, Kamarino, NetApp, Nutanix, Red Hat, Rackspace, Rubrik, Skytap, Veeam and Zadara Storage. Thanks to all the 20 sponsors that we can go out and bring our best stuff here. Really appreciate your support. Thanks for watching theCUBE. This is a wrap from VMworld, thanks guys, thanks everybody here, and that's a wrap for VMworld 2017, thanks for watching.

>> Narrator: Live, from San Francisco, it's the Cube, covering Informatica World 2017. Brought to you by Informatica. (techno music) >> Hey, welcome back, everyone. Live here in San Francisco, this is the Cube's exclusive coverage of Informatica World 2017, our third year covering Informatica, and more to come. I'm John Furrier with Silicon Angle, the Cube. My co-host, Peter Burris, Head of Research for Silicon Angle Media, as well as General Manager of Wikibon.com, check out the great research at Wikibon. Some great stuff there on IOT, cloud ping data, great stuff. Of course, go to SiliconAngle.com for all the coverage YouTube.com/SiliconAngle for all the Cube videos. Our next guest is Bruce Chizen, board member of a lot of private companies, also Special Advisor at Informatica. You're on the board of Informatica, no? >> Executive Chair. >> John: Executive Chair of Informatica. Not only as Special Advisor, Executive Chair. Welcome back, good to see you. >> Great to be here. >> You were on last year, great to have you back. What a popular video. Jerry Held was on yesterday. Let's get some Board insights, so first question, when are you going public? (laughing) >> Good one. >> John: Warmed you up, and then, no. I mean the performance is doing well. Give us a quick update. >> Company's doing well. Q4 was a good quarter, Q1 was a good quarter. I think we will be positioned to do something late 2018, early 2019. A lot depends on how the company continues to do. A lot depends on the market. The private equity investors are in no hurry. >> John: Yeah. >> But it's always nice to have that option. >> So it's one of the things we, yeah, great option. Doing well. We heard that also from some of the management. We got O'Neil coming on, we'll press him on some of the performance side, but always had good products out, we talked about it last year. But the industry's going through a massive transformation. You've seen many waves over the years. The waves are hitting. What's your perspective right now? I mean, it's a pretty big wave. You got to get the surfboard out there, there's a set coming in. What's the big wave right now? >> So, data is driving every transformation within every organization. Any company that is not using and taking advantage of data will be left behind. You look at how companies like Amazon and Google and now a lot of our customers like Schwab and Tesla and others, the way they're using data, that will allow them to continue to either be successful in the case of a Schwab, or be a disruptor, like somebody like Tesla. Fortunately for us at Informatica, we are helping to drive that digital transformation. >> One of the things that I always observe, younger than you are, I've only seen a few waves in my day, but in the waves that were the most impactful in terms of creating wealth, and opportunity, and innovation, has had a cool and relevant factor. Meaning, if you go back to the PC days, it was cool and relevant. If you go back to mini computer, cool and relevant. And it goes on and on and on. And certainly internet, cool and relevant. But now, the, you mention Tesla. I'm testing driving one on Friday. My kids are like "Don't buy the Audi, buy the Tesla." This is my kids. So it's a cooler, it's a spaceship, it's cooler than the other cars. >> Bruce: Or an iPhone on wheels. >> Peter: (laughs) Exactly. A computer on wheels. >> So cool and relevant, talk about what is the cool and relevant thing right now. You talk about user experience, that's one. Data's changing it. So how is data being the cool and relevant trend? Point to some things that... >> If you look at what's happening from the chip on up, everything, everything will be intelligent. And I hate to use the term "internet of things," but the reality is everything will have intelligence. And that intelligent information will be able to be taken advantage of because of the scale of the cloud. Which means that any company will be able to take information, data, analyze it on the cloud, and then use it to do something with. And it's happening now. Fortunately, Informatica sits right in the middle of that, because they're the ones who could rationalize that data on behalf of their customers. 'Cause there's going to be a lot of it and somebody needs to govern it, secure it, homogenize it. >> John: You consider them an enabling platform? >> Absolutely, absolutely. I was joking, we just went through a rebranding exercise. And it's kind of cute, new logo, and it's kind of bold and sleek and it shows we'll have a leader, but it's a logo. But there's really around the messaging, we are finally getting across that we are the ones unleashing the power of data. That's what Informatica does. We'd just never really told anybody about it. We're very product focused, not really helping customers understand how uniquely positioned the company was. >> And it's also, you guys have done some things. Let's just go back and look at going private. Brought a new management team, have product chops again, we've talked about that in previous years. Last year in particular. So, okay, you have the wind at your back. Now you got Sally as a CMO, now you got to start being a humble braggart about the cool stuff you're doing. So which is marketing, basically. >> That's correct. >> John: But now, it's digital. >> Yeah. >> So, what's the Board conversation like, you say "Go, go build the brand!" >> So first of all, being private is great. (laughing) Because we get to do things you couldn't do as a public company. We're, a lot of our customers what to buy the products and solutions via subscription, that has huge impact to the P&L, especially in the short term. Cash flow's fine. So the PE guys are going okay, it's great, because we'll come out of this as a better company, and our customers like it because that's the way they want to buy products. So, that helps a lot. The conversation at the Board level has been, "Wow, we're number one in every category in which "we participate in. "Everything from big data to cloud integration "to traditional on-premise, to real-time streaming, "and, and, and data security." >> You're only one of three vendors in the Google general availabilities banner which went out yesterday. We covered that on Silicon Angle. >> We're number one there, we had AWS speak at our conference, we had Azure speak at our conference. All of the cloud guys love Informatica because we are the ones who are uniquely positioned to deal with all this data on behalf of their customers. As a private company, we're able to take advantage of that, spend some extra money on marketing. You know a lot of our customers know about us, but a lot more should know about us. So, part of coming out, having a new logo, having a new digital campaign, changing the website, that costs money. But as a private company, we get to do that. Because the fruits of those efforts will end up occurring a couple of years down the road, which is fine. >> So let me see if I can weave those two thoughts together in what I thought was an interesting way. Given that increasingly a lot of data's going to be in the cloud, and that's where the longer analysis is going to be required, that means a lot of the tools are going to have to be in the cloud. Amazon Marketplace is going to be a place where a lot of tools are going to be chosen. People are going to go into the Amazon Marketplace and see a lot of different options, including some that are free. They may not work as well, but they're free. You guys, what happens with marketing, and what's happening with that kind of a trend, is you need to buy, as customers, to choose tools that are actually going to work to serve or to solve the problem, to do the work that you need them to perform. And so what Sally Jenkins, the CMO, has done, with this new branding, is introduce the process of how do you buy us more customers to choose the right tool to do the right job? Does that make sense to you? >> It makes absolute sense, free is good. But be careful what you ask for. Sometimes you get what you pay for. You're talking about enterprise data. You want it to be governed, you want it to be secure. You want it to be accurate. >> John: Now there's laws coming out where you have to do it. >> You look at GTB... >> Peter: GDBPR. >> GDBPR in Europe, the privacy issues. You look at what's happening with Facebook, or what was reported today with France and how they're not happy with Facebook's privacy behaviors. It's an issue. It's an issue for anybody who does business anywhere, especially if you're a global company and you do business in Europe. You have to worry about corporate governance. Data security, data governance, data security. That's Informatica. The other thing is, while there will be some customers who will say "I'm going to AWS," there will be more customers who will either say "I have some legacy "systems that I'm going to leave on-premise, "and new projects will be in the cloud." Or they're going to say "I'm moving everything to "the cloud, but I don't want to be held hostage "by one cloud provider." And they're going to go with Amazon and Azure and Google and maybe Oracle, and, and, and. And again, because Informatica is Swiss, we're able to provide them with a solution that allows them to accomplish their data needs. >> Well, congratulations on the performance, I want to get that out of the way. But I want to ask a specific question on the historical, holistic picture of Informatica. Going back, what were the key bets that you guys made? 'Cause you guys sit around, and you got the private equity now coming to the table, they have expectations, but at the end of the day you've got to build a business. What were the key bets that is yielding the fruit that we're seeing? >> The number one bet was that the company had great products and a great R&D organization. We believed that, and fortunately, we got it right. Because if you don't have great products and passionate R&D organizations around the world, you can't make up for that. It doesn't make a difference how much you spend on marketing. At least not in the business that we're in. So that was number one bet, and that proved to play out well. The second thing was, this was a company that had done so well for so long that they never needed to change their business processes to behave like a billion, two billion, three billion, four billion dollar company. Many of their business processes were like that of a 200 million dollar company. And that's easier to fix. So things around back end, IT, legal, finance, go-to-market, marketing, sales. >> John: Less of a risk from an investment standpoint. >> That's correct. So that's what we believed, we were right And where we've been spending most of our energy and effort is helping the company, through the new management team, improve their business processes and their go-to-market. >> So we had a critical analysis yesterday during our wrap up session, and one of the comments I made, I want to get your reaction to this, was although impressive, your number one and all these Gartner Magic Quadrant categories, but that's an old scoreboard. If we're really living in digital transformation, those shouldn't really be a tell sign for what the performance of the new KBIs or the new metrics are. And so we were pontificating and analyzing what that would be, still unknown, we're going to see it. But Peter had a good point, he said "At the end "of the day, customer wins." >> Yeah, that was my reaction. It's like at the end of the day, all that matters do the customers.... >> What's the scoreboard look for customer wins? I know you were at the executive summit they had yesterday at the Intercontinental right around the corner. I had a chance to meet some of them at that dinner, some conversation. But I want to get your perspective. What is the vibe of the customers, what are those customer wins, and how does that translate into future growth for Informatica? >> Any customer who is looking at data, data management, strategically, is going with Informatica. >> Mmm hmm. >> There are a number of competitors that we have who try to compete with Informatica at the product level, and they end up doing okay through pricing, through better sales tactics, but when we have the opportunity to speak to the Chief Data Officer, the CIO, the CEO, they go with Informatica. It's the reason why Tesla went with Informatica on their project where they're trying to tie together the auto business with the solar business. Because if they get to know both sets of customers and are able to sync that up, one plus one will be greater than two for them, and that's why they did that deal. Or it's why Amazon has chosen our MDM solution for their sales operations. So you look at leading companies who are able to look at the enterprise level, at the strategic level, they are going with Informatica. That's why we know we're winning. >> So Bruce, give us three sentences, what is strategic data management? >> Strategic data management is being able to take reams and reams of data from all different platforms, traditional legacy, big data, real-time solutions, and data from the cloud and be able to look at it intelligently. Use artificial intelligence and machine learning to be able to analyze that data in a more intelligent way, and then act on it. >> So two questions on that point, I was going to ask about the AI washing going on in the industry. Every event now is like, "Oh my god, AI, we've got AI," but that's not really AI. What is AI, we call it augmented intelligence because you're really augmenting with the data, but even Google IO's got a little neural net throwback to the 80s, but what's your thoughts on how customers should look through the lens of b.s. to say, "Wow, that's the real AI, or the real "augmented intelligence." >> Does it do anything? That's ultimately the question that a Chief Data Officer or CIO or CEO...is something changing because of the artificial intelligence being applied? In the case of Informatica, we announced an AI platform called Clair, "clairvoyant," so artificial intelligence. What is Clair? It allows you to develop solutions like our enterprise information catalog, where an organization has thousands and thousands of databases, it's able to look at the metadata within those databases and then over time keep disclosing more and more data appropriate to the information that you're looking for. So then, if I'm an analyst or a businessperson, a marketing person, a sales person, I can take action on the right set of data. That's true artificial intelligence. >> Bruce, I want to get to one final point as we are winding down here. Again, you've seen many waves. But I want to talk about the companies that are trying to get through the transition of this transformation, Informatica certainly cleared the runway, they've got some things to work on, certainly brand-building. I see that as their air cover in many rising tide will float a lot of boats in the ecosystem. But there are companies where they have been in the infrastructure business and the cloud is one big infrastructure, selling boxes and whatnot. Other companies have traditional software models, download, whatever you want to call it, on-prem licenses, not subscriptions. They're working hard. Your advice to them if you are on their Board, or as a friend, what do you say to them, what do they got to do to get through this? And how should customers look at who's winning and who's losing, in terms of progress? >> The world of enterprise computing is moving to the cloud. Legacy systems will remain for a while. They need to figure out how to take their legacy solutions and make them relevant to the world of cloud computing. And if they can't do that, they should sell their company or get out of business. (laughing) >> And certainly data is the oil, it's the gold, it's the lifeblood of an organization. >> Of any organization. Even at Informatica, internally, we're using our own intelligent data platform to do our own marketing. Sally Jenkins is working closely with our CIO Graeme Thompson on working on solutions where we could help better understand what our customers want and need, so we can provide them with the right solution, leveraging our intelligent data leg. >> Bruce, thanks for coming on the Cube. Really appreciate your insight. Again, you've seen a lot of waves, you've been in the industry a long time, you have great Board presence, as well as other companies. Thanks for sharing the insight, and the data here on the Cube. A lot of insights and analytics being extracted here and sharing it with you. Certainly we're not legacy, we don't need to sell our business, we're doing great. If you haven't, make the transition. Good advice, thanks so much. >> Bruce: Great to be here. >> Bruce Chizen inside the Cube here. I'm John Furrier with Peter Burris. Stay with us for more coverage after this short break. (techno music)

>> Narrator: It's The Cube covering Sapphire Now 2017. Brought to you by S.A.P. Cloud Platform and Honna Interprise Cloud. >> Hello there, and welcome to The Cube conversation here in Palo Alto Studios, I'm John Furrier with The Cube, and we have a special guest here. Susie Wee, who's the vice president and CTO of DevNet at Cisco Systems for a Cube conversation around what's happening in cloud, and really some of the most important trends that are generating out of a new event that she's starting called DevNet Creative, which The Cube will be there. Susie, welcome to this Cube conversation. >> Hi, John. Thanks, it's great to be here. >> So, you were a pioneer within Cisco. You know, superstar technologist, CTO. You helped really put the Cisco DevNet Developer program together. Which as been a huge success. Congratulations. >> Thank you. >> And that's been, you know, Cisco has a big community of geeks. They're super smart. They like to surf the web and learn, and develop new stuff on Cisco, but there's also a whole nother world, and you created an event called DevNet Create as a new initiative. A new pioneering effort. >> Absolutely. >> Why a new event? What's the big news here? >> It's really interesting. I think that what's going on is in the world of, kind of, the infrastructure, right? So the infrastructure has our networking, our compute, our storage, and all of that is changing in that it's becoming programmable, and so once it's programmable, you're like, "What?" My infrastructure has APIs. Once it has APIs, you can do things like DevOps, right? You can start to do things like really have good flexibility with how you deploy your applications, you can get much more rapid deployment of apps, and you can get, just, fundamentally, different, and improved applications. So, the big thing that's going on is that there's this huge industry transformation in front of us, and the transformation is in how applications meet infrastructure, and this has happened as applications go to the cloud, then how applications meet the cloud, apps are changing, right? Then as the infrastructure becomes programmable, there's APIs into it, so there's this really kind of fresh ground that's ahead of us, and we can make the most of this, and that's what DevNet Create is all about. >> You know, people always ask me, this is our eighth year doing The Cube, "John, you and Dave do such a good job with The Cube." "You always pick the events that are going to be good." (laughter) We did some when we were first on, I do parole, I mean, with Cloud Air, and nobody had heard of Cloud Air. We can sniff the trends out, and to me, I think you're onto something really big here, and this is why I'm excited to bring The Cube to your event. I know it's small, it's inaugural, and it's very community-oriented, but I think you guys are on fault line of a massive shift, and I think you're on the right side of this, and I think the app dynamics acquisition that Cisco did points to some of the things that going to give Cisco, I think, a big lift, and that is, by looking at the plumbing as being automated, certainly relevant, that's not going away, but as you move up the stack, there's going to be the need for rapid, rapid application deployment. >> Susie Wee: Absolutely. >> Conceive, build, ship in minutes. It could be automated with bots and AI and whatnot, so this is the trend. Talk about that dynamic, 'cause that requires a fundamental rethinking and reimagining of the Cloud, security, how packets move. >> Susie Wee: Absolutely. >> Do you agree with that, and obviously, you're running the event, so you probably have some bias there, but more importantly, this big trend. >> Yeah, absolutely. So, kind of the applications themselves, we take apps for granted these days, and we've had applications forever, right? But the applications are how people interact with the system, with the Cloud, with all the surfaces that they use everyday, so we know that everyone's lives have been transformed with apps, and then we also know that the Cloud has been huge. You know, work loads are moving with the Cloud. The Cloud has instant deployment, global resources, again, big stuff there as well, but that's going to shift again, right? So what happens is now that the Cloud is as awesome as it is, now that applications are great as they are, we're going to go to this next generation where the applications get even better, the Cloud gets even better, the way they meet, and therefore, the surfaces that people use get better. Let's have some examples of like, what could be better? Well, now that you have things like app dynamics, you can start to get information from your applications in the infrastructure that give you business insights, so let's say that you have your application running, and then you know how many times different APIs have been called. You know what parts of your systems, or your applications, are called the most. You know who's using them. You know how often they're being used, by whom, and so on. What order are they being used? All of this can start to give you business insight, so then you say, oh, the infrastructure's not just about delivering, compute, network, and storage, it's also about giving the insights into how people are using my stuff, so I can get business insights all of a sudden, and then it's a whole new world. >> Talk about how you got here, and your journey with Cisco being creating the DevNet and now DevNet Create, 'cause I think there's some trends in the industry, and we're going to be covering Sapphire, which is SAP's big show coming up in Orlando, and Cisco has some announcements, I know, I was brief under NDA on that so I really can't talk about it right now, but I do know for a fact it's going to be some significant innovations that's Cisco's bringing to the table, and they're an app provider. Now, they're older version, they're the big ERP, and the big software and framewares, and they announced Cloud Native with iOS development. This notion of, like a new breed of developers is not a mutually exclusive argument against IT, it's just the continuation. There's a dynamic going on between software developments and apps, and not only just on the business model side, but actually, technically. >> Yeah, absolutely. There's a few different things. So, first of all, an app developers can, so we have something called Meraki. Meraki is our wireless access points, it was a big acquisition we did a few years ago, and you can think of, you know, wireless access points as giving you connectivity, wireless connectivity, but now imagine that it also, you have APIs into it and it tells you how many mobile devices are connected. Where are they connected from? And where are the mobile devices located? If someone comes into your store, how many people have been there before? And how many people is it their first time there? So, this is all stuff that you can get from your wireless access points and you can start to do really interesting stuff. I think any app developer would love to have that information of what can I get? Who's in my store, or who's in my venue? And the infrastructure gives you that. >> And you guys run most, if not all the networks in the world. An IOT device and your other things that's connected to a network, wireless or wired. >> Yeah. >> And packets are moving around, so you have that data. >> We have that data, yes. So, yes, exactly. Cisco infrastructure is everywhere. >> But it's been hard to expose that over the years because Cisco's always had this notion that we play at a certain part of the stack and now it's almost like finally, after decades of conversations, I know from folks I talked to at Cisco, let's move up the stack. There's always been this push that does Cisco move up the stack and how? >> Yes, and basically the way that the way and the reason that Cisco can move up the stack now is because the infrastructure is programmable, so now, our kit, the network, is programmable. Now there's analytics that are being built into the network as things are running around, so like having a programmable network, having analytics, where you can either gather information together on how applications and things are being used, or a key, and then how do we move up the stack is when we work with the ecosystem. We work with the community, is that we have a developer program like DevNet, which is why we founded it, is we're going to enable those app developers to come to the world of the enterprise, so right now, when you have an enterprise, you know, who can write an awesome IOT app for a building, or for a casino, or for a mall, or for a hotel, it's whoever that hotel works with. Whatever system integrator they have, and that's all amazing, 'cause, you know, your building's instrumented, >> Yeah, so you don't have to >> Susie Wee: You know where people are. >> It's a horizontal market of developers versus a specific Cisco community, which you have to nurture in and of itself. >> Exactly. >> In the course of business, guys who know how to handle the packets and the networking gear, and know someone who's, hey, I know Cisco's a network provider, a network supplier, I just don't want to have to go get a training certification to get some data; just give it to me. >> That's right, and so what we can do is say, hey, here's the APIs, go to developer.cisco.com. Everything's there. Everything's free. Here's learning labs on how to use the different APIs. Here's use cases. We actually have kit in the clouds so we have a sandbox that lets people use stuff. If you want to write an app for a contact center, 'cause we sell contacts in our stuff, we have a contact center that you can write and deploy your app on. You don't have to buy one to test it, right? So it's really interesting when these apps hit these places, which is that, you know, you need a contact center, well, we'll have one for you. >> Here's the hard question. I want to put you on the spot and bring the heat, if you will. You guys have been great in your own ecosystem. Dominant for Cisco as a company. As you move into this new ecosystem, because ecosystems are now business-model parts of public companies. Cloud Air just went public. Ortenwer's went public. Viewelsoft. A new class of new kind of open-source companies are going public. You guys are not necessarily an open-source company. You have open-source initiatives. You have to now embrace a new kind of ecosystem. >> Absolutely. >> Where's the progress on this? How early is it? 'Cause I think that's what DevNet created to me, and Cisco is now going into a new market and being proactive. >> Absolutely >> The question is are you ready? Do you have the chops? Where are you in the progress of that? (laughter) >> We're ready. Now, it's going to take work to work with the community to get there, but let me just go back 'cause when we first started DeveNet three years ago, we said, hey, are those networkers and those infrastructure guys, are they really ready for programmability and software? We didn't know, and then we had out first DevNet event, and it was packed. We're like, oh my gosh, these guys are so ready, and we didn't know that at the time, so we've made good progress there, but now that we're sitting there to work with the community, I think that I'm hoping that they're going to be embracing so we're certainly going to be open. We've actually opened up, kind of, the thinking within Cisco. We've done a lot of cultural change within Cisco because people have seen the success of DevNet and of the developers outside in the world who are actually jumping in and ready to embrace programmability. >> So, it's the old data. It started home. What you did. >> It started home. >> You did with your own core. >> And then used that to then build out. >> And you guys have apps, we know, again, we go to a lot of events. I've seen Cisco around in a lot of some of the open-stores events. I was at the Nix Foundation. You guys had some presence, but it seemed like a toe in the water. How are you guys going to go big in this? >> That's what changed, is actually Cisco has had some little developer efforts and a lot of heroics done by people within Cisco. Like, hey, I have this great product, I want to run a hackathon, right? So, we've had all of these heroic attempts, but until DevNet came along, we didn't have one centrally funded program with a mandate from the CEO to go and get that programmability and develop our ecosystem out there. That's what we had now for the last three years with DevNet, so now is we go to the next layer. You're right, we do have the people who are out working with the Cloud Native, working with OpenStock, working with OpenDaylight, working in the SDN, the Lennox foundation, and what we're doing is now bringing that to the next level. Again, adding the DevNet power, now that we have kind of established our base to really embrace this, so we hope that we're going to provide a lot more, kind of, foundation so that we can go big in these cases. >> How big is the cultural change within Cisco, just give some color without giving away too many trade secrets, but I know Cisco have, and a lot of my friends worked there I've known for years, from the beginning, I've been intimate with the company's culture, and they've been a case study of dominance, just the way their competitiveness has been, the products have been great. They run the networks, but now they have to move into this open source and the community world. Talk about some of the cultural changes. Any conversations? The CEO, when you talk to him, what's the conversation like there? >> I just met with our CEO, Chuck Robins, a couple weeks ago, updated him on our progress. He actually, he an John Chambers, together, helped found DevNet, so they understand the need for it, and they helped break down the barriers and create the funding and the organization to do it, and we had to do some re-orgs to get it going originally. >> It's not just lip service, they're putting their muscle behind it. >> They're putting their effort behind it and they're dedicated to it, and they understand it. Chuck is fully behind it. He sees the importance of programmability. He actually understands the applications meet infrastructure and the transformation that can happen there, so he is super supportive all the way. He sent me a text this morning and said, "Yeah, when is DevNet Create again?" >> Great. >> So he's on top of it. He knows what we're doing. >> We'll have him on The Cube for sure. >> Absolutely. >> So applications meets infrastructure is the DevOps ethos, and that really highlights your theme. >> It does. Now, some of the other cultural change that has happened is, for example, we have something called systems engineers in our sales force. So what happens is, in our sales force, we have technical folks. We have 6,000 sales engineers around the world. Systems engineers, and they understand the technical side. They're all taking DevNet training. They're taking DevNet learning labs. They're learning to code. They're learning to use our APIs and now, the other thing is that they're now running DevNet events around the world. These guys are not only getting trained, but they are running their own developer events, and so they've picked it all up. This is a transformation that, you know, we've partnered with them on, and that's really changed what they're doing and they're realizing that, hey, there's a conversation, like, we can finally have the assets to help out app developers, and the app developers, they do need help. People have been rating mobile apps for years. Not that many of them are making money, right? The question is how do you do good to those app developers? How do you bring those app developers into the enterprise? How do you take it and make sure that when you have the newest things, like... >> I've always said: feed it data. >> Feed it data. >> Data is a great life blood of applications. >> Absolutely, and so then the applications have data. Then you start to analyze it, you get the intelligence from it right there, and then all new insight. >> The automation around provisioning all that network plumbing is really, really hard and nuanced. If you can automate that away, developers will just have parade to your door. >> Absolutely. >> Alright, so, personal question. You've been very successful in building DevNet. Building developer programs is everyone's holy grail right now. There are people in companies: "We got to build a developer program." "Throw some money at it." They might have some lip service from the CEO or full commitment. What is the key to success. To get the companies and to actually conceive, to build, and deploy a successful developer program for a company? >> Yeah, that's a good question. I have to say that building the developer program is not as easy as you would think. I would think it should be easy, like get out there, go find some web service that's running free developer community stuff >> Someone creates a free code. >> Give 'em code, and that's it? But it's actually not that at all. There is actually a few things that have been key to what we've done. One of them, and actually, I spoke about this at the Evan's developer relations conference a few weeks back, but one of the keys there is just be entrepreneurial. You actually have to be an entrepreneur even if you're in a big company, then you especially have to be entrepreneurial. >> John: You got to hustle harder. >> And what I mean is you have to hustle hard and, with few resources, you have to show quick wins fast, and you have to make bets, right? What are the kind of things we do? Well, when we first started, we actually didn't have an organization. It was me. It was a couple rebels from different parts of the org who are like, we need this, and we were making proposals. >> Skull and crossbones kind of thing going on, yeah, big time. >> And we pretended that, hey, just pretend that we have a full-blown developer program. What would you do? What we did was, we went out there, we went made developer.cisco.com, we made one site, we brought all of the APIs into one place so that developers could access it, and it was just going through and kind of building that site, which is really hard in a big company like Cisco with APIs all over the place, and we just silently launched it, and then people started discovering it. Like, oh, all of Cisco's stuff is here. Holy Cow. That was one thing. >> Go humble early. Learned from Lennox himself. >> And we actually got kind of blasted on the Twittershpere because actually on our developer page, we had one section that was actually going to just product information and not having APIs in it, and so this guy was like, that's all product stuff. That's not about APIs, so we got blasted. We were like holy crap, he's right. We went, we changed it. Got rid of all that. >> That's agile. >> And fixed it and then he became our biggest fan, right? We changed and we learned from feedback from the community. >> You applied the entrepreneurial hustle. Hustle hard and make bets. >> Susie: Make bets. >> What's your big bet that your hustling now for, and I mean hustle in a good way, DevNet Create. What's your bet? >> Our first bet back then, big bet, was the DevNet's own at Cisco Live, was let's have a developer conference at Cisco Live. We have no idea if people are going to be interested, but let's just do it. So, we got second floor of Mosconi's. >> You're going big or going home. >> Yeah, exactly, so we like boom! Kind of got the same place they have Google IO and Dreamforce. We got the space, kind of created it, didn't know if anybody would come. It was jampacked. We're like, oh my God. John Chambers came by. He told his whole staff, like, you guys have to see what's happening. The DevNet zone's now the busiest part of Cisco Live. That was our big bet then, and fortunately it paid off, and I think that's what made us part of the fabric that let us continue on, but now our big bet is DevNet Create. It's about applications hitting the infrastructure and really ensuring that the infrastructure is giving benefit to app developers. >> John: Real benefit. >> Real benefit. It's not just for the sake of business, it's actually because, to me, there's a real inflection going on in the industry. Apps can just ride on top, and then just do whatever the infrastructure can provide for them, and that'll get us to one place, but once you really think about it, then you say, okay, where does the data for the apps need to sit? Oh my gosh, there's data sovereignty issues, so it can't just sit anywhere. How do we scale out? Like, when we scale out, and you could just say, oh yeah, just go buy it and Amazon, Google, someone else will take care of it for me. Well, some of it will, and you should absolutely use... We're using all of those >> The policy stuff. >> As well, but there's policy, there's, you know, so when you're really working to scale out and understand what's critical for your business, there's more that can be had, and then now you can go to the next level of where apps can get value added business insights from the network like what we were talking about before, and then, a really big thing is just when I kind of think forward to the world of IOT, and you say again, this building is now IOT enabled. This building has APIs. It's the infrastructure, and app developers would love to get access to that. >> Peter Barris and I were talking at The Cube about a new standard we want to see. All data should be presented in less than 100 milliseconds from any database. >> Susie: Nice, nice. >> That's a moon shot, but let's think about that. That's what we want. Okay, so final question. Congratulations on all your success, and I do believe that a trend is there, the question is when will it get there. Upcoming for DevNet Create, what do you hope to bring to the community? What do you want the community to look for and expect? And what will they see? >> Absolutely. What we want is, we hope that DevNet Create is just a catalyst for this to happen. For this transformation that's happening, and we want it to help drive things with the community in a faster way than if we just let it go itself. There's basically going to be two tracks at DevNet Create. One is on Cloud and DevOps, and the other is on IOT and apps. With Cloud, there's all these questions of how are we going to take monolithic legacy apps and turn them into micro surfaces? We have the world of containers. We have the world of container orchestration and everything there. That's all really hot stuff, but the way that we move this together, bring it into full production and get all of the apps really embracing that is key. What we're hoping will happen at DevNet Create is that the world of Cloud developers, the world of app developers, IOT developers will come together with those that are working in DevOps, those in the infrastructure to really understand what are the benefits that can happen across these layers? I'm not saying that every app developer needs to become an infrastructure developer, right? I'm not saying that every developer must be an operator, but there's benefits that can happen in the right way. Really, what we're hoping is that with DevNet Create, we can drive that conversation at the event itself and then continue with the ongoing community. >> And who are you targeting specifically to the event? Non-Cisco developers or Cisco developers with a plus, with a twist, or? >> Non-Cisco developers as well as some Cisco developers as well, but it's really about the industry. Where as when you go to a traditional DevNet event, you're going to be hearing all about Cisco APIs and Cisco products and how they play together in these solutions, but at DevNet Create, 90% or more of the talks are non-Cisco. We had a call for papers. I was really nervous when we had the call for papers and I was super relieved because we had great papers come in. Actually, the only problem is that we didn't have enough slots for the great papers. We even had to turn around some really good ones. Turn away some really good ones. We have a really strong agenda, and we actually said no to more Cisco talks because we wanted it from the ecosystem. We have people from Google, from Amazon, from Howdy. There's just lots of... >> And so will this be a Cisco event going forward? Or an industry event? Because there's a trend in the event world where people are going in for the big DreamForce and the big one show, big tent, zillion people, and then a series of industry shows around open-source communities with governance. Are you guys going to make this a Cisco managed show? Or thinking about opening it up to the community to manage? What's your thoughts on the vision of that? >> We're hoping to catalyze it. We will continue to have our other Cisco DevNet events that are really about the Cisco APIs themselves and really training and bringing along that core community, and we invite all the developers to attend that as well, but we really view DevNet Create to really be an event for the community. We'd be open to doing this with cosponsors and hosting it with others. >> So you're open. >> We're open. We're actually doing this with Lennox Foundation as well, so we have them involved. Many of them are on our advisory board. We are very open. We're actually working with SiliconANGLE and The Cube. We want to do it in the most open way as possible. >> As I said, we like to sniff out all the hot events. This is one inaugural event. I think it's really, really important because it really shows Cisco's commitment to open source in a way that's been toe in the waters in the past, like you said, little rebels in the organization doing their thing trying to get the word inside Cisco, but now with the cultural shift, I think you guys have it with app dynamics. There's a business path. I see a path there and I think the community only benefits. >> Absolutely, and if the community benefits, and our goal is to actually make our community and our developers successful. That's actually our only goal. For them to be successful in their careers and their business, and that will, in turn, make Cisco successful, but really, it's really about making the community successful. >> I mean if you think about the 5G end-to-end. I mean, end-to-end architectures are winning. We do a whole segment on end-to-end, but to make it end-to-end work that's not just one company, you'd need to have a strong developer community, and I think this is kind of where I see the event's importance is true network transformation and programmability. The ethos of DevOps needs to go to the next level so cars can program themselves. I mean, everything. 5G's coming too, so a lot of new stuff happening. >> Absolutely. I don't think any major industry transformation happened with one company alone. It really takes a community, right? Be it a community of product makers, a community of solutions providers, surface providers, and consumers themselves. This is really about the community. >> Susie, congratulations on all your success, and we're looking forward to seeing DevNet Create's inaugural opening in May. Appreciate it, and great to talk to you about some of the mega trends and your perspective on that. >> And thank you for helping to drive this vision and agenda. I think that we'll be able to do this together. >> Susie, with CTO at Cisco Systems, DevNet creator and pioneer with her team of rebels, now a full on group. Really talking about the app meets infrastructure total transformation enabling all the AI in terms of vehicles, smart cities, smart home. Thanks for joining us. This is a Cube conversation. I'm John Furrier and thanks for watching. (upbeat music)

>> Narrator: Live from San Jose, California It's the CUBE, covering Big Data Silicon Valley 2017. >> Okay welcome back everyone, live in Silicon Valley, this is the CUBE coverage of Big Data Week, Big Data Silicon Valley, our event, in conjunction with Strata Hadoop. This is the CUBE for two days of wall-to-wall coverage. I'm John Furrier with Analyst from Wikibon, George Gilbert our Big Data as well as Peter Buress, covering all of the angles. And our next guest is Wei Wang, Senior Director of Product Market at Hortonworks, a CUBE alumni, and Oliver Chiu, Senior Product Marketing Manager for Big Data and Microsoft Cloud at Azure. Guys, welcome to the CUBE, good to see you again. >> Yes. >> John: On the CUBE, appreciate you coming on. >> Thank you very much. >> So Microsoft and Hortonworks, you guys are no strangers. We have covered you guys many times on the CUBE, on HD insights. You have some stuff happening, here, and I was just talking about you guys this morning on another segment, like, saying hey, you know the distros need a Cloud strategy. So you have something happening tomorrow. Blog post going out. >> Wei: Yep. >> What's the news with Microsoft? >> So essentially I think that we are truly adopting the CloudFirst. And you know that we have been really acquiring a lot of customers in the Cloud. We have that announced in our earnings that more than a quarter of our customers actually already have a Cloud strategy. I want to give out a few statistics that Gardner told us actually last year. The increase for their end users went up 57% just to talk about Hadoop and Microsoft Azure. So what we're here, is to talk about the next generation. We're putting our latest and greatest innovation in which comes in in the package of the release of HDP2.6, that's our last release. I think our last conversation was on 2.5. So 2.6's great latest and newest innovations to put on CloudFirst, hence our partner, here, Microsoft. We're going to put it on Microsoft HD Insight. >> That's super exciting. And, you know, Oliver, one of the things that we've been really fascinated with and covering for multiple years now is the transformation of Microsoft. Even prior to Satya, who's a CUBE alumni by the way, been on the CUBE, when we were at XL event at Stanford. So, CEO of Microsoft, CUBE alumni, good to have that. But, it's interesting, right? I mean, the Open Compute Project. They donated a boatload of IP into the open-source. Heavily now open-source, Brendan Burns works for Microsoft. He's seeing a huge transformation of Microsoft. You've been working with Hortonworks for a while. Now, it's kind of coming together, and one of the things that's interesting is the trend that's teasing out on the CUBE all the time now is integration. He's seeing this flash point where okay, I've got some Hadoop, I've got a bunch of other stuff in the enterprise equation that's kind of coming together. And you know, things like IOT, and AIs all around the corner as well. How are you guys getting this all packaged together? 'Cause this kind of highlights some of the things that are now integrated in with the tools you have. Give us an update. >> Yeah, absolutely. So for sure, just to kind of respond to the trend, Microsoft kind of made that transformation of being CloudFirst, you know, many years ago. And, it's been great to partner with someone like Hortonworks actually for the last four years of bringing HD Insight as a first party Microsoft Cloud service. And because of that, as we're building other Cloud services around in Azure, we have over 60 services. Think about that. That's 60 PAZ and IAZ services in Microsoft, part of the Azure ecosystem. All of this is starting to get completely integrated with all of our other services. So HD Insight, as an example, is integrated with all of our relational investments, our BI investments, our machine learning investments, our data science investments. And so, it's really just becoming part of the fabric of the Azure Cloud. And so that's a testament to the great partnership that we're having with Hortonworks. >> So the inquiry comment from Gardner, and we're seeing similar things on the Wikibon site on our research team, is that now the legitimacy of say, of seeing how Hadoop fits into the bigger picture, not just Hadoop being the pure-play Big Data platform which many people were doing. But now they're seeing a bigger picture where I can have Hadoop, and I can have some other stuff all integrating. Is that all kind of where this is going from you guys' perspective? >> So yeah, it's again, some statistics we have done tech-validate service that our customers are telling us that 43% of the responders are actually using that integrated approach, the hybrid. They're using the Cloud. They're using our stuff on-premise to actually provide integrated end-to-end processing workload. They are now, I think, people are less think about, I would think, a couple years ago, people probably think a little bit about what kind of data they want to put in the Cloud. What kind of workload they want to actually execute in the Cloud, versus their own premise. I think, what we see is that line starting to blur a little bit. And given the partnership we have with Microsoft, the kind of, the enterprise-ready functionalities, and we talk about that for a long time last time I was here. Talk about security, talk about governance, talk about just layer of, integrated layer to manage the entire thing. Either on-premise, or in the Cloud. I think those are some of the functionalities or some of the innovations that make people a lot more at ease with the idea of putting the entire mission-critical applications in the Cloud, and I want to mention that, especially with our blog going out tomorrow that we will actually announce the Spark 2.1. In which, in Microsoft Azure HD Insight, we're actually going to guarantee 99.9% of SLA. Right, so it's, for that, it's for enterprise customers. In which many of us have together that is truly an insurance outfield, that people are not just only feel at ease about their data, that where they're going to locate, either in the Cloud or within their data center, but also the kind of speed and response and reliability. >> Oliver, I want to queue off something you said which was interesting, that you have 60 services, and that they're increasingly integrated with each other. The idea that Hadoop itself is made up of many projects or services and I think in some amount of time, we won't look at it as a discrete project or product, but something that's integrated with together makes a pipeline, a mix-and-match. I'm curious if you can share with us a vision of how you see Hadoop fitting in with a richer set of Microsoft services, where it might be SQL server, it might be streaming analytics, what that looks like and so the issue of sort of a mix-and-match toolkit fades into a more seamless set of services. >> Yeah, absolutely. And you're right, Hadoop and Wei will definitely reiterate this, is that Hadoop is a platform right, and certainly there is multiple different workloads and projects on that platform that do a lot of different things. You have Spark that can do machine learning and streaming, and SQL-like queries, and you have Hadoop itself that can do badge, interactive, streaming as well. So, you see kind of a lot of workloads being built on open-source Hadoop. And as you bring it to the Cloud, it's really for customers that what we found, and kind of this new Microsoft that is often talked about, is it's all about choice and flexibility for our customers. And so, some customers want to be 100% open-source Apache Hadoop, and if they want that, HD Insight is the right offering, and what we can do is we can surround it with other capabilities that are outside of maybe core Hadoop-type capabilities. Like if you want to media services, all the way down to, you know, other technologies nothing related to, specifically to data and analytics. And so they can combine that with the Hadoop offering, and blend it into a combined offering. And there are some customers that will blend open-source Hadoop with some of our Azure data services as well, because it offers something unique or different. But it's really a choice for our customers. Whatever they're open to, whatever their kind of their strategy for their organization. >> Is there, just to kind of then compare it with other philosophies, do you see that notion that Hadoop now becomes a set of services that might or might not be mixed and matched with native services. Is that different from how Amazon or Google, you know, you perceive them to be integrating Hadoop into their sort of pipelines and services? >> Yeah, it's different because I see Amazon and Google, like, for instance, Google kind of is starting to change their philosophy a little bit with introduction of dataproc. But before, you can see them as an organization that was really focused on bringing some of the internal learnings of Google into the marketplace with their own, you can say proprietary-type services with some of the offerings that they have. But now, they're kind of realizing the value that Hadoop, that Apache Hadoop ecosystem brings. And so, with that comes the introduction of their own manage service. And for AWS, their roots is IAZ, so to speak, is kind of the roots of their Cloud, and they're starting to bring kind of other systems, very similar to, I would say Microsoft Strategy. For us, we are all about making things enterprise-ready. So that's what the unique differentiator and kind of what you alluded to. And so for Microsoft, all of our data services are backed by 99.9% service-level agreement including our relationship with Hortonworks. So that's kind of one, >> Just say that again, one more time. >> 99.9% up-time, and if, >> SLA. >> Oliver: SLA and so that's a guarantee to our customers. So if anything we're, >> John: One more time. >> It's a guarantee to our customers. >> No, this is important. SLA, I mean Google Next didn't talk much about last week their Cloud event. They talked about speed thieves, >> Exactly >> Not a lot of SLAs. This is mandate for the enterprise. They care more about SLA so, not that they don't care about price, but they'd much rather have solid, bulletproof SLAs than the best price. 'Cause the total cost of ownership. >> Right. And that's really the heritage of where Microsoft comes from, is we have been serving our on-premises customers for so long, we understand what they want and need and require for a mission-critical enterprise-ready deployment. And so, our relationship with Hortonworks absolutely 99.9% service-level agreement that we will guarantee to our customers and across all of the Hadoop workloads, whether it would be Hive, whether it would be Spark, whether it'd be Kafka, any of the workloads that we have on HD Insight, is enterprise-ready by virtue, mission-critical, built-in, all that stuff that you would expect. >> Yeah, you guys certainly have a great track record with enterprise. No debate about that, 100%. Um, back to you guys, I want to take a step back and look at some things we've been observing kicking off this week at the Strata Hadoop. This is our eighth year covering, Hadoop world now has evolved into a whole huge thing with Big Data SV and Big Data NYC that we run as well. The bets that were made. And so, I've been intrigued by HD Insights from day one. >> Yep. >> Especially the relationship with Microsoft. Got our attention right away, because of where we saw the dots connecting, which is kind of where we are now. That's a good bet. We're looking at what bets were made and who's making which bets when, and how they're panning out, so I want to just connect the dots. Bets that you guys have made, and the bets that you guys have made that are now paying off, and certainly we've done before camera revolution analytics. Obviously, now, looking real good middle of the fairway as they say. Bets you guys have made that hey, that was a good call. >> Right, and we think that first and foremost, we are sworn to work to support machine learning, we don't call it AI, but we are probably the one that first to always put the Spark, right, in Hadoop. I know that Spark has gained a lot of traction, but I remember that in the early days, we are the ones that as a distro that, going out there not only just verbally talk about support of Spark, but truly put it in our distribution as one of the component. We actually now in the last version, we are actually allows also flexibility. You know Spark, how often they change. Every six weeks they have a new version. And that's kind of in the sense of running into paradox of what actually enterprise-ready is. Within six weeks, they can't even roll out an entire process, right? If they have a workload, they probably can't even get everyone to adopt that yet, within six weeks. So what we did, actually, in the last version, in which we will continue to do, is to essentially support multiple versions of Spark. Right, we essentially to talk about that. And the other bet we have made is about Hive. We truly made that as kind of an initiative behind project Stinger initiative, and also have ties now with LAP. We made the effort to join in with all the other open-source developers to go behind this project that make sure that SQL is becoming truly available for our customers, right. Not only just affordable, but also have the most comprehensive coverage for SQL, and C20-11. But also now having that almost sub-second interactive query. So I think that's the kind of bet we made. >> Yeah, I guess the compatibility of SQL, then you got the performance advantage going on, and this database is where it's in memory or it's SSD, That seems to be the action. >> Wei: Yeah. >> Oliver, you guys made some good bets. So, let's go down the list. >> So let's go down memory lane. I always kind of want to go back to our partnership with Hortonworks. We partnered with Hortonworks really early on, in the early days of Hortonworks' existence. And the reason we made that bet was because of Hortonworks' strategy of being completely open. Right, and so that was a key decision criteria for Microsoft. That we wanted to partner with someone whose entire philosophy was open-source, and committing everything back to the Apache ecosystem. And so that was a very strategic bet that we made. >> John: It was bold at the time, too. >> It was very bold, at the time, yeah. Because Hortonworks at that time was a much smaller company than they are today. But we kind of understood of where the ecosystem was going, and we wanted to partner with people who were committing code back into the ecosystem. So that, I would argue, is definitely one really big bet that was a very successful one and continues to play out even today. Other bets that we've made and like we've talked about prior is our acquisition of Revolution Analytics a couple years ago and that's, >> R just keeps on rolling, it keeps on rolling, rolling, rolling. Awesome. >> Absolutely. Yeah. >> Alright, final words. Why don't we get updated on the data science experiences you guys have. Is there any update there? What's going on, what seems to be, the data science tools are accelerating fast. And, in fact, some are saying that looks like the software tools years and years ago. A lot more work to do. So what's happening with the data science experience? >> Yeah absolutely and just tying back to that original comment around R, Revolution Analytics. That has become Microsoft, our server. And we're offering that, available on-premises and in the Cloud. So on-premises, it's completely integrated with SQL server. So all SQL server customers will now be able to do in-database analytics with R built-in-to-the-core database. And that we see as a major win for us, and a differentiator in the marketplace. But in the Cloud, in conjunction with our partnership with Hortonworks, we're making Microsoft R server, available as part of our integration with Azure HD Insights. So we're kind of just tying back all that integration that we talked about. And so that's built in, and so any customer can take R, and paralyze that across any number of Hadoop and Sparknotes in a managed service within minutes. Clusters will spin up, and they can just run all their data science models and train them across any number of Hadoop and Sparknotes. And so that is, >> John: That takes the heavy lifting away on the cluster management side, so they can focus on their jobs. >> Oliver: Absolutely. >> Awesome. Well guys, thanks for coming on. We really appreciate Wei Wang with Hortonworks, and we have Oliver Chiu from Microsoft. Great to get the update, and tomorrow 10:30, the CloudFirst news hits. CloudFirst, Hortonworks with Azure, great news, congratulations, good Cloud play for Hortonworks. To CUBE, I'm John Furrier with George Gilbert. More coverage live in Silicon Valley after this short break.

>> Announcer: Live from San Jose, California, it's the Cube, covering Big Data Silicon Valley 2017. (upbeat music) >> Hello and welcome to the Cube's special coverage of Big Data SV, Big Data in Silicon Valley in conjunction with Strata + Hadoop. I'm John Furrier with George Gilbert, with Mickey Bonn and Peter Burns as well. We'll be doing interviews all day today and tomorrow, here in Silicon Valley in San Jose. Our next guest is Amit Walia who's the Executive Vice President and Chief Product Officer of Informatica. Kicking of the day one of our coverage. Great to see you. Thanks for joining us on our kick off. >> Good to be here with you, John. >> So obviously big data. this is like the eighth year of us covering, what was once Hadoop World, now it's Strata + Hadoop, Big Data SV. We also do Big Data NYC with the Cube and it's been an interesting transformation over the past eight years. This year has been really really hot with you're starting to see Big Data starting to get a clear line of sight of where it's going. So I want to get your thoughts, Amit, on where the view of the marketplace is from your standpoint. Obviously Informatica's got a big place in the enterprise. And the real trends on how the enterprises are taking analytics and specifically with the cloud. You got the AI looming, all buzzed up on AI. That really seized, people had to get their arms around that. And you see IoT. Intel announced an acquisition, $15 billion for autonomous vehicles, which is essentially data. What's your views? >> Amit: Well I think it's a great question. 10 years have happened since Hadoop started right? I think what has happened as we see is that today what enterprises are trying to encapsulate is what they call digital transformation. What does it mean? I mean think about it, digital transformation for enterprises, it means three unique things. They're transforming their business models to serve their customers better, they're transforming their operational models for their own execution internally, if I'm a manufacturing or an execution-oriented company. The third one is basically making sure that their offerings are also tailored to their customers. And in that context, if you think about it, it's all a data-driven world. Because it's data that helps customers be more insightful, be more actionable, and be a lot more prepared for the future. And that covers the things that you said. Look, that's where Hadoop came into play with big data. But today the three things that organizations are catered around big data is just a lot of data right? How do I bring actionable insights out of it? So in that context, ML and AI are going to play a meaningful role. Because to me as you talk about IoT, IoT is the big game changer of big data becoming big or huge data if I may for a minute. So machine learning, AI, self-service analytics is a part of that, and the third one would be big data and Hadoop going to cloud. That's going to be very fast. >> John: And so the enterprises now are also transforming, so this digital transformation, as you point out, is absolutely real, it's happening. And you start to see a lot more focus on the business models of companies where it's not just analytics as a IT function, it's been talked about for a while, but now it's really more relevant because you're starting to see impactful applications. >> Exactly. >> So with cloud and (chuckles) the new IoT stuff you start to say okay apps matter. And so the data becomes super important. How is that changing the enterprises' readiness in terms of how they're consuming cloud and data and what not? What's you're view on that? Because you guys are deep in this. >> Amit: Yep. >> What's the enterprises' orientation these days? >> So slight nuance to that, as an answer. I think what organizations have realized is that today two things happened that never happened in the last 20 years. Massive fragmentation of the persistence layer, you see Hadoop itself fragmented the whole database layer. And a massive fragmentation of the app layer. So there are 3,000 enterprise size apps today. So just think about it, you're not restricted to one app. So what customers and enterprises are realizing is that, the data layer is where you need to organize yourself. So you need to own the data layer, you cannot just be in the app layer and the database layer because you got to be understanding your data. Because you could be anywhere and everywhere. And the best example I give in the world of cloud is, you don't own anything, you rent it. So what do you own? You own the darn data. So in that context, enterprise readiness as you came to, becomes very important. So understanding and owning your data is the critical secret sauce. And that's where companies are getting disrupted. So the new guys are leveraging data, which by the way the legacy companies had, but they couldn't figure it out. >> What is that? This is important. I want to just double-click on that. Because you mentioned the data layer, what's the playbook? Because that's like the number one question that I get. >> Mm-hmm. >> On Cube interviews or off camera is that okay, I want to have a data strategy. Now that's empty in its statement, but what is the playbook? I mean, is it architecture? Because the data is the strategic advantage. >> Amit: Yes. >> What are they doing? What's the architecture? What are some of the things that enterprises do? Now obviously they care about service level agreements and having potentially multicloud, for instance, as a key thing. But what is that playbook for this data layer? >> That's a very good question, sir. Enterprise readiness has a couple of dimensions. One you said is that there will be hybrid doesn't mean a ground cloud multicloud. I mean you're going to be in multi SAS apps, multi platform apps, multi databases in the cloud. So there is a hybrid world over there. Second is that organizations need to figure out a data platform of their own. Because ultimately what they care for is that, do I have a full view of my customer? Do I have a full view of the products that I'm selling and how they are servicing my customers? That can only happen if you have what I call a meta-data driven data platform. Third one is, boy oh boy, you talked about self-service analytics, you need to know answers today. Having analytics be more self-serving for the business user, not necessarily the IT user, and then leveraging AI to make all these things a lot more powerful. Otherwise, you're going to be spending, what? Hours and hours doing statistical analysis, and you won't be able to get to it given the scale and size of data models. And SLAs will play a big role in the world of cloud. >> Just to follow up on that, so it sounds like you've got the self-service analytics to help essentially explore and visualize. >> Amit: Mm-hmm. >> You've got the data governance and cataloging and lineage to make sure it is high quality and navigable, and then you want to operationalize it once you've built the models. But there's this tension between I want what made the data lake great, which was just dump it all in there so we have this one central place, but all the governance stuff on top of that is sort of just well, we got to organize it anyway. >> Yeah. >> How do you resolve that tension? >> That is a very good question. And that's where enterprises kind of woke up to. So a good example I'll give you, what everybody wanted to make a data lake. I mean if you remember two years ago, 80% of the data lakes fell apart and the reason was for the fact that you just said is that people made the data lake a data swamp if I may. Just dump a lot of data into my loop cluster, and life will be great. But the thing is that, and what customers of large enterprises realized is they became system integrators of their own. I got to bring data, catalog it, prepare it, surface it. So the belief of customers now is that, I need a place to go where basically it can easily bring in all the data, meta-data driven catalog, so I can use AI and ML to surface that data. So it's very easy at the preparation layer for my analysts to go around and play with data and then I can visualize anything. But it's all integrated out of the box, then each layer, each component being self-integrated, then it falls apart very quickly when you want to, to your question, at an enterprise level operationalize it. Large enterprises care about two things. Is it operationalizable? And is it scalable? That's where this could fall apart. And that's what our belief is. And that's where governance happens behind the scenes. You're not doing anything. Security of your data, governance of their data is driven through the catalog. You don't even feel it. It's there. >> I never liked the data lakes term. Dave Vellante knows I've always been kind of against, even from day one, 'cause data's more fluid, I call it a data ocean, but to your point, I want to get on that point because I think data lakes is one dimension, right? >> Yeah. >> And we talked about this at Informatica World, last year I think. And this year it's May 15th. >> Yes. >> I think your event is coming up, but you guys introduced meta-data intelligence. >> Yep. >> So there was, the old model was throw it centralized, do some data governance, data management, fence it out, call, make some queries, get some reports. I'm over simplifying but it was like, it was like a side function. You're getting at now is making that data valuable. >> Amit: Yep. >> So if it's in a lake or it's stored, you never know when the data's going to be relevant, so you have to have it addressable. Could you just talk about where this meta-data intelligence is going? Because you mentioned machine learning and AI. 'Cause this seems to be what everyone is talking about. In real time, how do I make the data really valuable when I need it? And what's the secret sauce that you guys have, specifically, to make that happen? >> So that, to contextualize that question, think about it. So if you. What you don't want to do is keep make everything manual. Our belief is that the intelligence around data has to be at the meta-data level, right? Across the enterprise, which is why, when we invested in the catalog, I used the word, "It's the google of data for the enterprise." No place in an enterprise you can go search for all your data, and given that the fast, rapid-changing sources of data, think about IoT, as you talked about, John. Or think about your customer data, for you and me may come from a new source tomorrow. Do you want the analyst to figure out where the data is coming from? Or the machine learning or AI to contextualize and tell you, you know what, I just discovered a great new source for where John is going to go shop. Do you want to put that as a part of analytics to give him an offer? That's where the organizing principle for data sits. The catalog and all the meta-data, which is where ML and AI will converge to give the analyst self-discovery of data sets, recommendations like in Amazon environment, recommendations like Facebook, find other people or other common data that's like a Facebook or a LinkedIn, that is where everything is going, and that's why we are putting all our efforts on AI. >> So you're saying, you want to abstract the way the complexity of where the data sits? So that the analyst or app can interface with that? >> That's exactly right. Because to me, those are the areas that are changing so rapidly, let that be. You can pick whatever data sets based on what you want, you can pick whichever app you want to use, wherever you want to go, or wherever your business wants to go. You can pick whichever analytical tool you like, but you want to be able to take all of those tools but be able to figure out what data is there, and that should change all the time. >> I'm trying to ask you a lot while you're here. What's going to be the theme this year at Informatica World? How do you take it to the next level? Can you just give us a teaser of what we might expect this year? 'Cause this seems to be the hottest trend. >> This is, so first, at Informatica World this year, we will be unveiling our whole new strategy, branding, and messaging, there's a whole amount of push on that one. But the two things that will be focused a lot on is, one is around that intelligent data platform. Which is basically what I'm talking about. The organizing principle of every enterprise for the next decade, and within that, where AI is going to play a meaningful role for people to spring forward, discover things, self-service, and be able to create sense from this mountains of data that's going to sit around us. But we won't even know what to do. >> All right, so what do you guys have in the product, just want to drill into this dynamic you just mentioned, which is new data sources. With IoT, this is going to completely make it more complex. You never know what data's going to be coming off the cars, the wearables, the smart cities. You have all these new killer use-cases that are going to be transformational. How do you guys handle that, and what's the secret sauce of? 'Cause that seems to be the big challenge, okay, I'm used to dealing with data, its structure, whether it's schemas, now we got unstructured. So okay, now I got new data coming in very fast, I don't even know when or where it's going to come in, so I have to be ready for these new data. What is the Informatica solution there? >> So in terms of taking data from any source, that's never been a challenge for us, because Informatica, one of the bread and butter for us is that we connect and bring data from any potential source on the planet, that's what we do. >> John: And you automate that? >> We automate that process, so any potential new source of data, whether it's IoT, unstructured, semi-structured, log, we connect to that. What I think the key is, where we are heavily invested, once you've brought all that. By the way, you can use Kafka Cues for that, you can use back-streaming, all of that stuff you could do. Question is, how do you make sense out of it? I can get all the data, dump it in a Kafka Cue, and then I take it to do some processing on Spark. But the intelligence is where all the Informatica secret sauce is, right? The meta-data, the transformations, that's what we are invested in, but in terms of connecting anything to everything? That we do for a living, we have done that for one quarter of a century, and we keep doing it. >> I mean, I love having a chat with you, Amit, you're a product guy, and we love product guys, 'cause they can give us a little teaser on the roadmap, but I got to ask you the question, with all this automation, you know, the big buzz out in the world is, "Oh machine learning and AI is replacing jobs." So where is the shift going to be, because you can almost connect the dots and say, "Okay, you're going to put some people out of work, "some developer, some automation, "maybe the systems management layer or wherever." Where are those jobs shifting to? Because you could almost say, "Okay, if you're going to abstract away and automate, "who loses their job?" Who gets shifted and what are those new opportunities, because you could almost say that if you automate in, that should create a new developer class. So one gets replaced, one gets created possibly. Your thoughts on this personnel transformation? >> Yeah, I think, I think what we see is that value creation will change. So the jobs will go to the new value. New areas where value is created. A great example of that is, look at developers today, right. Absolutely, I think they did a terrific job in making sure that the Hadoop ecosystem got legitimized, right? But in my opinion, where enterprise scalability comes, enterprises don't want lots of different things to be integrated and just plumbed together. They want things to work out of the box, which is why, you know, software works for them. But what happens is that they want that development community to go work on what I call value-added areas of the stack. So think about it, in connected car, they're working with lots of customers on the connected car issue, right? They don't want developers to work on the plumbing. They want us to kind of give that out of the box, because SLA is operational scale, and enterprise scalability matters, but in terms of the top-layer analytics, to make sure we can make sense out of it, that's what they're, that's where they want innovation. So what you will see is that, I don't think the jobs will go in vapor, but I do think the jobs will get migrated to a different part of the stack, which today it has not been, but that's, you know, we live in Silicon Valley, that's a natural evolution we see, so I think that will happen. In general in the larger industry, again I'd say, look, driverless cars, I don't think they've driven away jobs. What they've done is created a new class of people who work. So I do think that will be a big change. >> Yeah there's a fallacy there. I mean with the ATM argument was ATM's are going to replace tellers, yet more branches opened up. >> That's exactly it. >> So therefore creating new jobs. I want to get to the quick question, I know George has a question, but I want to get on the cost of ownership, because one of the things that's been criticized in some of these emerging areas, like Hadoop and Open Stack, for instance, just to pick two random examples. It's great, looks good, you know, all peace and love. An industry's being created, legitimized, but the cost of ownership has been critical to get that done, it's been expensive, talent, to find talent and deploying it was hard. We heard that on the Cube many times. How does the cost of ownership equation change? As you go after these more value, as developers and businesses go after these more value-creating activities in the Stack? >> See look, I always say, there is no free lunch. Nothing is free. And customers realize that, that open source, if you completely wanted to, to your point, as enterprises wanted to completely scale out and create an end-to-end operational infrastructure, open source ends up being pretty expensive. For all the reasons, right, because you throw in a lot of developers, and it's not necessarily scalable, so what we're seeing right now is that enterprises, as they have figured that this works for me, but when they want to go scale it out, they want to go back to what I call a software provider, who has the scale, who has the supportability, who also has the ability to react to changes and also for them to make sure that they get the comfort that it will work. So to me, that's where they find it cheaper. Just building it, experimenting with that, it's cheaper here, but scaling it out is cheaper with a software provider, so we see a lot of our customers when we start a little bit experimenting to developers, downloading something, works great, but would I really want to take it across Nordstrom or a JP Morgan or a Morgan Stanley. I need security, I need scalability, I need somebody to call to, at that point on those equations become very important. >> And that's where the out of box experience comes in, where you have the automation, that kind of. >> Exactly. >> Does that ease up some of the cost of ownership? >> Exactly, and the talent is a big issue, right? See we live in Silicon Valley, so we. By the way, Silicon Valley hiring talent is hard. Just think about it, if you go to Kansas City, hiring a scholar developer, that's a rare breed. So just, when I go around the globe and talk to customers, they don't see that talent at all that we here just somehow take for granted. They don't, so it's hard for them to kind of put their energy behind it. >> Let me ask. More on the meta-data layer. There's an analogy that's come up from the IIoT world where they're building these digital twins, and it's not just GE. IBM's talking about it, and actually, we've seen more and more vendors where the digital twin is this, it's a digital representation now of some physical object. But you could think of it as meta-data, you know, for a physical object, and it gets richer over time. So my question is, meta-data in the old data warehouse world, was we want one representation of the customer. But now it's, there's a customer representation for a prospect, and one for an account, and one for, you know, in warranty, and one for field service. Is that, how does that change what you offer? >> That's a very very good question. Because that's where the meta-data becomes so much more important because its manifestation is changing. I'll give you a great example, take Transamerica, Transamerica is a customer of ours leveraging big data at scale, and what they're doing is that, to your question, they have existing customers who have insurance through them. But they're looking for white space analysis, who could be potential opportunities? Two distinct ones, and within that, they're looking at relationships. I know you, John, you have Transamerica, could you be an influencer with me? Or within your family, extended family. I'm a friend, but what about a family member that you've declared out there on social media? So they are doing all that stuff in the context of a data lake. How are they doing it? So in that context, think about that complexity of the job, pumping data into a lake won't solve it for them, but that's a necessary first step. The second step is where all of that meta-data through ML and AI, starts giving them that relationship graph. To say, you know what, John in itself has this white space opportunity for you, but John is related to me in one way, him and me are connected on Facebook. John's related to you a little bit more differently, he has a stronger bond with you, and within his family, he has different strong bonds. So that's John's relationship graph. Leverage him, if he has been a good customer of yours. All of that stuff is now at the meta-data level, not just the monolithic meta-data, relationship graph. His relationship graph of what he has bought from you, so that you can just see that discovery becomes a very important element. Do you want to do that in different places? You want to do that in one place. I may be in a cloud environment, I may be on prem, so that's where when I say that meta-data becomes the organized principle, that's where it becomes real. >> Just a quick follow-up on that, then. It doesn't seem obvious that every end customer of yours, not the consumer but the buyer of the software, would have enough data to start building that graph. >> I don't think, to me, what happened was, the word big data, I thought got massively abused. A lot of Hadoop customers are not necessarily big data customers. I know a lot of banking customers, enterprise banking, whose data volumes will surprise you, but they're using Hadoop. What they want is intelligence. That's why I keep saying that the meta-data part, they are more interested in a deeper understanding of the data. A great example is, if John. I had a customer, who basically had a big bank. Rich net worth customer. In their will, the daughter was listed. When the daughter went to school, by the way, went to the bank branch in that city, she had no idea, she walked up, she basically wanted to open an account. Three more friends in the line. Manager comes out because at that point, the teller said, "This is somebody you should take special care of." Boom, she goes in a special cabin, the other friends are standing in a line. Think of the customer service perception, you just created a new millennia right? That's important. >> Well this brings up the interesting comment. The whole graph thing, we love, but this brings back the neural network trend. Which is a concept that's been around for a long long time, but now it's front and center. I remember talking to Diane Green who runs Google Cloud, she was saying that you couldn't hire neural network, they couldn't get jobs 15 years ago. Now you can't hire enough of them. So that brings up the ML conversation. So, I want to take that to a question and ask about the data lake, 'cause you guys have announced a new cloud data lake. >> Yes. >> So it sounds like, from what you're saying, is you're going beyond the data lake. So talk about what that is. Because data lake, people get, you throw stuff into a lake. And hopefully it doesn't become a swamp. How are you guys going beyond just the basic concept of a data lake with your new cloud data lake? >> Yeah, so, data lake. If you remember last year, actually at Strata San Jose we chatted, and we had announced the data lake because we realized customers, to your point John, as you said, were struggling on how to even build a data lake, and they were all over the place, and they were failing. And we announced the first data lake there, and then in Strata New York, basically we brought the meta-data ML part to the data lake. And then obviously right now we're taking it to the cloud, and what we see in the world of data lake is that customers ask for three things. First, they want the prebuilt integrated solution. Data can come in, but I want the intelligence of meta-data and I want data preparation baked in. I don't want to have three different tools that I will go around, so out of the box. But we also saw, as they become successful with our customers, they want to scale up, scale down. Cloud is just a great place to go. You can basically put a data lake out there, by the way in the context of data, a lot of new data sources are in the cloud, so it's easy for them to scale in and out in the cloud, experiment there and all that stuff. Also you know Amazon, we supported Amazon Kinesis, all of these new sources and technologies in the world of cloud are allowing experimentation in the data lake, so that allowed our customers to basically get ahead of the curve very quickly. So in some ways, cloud allowed customers to do things a lot faster, better, and cheaper. So that's what we basically put in the hands of our customers. Now that they are feeling comfortable, they can do a secured and governed data lake without feeling that it's still not self-served. They want to put it in the cloud and be a lot more faster and cheaper about it. >> John: And more analytics on it. >> More analytics. And now, because our ML, our AI, the meta-data part, connects cloud, ground, everything. So they have an organizing principle, whatever they put wherever, they can still get intelligence out of it. >> Amit, we got to break, but I want to get one final comment for you to kind of end the segment, and it's been fun watching you guys work over the past couple years. And I want to get your perspective because the product decisions always have kind of a time table to them, it's not like you made this up last night because it's trendy, but you guys have made some good product choices. It seems like the wind's at your back right now at Informatica. What, specifically, are bets that you guys made a couple years ago that are now bearing fruit? Can you just take a minute to end the segment, share some of those product bets. Because it's not always that obvious to make those product bets years earlier, seems to be a tail wind for you. You agree, and can you share some of those bets? >> I think you said it rightly, product bets are hard, right? Because you got to see three, four years ahead. The one big bet that we made is that we saw, as I said to you, the decoupling of the data layer. So we realized that, look, the app layer's getting fragmented. The cloud platforms are getting fragmented. Databases are getting fragmented. That that whole old monolithic architecture is getting fundamentally blown up, and the customers will be in a multi, multi, multi spread out hybrid world. Data is the organizing principle, so three years ago, we bet on the intelligent data platform. And we said that the intelligent data platform will be intelligent because of the meta-data driven layer, and at that point, AI was nowhere in sight. We put ML in that picture, and obviously, AI has moved, so the bet on the data platform. Second bet that, in that data platform, it'll all be AI, ML driven meta-data intelligence. And the third one is, we bet big on cloud. Big data we had already bet big on, by the way. >> John: You were already there. >> We knew the cloud. Big data will move to the cloud far more rapidly than the old technology moved to the cloud. So we saw that coming. We saw the (mumbles) wave coming. We worked so closely with AWS and the Azure team. With Google now, as well. So we saw three things, and that's what we bet. And you can see the rich offerings we have, the rich partnerships we have, and the rich customers that are live in those platforms. >> And the market's right on your doorstep. I mean, AI is hot, ML, you're seeing all this stuff converge with IoT. >> So those were, I think, forward-looking bets that paid out for us. (chuckles) And but there's so much more to do, and so much more upside for all of us right now. >> A lot more work to do. Amit, thank you for coming on, sharing your insight. Again, you guys got in good pole position in the market, and again it's right on your doorstep, so congratulations. This is the Cube, I'm John Furrier with George Gilbert. With more coverage in Silicon Valley for Big Data SV and Strata + Hadoop after this short break.