>> From around the globe, it's theCUBE, with digital coverage of VMworld 2020, brought to you by the VMworld and its ecosystem partners. >> I'm Stu Miniman, and welcome back to theCUBES coverage of VMworld 2020, our 11th year doing this show, of course, the global virtual event. And what do we love talking about on theCUBE? We love talking to customers. It is a user conference, of course, so really happy to welcome to the program. From the University of Pisa, the Chief Technology Officer Maurizio Davini and joining him is Thierry Pellegrini, one of our theCUBE alumni. He's the vice president of worldwide, I'm sorry, Workload Solutions and HPC with Dell Technologies. Thierry, thank you so much for joining us. >> Thanks too. >> Thanks to you. >> Alright, so let, let's start. The University of Pisa, obviously, you know, everyone knows Pisa, one of the, you know, famous city iconic out there. I know, you know, we all know things in Europe are a little bit longer when you talk about, you know, some of the venerable institutions here in the United States, yeah. It's a, you know, it's a couple of hundred years, you know, how they're using technology and everything. I have to imagine the University of Pisa has a long storied history. So just, if you could start before we dig into all the tech, give us our audience a little bit, you know, if they were looking up on Wikipedia, what's the history of the university? >> So University of Pisa is one of the oldest in the world because there has been founded in 1343 by a pope. We were authorized to do a university teaching by a pope during the latest Middle Ages. So it's really one of the, is not the oldest of course, but the one of the oldest in the world. It has a long history, but as never stopped innovating. So anything in Pisa has always been good for innovating. So either for the teaching or now for the technology applied to a remote teaching or a calculation or scientific computing, So never stop innovating, never try to leverage new technologies and new kind of approach to science and teaching. >> You know, one of your historical teachers Galileo, you know, taught at the university. So, you know, phenomenal history help us understand, you know, you're the CTO there. What does that encompass? How, you know, how many students, you know, are there certain areas of research that are done today before we kind of get into the, you know, the specific use case today? >> So consider that the University of Pisa is a campus in the sense that the university faculties are spread all over the town. Medieval like Pisa poses a lot of problems from the infrastructural point of view. So, we have bought a lot in the past to try to adapt the Medieval town to the latest technologies advancement. Now, we have 50,000 students and consider that Pisa is a general partners university. So, we cover science, like we cover letters in engineering, medicine, and so on. So, during the, the latest 20 years, the university has done a lot of effort to build an infrastructure that was able to develop and deploy the latest technologies for the students. So for example, we have a private fiber network covering all the town, 65 kilometers of a dark fiber that belongs to the university, four data centers, one big and three little center connected today at 200 gigabit ethernet. We have a big data center, big for an Italian University, of course, and not Poland and U.S. university, where is, but also hold infrastructure for the enterprise services and the scientific computing. >> Yep, Maurizio, it's great that you've had that technology foundation. I have to imagine the global pandemic COVID-19 had an impact. What's it been? You know, how's the university dealing with things like work from home and then, you know, Thierry would love your commentary too. >> You know, we, of course we were not ready. So we were eaten by the pandemic and we have to adapt our service software to transform from imperson to remote services. So we did a lot of work, but we are able, thanks to the technology that we have chosen to serve almost a 100% of our curriculum studies program. We did a lot of work in the past to move to virtualization, to enable our users to work for remote, either for a workstation or DC or remote laboratories or remote calculation. So virtualization has designed in the past our services. And of course when we were eaten by the pandemic, we were almost ready to transform our service from in person to remote. >> Yeah, I think it's, it's true, like Maurizio said, nobody really was preparing for this pandemic. And even for, for Dell Technologies, it was an interesting transition. And as you can probably realize a lot of the way that we connect with customers is in person. And we've had to transition over to modes or digitally connecting with customers. We've also spent a lot of our energy trying to help the community HPC and AI community fight the COVID pandemic. We've made some of our own clusters that we use in our HPC and AI innovation center here in Austin available to genomic research or other companies that are fighting the the virus. And it's been an interesting transition. I can't believe that it's already been over six months now, but we've found a new normal. >> Detailed, let's get in specifically to how you're partnering with Dell. You've got a strong background in the HPC space, working with supercomputers. What is it that you're turning to Dell in their ecosystem to help the university with? >> So we are, we have a long history in HPC. Of course, like you can imagine not to the biggest HPC like is done in the U.S. so in the biggest supercomputer center in Europe. We have several system for doing HPC. Traditionally, HPC that are based on a Dell Technologies offer. We typically host all kind of technology's best, but now it's available, of course not in a big scale but in a small, medium scale that we are offering to our researcher, student. We have a strong relationship with Dell Technologies developing together solution to leverage the latest technologies, to the scientific computing, and this has a lot during the research that has been done during this pandemic. >> Yeah, and it's true. I mean, Maurizio is humble, but every time we have new technologies that are to be evaluated, of course we spend time evaluating in our labs, but we make it a point to share that technology with Maurizio and the team at the University of Pisa, That's how we find some of the better usage models for customers, help tuning some configurations, whether it's on the processor side, the GPU side, the storage and the interconnect. And then the topic of today, of course, with our partners at VMware, we've had some really great advancements Maurizio and the team are what we call a center of excellence. We have a few of them across the world where we have a unique relationship sharing technology and collaborating on advancement. And recently Maurizio and the team have even become one of the VMware certified centers. So it's a great marriage for this new world where virtual is becoming the norm. >> But well, Thierry, you and I had a conversation to talk earlier in the year when VMware was really geering their full kind of GPU suite and, you know, big topic in the keynote, you know, Jensen, the CEO of Nvidia was up on stage. VMware was talking a lot about AI solutions and how this is going to help. So help us bring us in you work with a lot of the customers theory. What is it that this enables for them and how to, you know, Dell and VMware bring, bring those solutions to bear? >> Yes, absolutely. It's one statistic I'll start with. Can you believe that only on average, 15 to 20% of GPU are fully utilized? So, when you think about the amount of technology that's are at our fingertips and especially in a world today where we need that technology to advance research and scientistic discoveries. Wouldn't it be fantastic to utilize those GPU's to the best of our ability? And it's not just GPU's , I think the industry has in the IT world, leverage virtualization to get to the maximum recycles for CPU's and storage and networking. Now you're bringing the GPU in the fold and you have a perfect utilization and also flexibility across all those resources. So what we've seen is that convergence between the IT world that was highly virtualized, and then this highly optimized world of HPC and AI because of the resources out there and researchers, but also data scientists and company want to be able to run their day to day activities on that infrastructure. But then when they have a big surge need for research or a data science use that same environment and then seamlessly move things around workload wise. >> Yeah, okay I do believe your stat. You know, the joke we always have is, you know, anybody from a networking background, there's no such thing as eliminating a bottleneck, you just move it. And if you talk about utilization, we've been playing the shell game for my entire career of, let's try to optimize one thing and then, oh, there's something else that we're not doing. So,you know, so important. Retail, I want to hear from your standpoint, you know, virtualization and HPC, you know, AI type of uses there. What value does this bring to you and, you know, and key learnings you've had in your organization? >> So, we as a university are a big users of the VMware technologies starting from the traditional enterprise workload and VPI. We started from there in the sense that we have an installation quite significant. But also almost all the services that the university gives to our internal users, either personnel or staff or students. At a certain point that we decided to try to understand the, if a VMware virtualization would be good also for scientific computing. Why? Because at the end of the day, their request that we have from our internal users is flexibility. Flexibility in the sense of be fast in deploying, be fast to reconfiguring, try to have the latest beats on the software side, especially on the AI research. At the end of the day we designed a VMware solution like you, I can say like a whiteboard. We have a whiteboard, and we are able to design a new solution of this whiteboard and to deploy as fast as possible. Okay, what we face as IT is not a request of the maximum performance. Our researchers ask us for flexibility then, and want to be able to have the maximum possible flexibility in configuring the systems. How can I say I, we can deploy as more test cluster on the visual infrastructure in minutes or we can use GPU inside the infrastructure tests, of test of new algorithm for deep learning. And we can use faster storage inside the virtualization to see how certain algorithm would vary with our internal developer can leverage the latest, the beat in storage like NVME, MVMS or so. And this is why at the certain point, we decided to try visualization as a base for HPC and scientific computing, and we are happy. >> Yeah, I think Maurizio described it it's flexibility. And of course, if you think optimal performance, you're looking at the bare medal, but in this day and age, as I stated at the beginning, there's so much technology, so much infrastructure available that flexibility at times trump the raw performance. So, when you have two different research departments, two different portions, two different parts of the company looking for an environment. No two environments are going to be exactly the same. So you have to be flexible in how you aggregate the different components of the infrastructure. And then think about today it's actually fantastic. Maurizio was sharing with me earlier this year, that at some point, as we all know, there was a lot down. You could really get into a data center and move different cables around or reconfigure servers to have the right ratio of memory, to CPU, to storage, to accelerators, and having been at the forefront of this enablement has really benefited University of Pisa and given them that flexibility that they really need. >> Wonderful, well, Maurizio my understanding, I believe you're giving a presentation as part of the activities this week. Give us a final glimpses to, you know, what you want your peers to be taking away from what you've done? >> What we have done that is something that is very simple in the sense that we adapt some open source software to our infrastructure in order to enable our system managers and users to deploy HPC and AI solution fastly and in an easy way to our VMware infrastructure. We started doing a sort of POC. We designed the test infrastructure early this year and then we go fastly to production because we had about the results. And so this is what we present in the sense that you can have a lot of way to deploy Vitola HPC, Barto. We went for a simple and open source solution. Also, thanks to our friends of Dell Technologies in some parts that enabled us to do the works and now to go in production. And that's theory told before you talked to has a lot during the pandemic due to the effect that stay at home >> Wonderful, Thierry, I'll let you have the final word. What things are you drawing customers to, to really dig in? Obviously there's a cost savings, or are there any other things that this unlocks for them? >> Yeah, I mean, cost savings. We talked about flexibility. We talked about utilization. You don't want to have a lot of infrastructure sitting there and just waiting for a job to come in once every two months. And then there's also the world we live in, and we all live our life here through a video conference, or at times through the interface of our phone and being able to have this web based interaction with a lot of infrastructure. And at times the best infrastructure in the world, makes things simpler, easier, and hopefully bring science at the finger tip of data scientists without having to worry about knowing every single detail on how to build up that infrastructure. And with the help of the University of Pisa, one of our centers of excellence in Europe, we've been innovating and everything that's been accomplished for, you know at Pisa can be accomplished by our customers and our partners around the world. >> Thierry, Maurizio, thank you much for so much for sharing and congratulations on all I know you've done building up that COE. >> Thanks to you. >> Thank you. >> Stay with us, lots more covered from VMworld 2020. I'm Stu Miniman as always. Thank you for watching the theCUBE. 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>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen, Brought to you by Del Technologies and its ecosystem partners. >> Welcome back to Las Vegas, Lisa Martin. With the cue, we're live Day one of our duel set coverage of Del Technologies World twenty nineteen student a menace here with me, and we're welcoming back a couple of alumni. But for the first time together on our set, we've got Terry Pellegrino, the BP of high performance computing at Delhi Emcee and Nick, who grew VP of Data Analytics and Cyber Securities just at MasterCard. Did I get that right? All right, good. So, guys, thanks for joining Suited me this afternoon, by the way. So we will start with you High performance computing. Talk about that a lot. I know you've been on the Cube talking about HPC in the Innovation lab down in in Austin, high performance computing, generating a ton of data really requiring a I. We talk a lot of it II in machine learning, but let's look at it in the context of all this data. Personal data data from that word, you know, it turns out do with mastercard, for example How are you guys working together? Dell Technologies and MasterCard to ensure that this data is protected. It secure as regulations come up as fraud, is a huge, expensive >> issue. Well, I think make way worked together to really well worry about the data being secure, but also privacy being a key item that we worry about every day you get a lot of data coming through, and if we let customer information or any kind of information out there, it can be really detrimental. So we've really spent a lot of time not only helping manage and worked through the data through the infrastructure and the solutions that we've put together for. For Nick, who also partnered with the consortium project that got started Mosaic Crown to try to focus even more on data privacy on Mosaic Crown is is really interesting because it's getting together and making sure that the way we keep that privacy through the entire life cycle of the data that we have the right tools tio have other folks understand that critical point. That's that's how we got all the brains working together. So it's not just Delon DMC with daily emcee and MasterCard It's also ASAP We have use of Milan, you're sort of bergamot and we'Ll solve the only three c and all together back in January decided to get together and out of Nick's idea. Think about how we could put together with all those tools and processes to help everybody have more private data. Other. >> I think this was your idea. >> I can't say it was my idea. The European Union itself with what? The advent of Judy parent privacy. Their biggest concern was we don't want people to stop sharing. Data began with artificial intelligence. The great things that we do with it from the security, you know, carrying diseases all the way through, making sure transactions are safe and secure. Look, we don't want people to stop our organizations to stop sharing that data because they have fear of the regulations. How do we create a date on market? So the U has something called Horizon twenty twenty on one of their initiatives. Wass Way wanted to understand what a framework for data market would look like where organizations can share that data with confidence that they're complying to all the regulations there, doing the anonymous ization of that data, and the framework itself allows someone to say, I could do analysis without worrying that if it's surfacing personally identifiable information or potentially financial information, but I can share it so that it can progress the market data economy. So as a result of that, what we did is we put the guilt. I said, This is a really good idea for us. Went to the partners at del. That's it, guys, this is something we should consider doing now. Organization always been looking at privacy, and as a result, we've done a very good job of putting that consortium together. >> So, Nick, we've talked with you on the Cuba quite a few times about security. >> Can you just give >> us? You know, you talked about that opportunity of a I We don't want people to stop giving data in. There was concerned with GPR that Oh, wait, I need you to stop collecting information because I'm going to get sued out of existence. If it happened, how do we balance that? You know, data is the new oil I need, you know, keep not flowing and oh, my God. I'm going to get hacked. I'm going to get sued. I'm going to have the regulation, You know, people's personal information. I'm goingto walk down the grocery store and they're going to be taking it from me. How do we balance that? >> Well, the nice part is, since State is the new oil, well, we considered it is artificial intelligences that refinery for that oil. So, for our perspective, is the opportunity to say we can use a eye to help. Somebody says, Hey, I don't want you to share my data information. I want to be private, but I can use a I d. S. Okay, let's filter those out so I can use a I'd actually sit on top of that. I can sit down and say, Okay, how do I keep that person's safe, secure and only share the necessary data that will solve the problem again, using artificial intelligence through different types of data classifications, whoever secure that data with different methods of data security, how we secure those types of things come into play. And again, there's also people say, I don't ever want my data to be we identified so we can use different methods to do complete anonymous ation. >> How do you do that when there are devices that are listening constantly, what Walmart's doing? Everybody that has those devices at home with the lady's name. I won't say it. I know it activates it. How How do you draw the line with ensuring that those folks that don't want certain things shared if they're in the island Walmart talking about something that they don't want shared? How do you facilitate that? >> Well, part of that is okay. At a certain point, when it comes to privacy, you've gotta have a little bit of parenting. Just because you have that information doesn't mean you need to use that information. So that's where we as humans have to come into play and start thinking about what is the data that we're collecting And how should we use that information on that person and who is walking through a store? And we say we are listening to what their conversations are? Well, I don't need to identify that you or you. I just didn't know what is the top talking about? Maybe that's the case, but again, you have to make that decision again. It's about being a parent at this point. That's the ethical part of data which we've discussed on this program before. Alright, >> so teary. Talkto us some about the underlying architecture that's going to drive all of this. You know, we we love the shift. For years ago, it was like storing my data. You know, Now we're talking about how do we extract the value of the data? We know data's moving a lot, So you know what's changing And I talk every infrastructure company I talked to, it's like, Oh, well, we've got the best ai ai, you know, x, whatever. So you know what kind of things should custom be looking for To be able to say, Oh, this is something, really. It's about scale. It's about, you know, really focused on my data. Yeah, absolutely. Well, I will say first, the end of underlying infrastructure. We have our set of products that have security intrinsic in the way they're designed. I really worry about ki management for software we have silicon based would have trust throughout a lot of our portfolio. We also think about secure supply chain, even thinking through security race. If you lose your hard drive on, we can go and make sure that the data is not removed. So that's on the security front. On the privacy side, as a corporation, William C. Is very careful about the data that we have access to on. Then you think about a HBC. So being in charge of H. P. C for Cordelia emcee way actually are part of how the data gets created, gets transferred, gets generated, curated and then stored. Of course, storage s O. What we want to make sure is our customers feel like where that one company that can help them through their journey for their data. And as you heard Michael this morning during keynote, >> uh, getting that value out of the data because it's really where that little transformation is going to get everybody to the next level. But right now there's a lot of data. Has Nick stated this data has more personal information at times? Andan i'll add one more thing way. Want to really make sure that innovation is not stifled and the way we get there is to make sure >> that the data sets are as broad as possible, and today it's very difficult to share data. Sets mean that there are parts of the industry there are so worried about data that they will not even get it anywhere else than their own data center and locked behind closed doors. But if you think about all the data scientists, they're craving more data. And the way we can get there is with what make it talked about is making sure that the data that is collected is free of personal information and can still be qualified for some analysis and letting all the data scientists out there to get a lot of value out of it. >> So HBC can help make the data scientist job simpler or simplify evaluating this innumerable amun of data. >> Correct. So what in the days you had an Excel spreadsheet and wanted to run and put the table on it, you could do that on a laptop for end up tablet. When you start thinking about finding a black hole in the galaxy, you can do that on tablet. So you're gonna have to use several computers in a cluster with the right storage of the right interconnect. And that's why it's easy comes in place. >> I mean, if I man a tactical level, what you'LL see with HBC computing is when someone's in the moment, right? You want to be able to recognize that person has given me the right to communicate to them or has not given me the right to communicate to them, even though they're trying to do something that could be a transaction. The ability to say Hey, I have I know that this person's or this device is operating here is this and they have given me these permissions. You've got to do that in real time, and that's what you're looking for. HBC competing to do. That's what you're saying. I need my G p you to process in that way, and I need that cpt kind of meat it from the courts. The edges say Yep, you can't communicate. No, you can't. Here's where your permissions like. So, >> Nick, what should we >> be looking for? Coming out of this consortium is people are watching around the industry. You know what, what, what >> what expect for us? The consortium's about people understand that they can trust that they're data's being used properly, wisely, and it's being used in the way it was intended to be used so again, part of the framework is what do you expect to do with the data so that the person understands what their data is being used for the analysis being done? So they have full disclosure. So the goal here is you can trust your data's being used. The way was intended. You could trust that. It's in a secure manner. You can trust that your privacy is still in place. That's what we want this construction to create that framework to allow people to have that trust and confidence. And we want the organization to be able to not, you know, to be able to actually to share that information to again move that date economy forward. >> That trust is Nirvana. Well, Nick Terry, thank you so much for joining suing me on the cue this afternoon. Fascinating conversation about HPC data security and privacy. We can't wait to hear what's in store next for this consortium. So you're gonna have to come back. Thank >> you. We'LL be back. Excellent. Thanks so much. >> Our pleasure. First Minutemen, I'm Lisa Martin. You're watching us live from Las Vegas. The keeps coverage of day one of del technology World twenty nineteen. Thanks for watching

[Music] and welcome back everybody Jeff Rick here at the cube we're in Austin Texas at the deli MC high performance computing and artificial intelligence labs last been here for a long time as you can see behind us and probably here racks and racks and racks of some of the biggest baddest computers on the planet in fact I think number 256 we were told earlier it's just behind us we're excited to be here really as Dell and EMC puts together you know pre-configured solutions for artificial intelligence machine learning deep learning applications because that's a growing growing concern and growing growing importance to all the business people out there so we're excited to have the guy running the show he's Terry Pellegrino the VP of HPC and business strategy had a whole bunch of stuff you're a pretty busy guy I'm busy but you can see all those servers they're very busy too they're humming so just your perspective so the HPC part of this has been around for a while the rise of kind of machine learning and artificial intelligence as a business priority is relatively recent but you guys are jumping in with both feet oh absolutely I mean HPC is not new to us AI machine learning deep learning is happening that's the buzzword but we've been working on HPC clusters since back in the 90s and it's it's great to see this technology or this best practice getting into the enterprise space where data scientists need help and instead of looking for a one processor that will solve it all they look for the knowledge of HPC and what we've been able to put together and applying into their field right so how do you kind of delineate between HPC and say the AI portion of the lab or is it just kind of on a on a continuum how do you kind of slice and dice absolutely it's it's all in one place and you see it all behind us this area in front of us we try to get all those those those servers put together and add the value for all the different workloads right so you get HPC a piece equal a IML deal all in one lab right and they're all here they're all here the old the legacy application only be called legacy applications all the way to the to the meanest and the newest and greatest exactly the old stuff the new stuff and and actually you know what some things you don't see is we're also looking at where the technology is going to take all those workloads AI m LD L is the buzzword today but down the road you're gonna see more applications and we're already starting to test those technologies in this lab so it's past present and future right so one of the specific solutions you guys have put together is the DL using the new Nvidia technology what if you could talk we hear about a media all the time obviously they're in really well position in autonomous vehicles and and their GPUs are taking data centers by storm how's that going where do you see some of the applications outside of autonomous vehicles for the the Nvidia base oh there are many applications I think the technology itself is is proving to solve a lot of customer problems and you can apply it in many different verticals many workloads again and you can see it in autonomous vehicles you can see it in healthcare live science in financial services risk management it's it's really everywhere you need to solve a problem and you need dense compute solutions and NVIDIA has one of technologies that a lot of our customers leverage to solve their problems right and you're also launching a machine learning solution based on Hadoop which we we've been going to Hadoop summit Hadoop world and strata for eight nine years I guess since 2010 eight years and you know it's kind of funny because the knock on Hadoop is always there aren't enough people it's too hard you know it's just a really difficult technology so you guys are really taken again a solutions approach with a dupe for machine learning to basically deliver either a whole rack full of stuff or that spec that you can build at your own place no absolutely that's one of the three major tenants that we have for those solutions that we're launching we really want it to be a solution that's faster so performance is key when you're trying to extract data and insights from from your data set you really need to be fast you don't want it to take months it has to be within countable measures so it's one of them we want to make it simple a data scientist is never going to be a PhD in HPC or any kind of computer technologies so making it simple it's critical and the last one is we want to have this proven trusted adviser feel for our customers you see it around you this HPC lab was not built yesterday it's been here showcasing our capabilities in HPC world our ability to combine the Hadoop environment with other environments to solve enterprise class problems and bring business value to our customers and that's really what we we think are our differentiation comes from right and it's really a lab I mean you and I are both wearing court coats right now but there's a gear stack following really heights of every shape and size and I think what's interesting is while we talk about the sexy stuff the GPUs and the CPUs and the do there's a lot of details that make one of these racks actually work and it's probably integrating some of those things as lower tier things and making sure they all work seamlessly together so you don't get some nasty bottleneck on an inexpensive part that's holding back all that capacity oh absolutely you know it's funny you mentioned that we're talking to customers about the technologies we're assembling and contrary to some web tech type companies that just look for any compute at all costs and they'll just stack up a lot of technologies because they want the compute in in HPC type environments or when you try to solve problems with deep learning and machine learning you're only as strong as your weakest link and if you have a a server or a storage unit or a an interconnect between all those that is really weak you're gonna see your performance go way down and we watch out for that and you know the one thing that you alluded to which I just wanted to point out what you see behind us is the hardware the the secret sauce is really in the aggregation of all the components and all the software stacks because AI M LDL great easy acronyms but when you start peeling the layers you realize it's layers and layers of software which are moving very fast where you don't want to be spending your life understanding the inter up requirements between those layers and and worrying about whether your your compute and your storage solution is gonna work right you want to solve problems a scientist and that's what we're trying to do give you a solution which is an infrastructure plus a stack that's been validated proven and you can really get to work right and even within that validated design for a particular workload customers have an opportunity maybe needs a little bit more IO as a relative scale these a little bit more storage needs a little bit more compute so even within a basic structured system that you guys have SPECT and certified still customers can come in and make little mods based on what their specific workload you've got it this is not we're not in the phase in the acceptance of a I am LDL where things are cookie cutter it's still going to be a collaboration that's what we have a really strong team working with our customers directly and trying to solution for their problem right if you need a little bit more storage if you need faster storage for your scratch if you need a little bit more i/o bandwidth because you're in a remote environment I mean all those characteristics are gonna be critical and the solutions we're launching are not rigid they're they're perfect starting point for customers I want to get something to run directly they feel like it but if you if you have a solution that's more pointed we can definitely iterate and that's what our team in the field and all the engineers that you have seen today walk through the lab that's what their role is we want to be as a consultant as a partner designing the right solution for the customer right so Terry before I let you guys just kind of one question from your perspective of customers and you're out talking to customers and how the conversation around artificial intelligence and machine learning has evolved over the last several years from you know kind of a cool science experiment or it's all the HPC stuff with the government or whether or heavy lifting really moving from that actually into a boardroom conversation as a priority and a strategic imperative going forward how's that conversation evolving when you're out talking to customers well you know it has changed you're right back in the 60s the science was there the technology wasn't there today we have the science we have the technology and we're seeing all the C Class decision makers really want to find value out of the data that we've collected and that that's where the discussion takes place this is not a CIO discussion most of the time and in what's really fantastic in mama contrary to a lot of the the technologies I have grown on like big data cloud and all those buzzwords here we're looking at something that's tangible we have real-life examples of companies that are using deep learning and machine learning to solve problems save lives and get our technology in the hands of the right folks so they can impact the community it's really really fantastic and that growth is set for success and we want to be part of that right it's just a minute just you know the continuation of this democratization trend you know get more people more data give more people more tools get more people more power and you're gonna get innovation you're gonna solve more problems and it's so exciting absolutely totally agree with you all right teri well thanks for taking a few minutes out of your busy day and congrats on the Innovation Lab here thank you so much all righty teri I'm Jeff Rick we're at the Dell EMC HPC and AI innovation labs in Austin Texas thanks for watching

(upbeat music) >> Welcome back everyone, theCUBE's three days of wall to wall coverage of Snowflake Summit '22 is coming to an end, but Dave Vellante and I, Lisa Martin are so pleased to have our final guest as none other than the co-founder and president of products at Snowflake, Benoit Dageville. Benoit, thank you so much for joining us on the program. Welcome. >> Thank you. Thank you, thank you. >> So this is day four, 'cause you guys started on Monday. This is Thursday. The amount of people that are still here speaks volumes. We've had close to 10,000 people here. >> Yeah. >> Could you ever have imagined back in the day, 10 years ago that it would come to something like this in such a short period of time? >> Absolutely not. And I always say if I had imagined that I might not have started Snowflake, right. This is somehow scary. I mean and yeah, it's huge. And you can feel the excitement of everyone. It is like mind boggling and the fact that so many people are still there after four days is great. >> Your keynote on Tuesday was fantastic. Your energy was off the charts. It was standing room only. There were overflow rooms. Like we just mentioned, a lot of people are still here. Talk about the evolution of Snowflake, this week's announcements and what it means for the future of the data cloud. >> Yeah, so evolution, I mean, I will start with the evolution. It's true that that's what we have announced. This week is not where we started necessarily. So we started really very quickly with big data combined with data warehouse as one thing. We saw that the world was moving into fragmented siloing data and we thought with Thierry, we are going to combine big data and data warehouse in one system for the cloud with this elasticity and this service simplicity. So simplicity, amazing elasticity, which is this multi workload architecture that I was explaining during the keynotes and really extreme simplicity with the service. Then we realized that there is one other attribute in the cloud, which is unique, which doesn't exist on-premise, which is collaboration. How you can connect different tenets of the platform together. And Google showed that with Google Docs. I always say to me, it was amazing that you could share document and have direct access to document that you didn't produce and you can collaborate on this document. So we wanted to do the same thing for data and this is where we created the data cloud and the marketplace where you can have all these data sets available and really the next evolution I would say is really about applications that are (indistinct) by that data, but are way simpler to use for all the tenets of the data cloud. And this is the way you can share expertise also, including, ML model, everyone talks about ML and the democratization of ML. How are you going to democratize ML? It's not by making necessary training super easy. Such that everyone can train their ML for themselves. It's by having very specialized application where data and ML is at the core, which are shared, through the marketplace and we shall leverage by many tenets of this marketplace that have no necessary knowledge about building this ML models. So that's where, yeah. >> When you and Thierry started the company, I go back to the improbable rise of Kubernetes and there were other more sophisticated container management systems back then, but they chose to focus on simplicity. And you've told me before, that was our main tenet. We are not going to worry about all the complex database stuff. You knew how to do that, but you chose not to. So my question is, did you envision solving those complex problems over time yourselves or through an ecosystem? Was this by design or did you... As you started to get into it, say let's not even try to go there let's partner to go there. >> Yeah, I mean, it's both. It's a combination of both. Snowflake, the simplicity of the platform is really important because if our partners are struggling to put their solution and build solution on top of Snowflake they will not build it. So it's very important that number one, our platform is really easy to use from day one. And that really has to be built inside the platform. You cannot build simplicity on top. You cannot have a complex solution and all of a sudden realize that, oh, this is complex. I need to build another layer on top of it to make it simpler, that will not work. So it had to be built from day one, but you're right. What is going to be Snowflake? I always say in 10 years from now, we just turn 10 years old or we are going to turn 10 years old in few months. Actually a few months, yes. >> Right. >> So for the next 10 years I really believe that most of Snowflake will not be built by Snowflake. And that's the power of the partners and these applications. When you are going to say I'm using Snowflake, actually, probably you are not going to use directly code developed by Snowflake. That code will leverage our platform, but you will use a solution that has been built on top of Snowflake. And this is the way we are going to decouple, the effort of Snowflake and multiply it. >> It's an interesting balance, isn't it? When I think of what you did with Apache Iceberg, if I use Iceberg and I'm not going to get as much functionality, but I may want that openness, but I'm going to get more functionality inside of the data cloud. And I don't know, but if you know the answer to what's going to happen. >> No, that's a super good question. So to explain what we did with Apache Iceberg, and the fact that now it's a native format for us. So everything that you can do with our internal formats, you can do it with Apache Iceberg, including security, defining masking, data masking all the governors that we have, fine grain security aspects, the replications you can define you can use (indistinct) on top of... >> But there's a but, right? But if I do that with native Snowflake tools, I'm going to get an even greater advantage, am I not? >> Yes. So that's what I'm saying. So that's why we embraced Iceberg, because I think we can bring all the benefit of Snowflake to people who have decided to use Iceberg, I mean open formats. Iceberg is a table format. So and why it was important because people had massive investments in open source in Hadoop. And we had a lot of companies saying, we love Snowflake. We want to be a Snowflake customer, but we cannot really migrate all our data. I mean, it will be really costly. And we have a lot of tools that need access, direct access. So this is why we created Iceberg because we can really... I mean, we really think that we can bring the benefit of Snowflake to this data. >> Gives customers optionality. Okay. I use this term super cloud. You don't use the term, but that's okay. And I get a lot of heat for it. But to me, what you're doing is quite a bit different than multicloud because you're creating that abstraction layer. You're bringing value above it. My question to you is, the most of the heat I get is, oh, that's just SaaS. Are you just SaaS? >> No. I mean, no, absolutely not. I mean, you're right we are a super cloud. I mean it's a much better word than saying we are multicloud. Multicloud is often viewed as oh, I have my system and now I can run this system in the different cloud providers. Snowflake is different. We have one single platform for the world, which happens to have some regions are AWS region, some regions are Azure, some regions are GCP, Google and we merge them together. We have this Snowgrid technology that connects all our regions together so that we have really one platform for the world. And that's very important because when you talk about connections of data and expertise applications you want to have global reach, right. It doesn't exist. We are not siloed by region of the world, right? You have a lot of companies which are multinational that have presence everywhere. And you want to have this global reach. The world is not a independent set of regions and countries, right. And that's the realization. So we had to create this global platform for our customers. >> And now you have people building clouds on top of your data cloud, well that to me is the next signal. In your keynote, you talked about seven pillars, all data, all workloads, global architecture, self-managed, programmable, marketplace, governance, which ones are the most important? >> All of them. It's like when you have kids, you don't want to pick and say, this one is my preferred one, so they are really important. All of them, as I said without data, there is no Snowflake, right? So all data is so important that we can reach every data, wherever it is. And Iceberg is a part of that, but all workload is really important because you don't want to put your data in one platform, if you cannot run all your workloads and workloads are much broader than just data warehousing, there is data engineering, data science, ML engineering, (indistinct) all these workloads applications. So that's critical. Programmable is where we are moving, right. We want to be the place where data applications are built. And we think we have a lot of advantages because data application needs to use many workloads at once, right? It's not that that application will do only data warehousing, they need to store their states, they need to use this new workload that we define, which is Unistore. They need to do data engineering because they need to get data, right. They have to save this data. So they need to combine many workload and if they have to stitch this workload, because the platform was not designed as one single product where everything is consistent and works together, that you have to stitch, it's complicated for this application to make it work. So Snowflake is we believe an ideal platform to run these data applications. So all workloads, programmable, obviously, so that you can program. And programmable has two aspects, which is big part of our announcement. Is both data programmability, which is running Python against petabyte, terabytes of data at scale and doing it scale out. So that's what we call data programmability. So both Java, Python and (indistinct), but also running applications like UI. And we had this acquisition of Streamlit. Streamlit now has been fully integrated in Snowflake. We announced that such that not only you can have this data programmability, but you can expose your data through this nice UIs, interactive UI to business users potentially. So it goes all the way there. Global is super important. As we say, we want to be one platform for the world. And of course, as I said, the last pillar, which is somehow critical for us, because we are cloud, we need to have governance. We need to have security of our data. And why it took us so long to do Python is not because it's out to run Python, right? Everyone can run Python it's because we had to secure it. And I talk about it creating this amazing sandboxing technology, such that when you include third party libraries and third party codes, you are guaranteed that this third party code will not reach to infiltrate your data, right. We control the environment that Snowflake provides. >> Can you share us some of the feedback from the customer? You probably had many customer conversations over the last four days. >> Look at that smile. (interviewer laughing) (Lisa laughing) >> Actually not because I was so busy everywhere. Unfortunately, I didn't speak to many customers. Saying that, I had everyone stopping me and talking about what they heard and yeah, there is a huge excitement about all of this. >> What's been the feedback around the theme of the event? The world of data collaboration. Data collaboration is so critical as every company these days must be a data company to compete, to win. What's been from just some of the feedback that you've had customers really embracing data collaboration, what Snowflake is enabling. >> Yeah. I mean, almost every company which is using Snowflake, is collaborating with data. You have heard, the number of stable edges that we have, and there is a real need for that because your data alone... You cannot make sense of your data if it is just alone. It needs to be connected with other data. You haven't not generated. So all data, when you say the first pillar of Snowflake is all data is not only about your data, but is about all the data that's created around you. That puts perspective on your own data. And that's critical and it's so painful to get. I mean, even your data is difficult to have access to your data, but imagine data that you didn't produce. And so yes, so the data collaboration is critical, and then now we expanded it to application and expertise, sharing models, for example, That's going to have a huge impact. >> All data includes now transaction data, right? >> Yes. >> That's a big part of the announcements that you guys made. >> Yeah. So and that's the motivation for that was really, if we want to run application, full application, we announced native applications, which are fully executed and run inside the (indistinct) data cloud, right. They need all the services that application need and in particular managing their states. And so we created Unistore, which is a new workload, which allows you to combine transactional data, which are generated by this application. And at the same time being able to do analytics directly on this data. So we call it Hybrid Table because it has this hybrid aspect. You can do both transactional access to this data and at the same time analytic here without having data pipeline and moving data and transforming it from the transactional system to the analytical system, right. Snowflake is one system. Again, in the spirit of simplifying everything, this is the Snowflake (indistinct). >> I can ask the same question I ask at first, (indistinct) when was the aha moment that you and Thierry had that said, this is not just a better data warehouse, it's actually more than that. You probably didn't call it a data cloud until later on, but did you know that from the beginning or was that something you kind of stumbled into? >> No. So as I said, we founded Snowflake in 2012 and Thierry and I, we locked in my apartment and we were doing the blueprint of Snowflake and trying to find what is the revolution with the cloud for this data warehouse system and analytical system, both big data and data warehouse. And the aha moment was but of course cloud, okay. What is cloud? It's elasticity, it's service and later collaboration. So in the elasticity aspect, when you ask database people, what is elasticity, they will tell you, oh, you have a cluster of nodes. Like if it is Oracle, it would be a (indistinct) cluster. And the elasticities that you can add one node, two node to this cluster without having too much impact on the existing workload, because you need to shuffle data, right. It's hard and doing it online, right, that's elasticity. If you can do that, you are elastic. We thought that that was not very interesting to do that. What is interesting with elasticity is to plug new workloads. You can plug a workload like that and that workload is running without having any impact on other workloads, which are running on the platform. So elasticity for us was having dedicated computer resources to workloads. And these computer resources could start and be part as soon as the workload starts and will shut down when the workload finishes and they will be sized exactly for the demand of that workload. And we thought the aha moment was, okay if we can do that, now we can run a workload with, let's say 10X more computer resources than what you would have used or 100X more. Okay, let's say 100X more because we paralyzed things. Now this workload can run 100X faster, right? That's assuming we do a good job in the scale, which is our IP. And if we can do that, now the computer resources that you have used, you have used them for 100 times less. So you have used 100 times more resources because you have more nodes, but because you go fast, you use them for less time, right? So if you multiply the two it's constant. So you can run and accelerate workload dramatically 10X, 100X for the same price. Even if we are not better in efficiency than competition, just having that was the magic, right? >> You know how Google founders originally had trouble raising money because who needs another search engine? Did you get from original, like when you started going to raise money, Amazon's got a database, so who needs another cloud database? Did you get that early on or was it just obvious Speiser and companies as well. >> Speiser is a little bit on the crazy side and ambitious and so Speiser is Speiser. And of course he had no doubt, but even him was saying Benoit, Thierry, Hadoop, right. Everyone is saying Hadoop is going to be the revolution. And you guys are betting actually against Hadoop because we told Speiser, Hadoop is a bad system, it's going to fail, but at the time everyone was so bullish about Hadoop, everyone was implementing Hadoop that it didn't look like it was going to fail and we were probably wrong. So there was a lot of skepticism about not leveraging Hadoop and not being an Hadoop. Okay, something being on top of Hadoop. That was number one. There was no cloud warehouse at the time we started. Redshift was not started. It was the pioneer somewhere when Snowflake was founded. So creating a data warehouse in the cloud sounded crazy to people. How am I going to move my data over there? And security and what about security, the cloud is not secure. So that was another... >> So you guys predated that Parexel move by... >> Yes. >> Okay, so that's interesting. And I thought when Redshift... I mean, Amazon announced Redshift, I was sure that Mike Speiser will come and say, guys it's too sad, but they beat you guys and they build something and actually it was the reverse. Mike Speiser was super excited and so it was interesting to me. >> Wow, that's amazing. 'Cause John Furrier and I, we were early with theCUBE. when theCUBE started it was like the beginning of Hadoop. And so we brought theCUBE to, I think it was the second Hadoop World and we was rubbing nickels together at the time. And I was so excited bring compute to storage and it made so much sense. But I remember and I won't say who it was, but an early Hadoop committer told me this is going to fail. And I'm like, what? And he started going age basis crap and all this stuff. And I was sad because I was so excited, but it turned out that you had the same (indistinct). >> Because of complexity. Okay, Hadoop failed for two reasons. One is because they decided that, oh, a lot of this database thing, you don't need transaction, you don't need SQL, you don't necessarily, you don't need to go fast. It'll be batch, normal real time interaction with data, no one needs that. >> Cheap storage. >> So a lot of compromise on the very important technology. And at the same time, extreme complexity and complexity for me was, where I was I knew that it was going to fail big time and we bet Snowflake on the failure of Hadoop indeed. >> And there was no cloud early on in Hadoop. >> And there was no cloud too. >> And that was what killed it. That was like... >> You're right. And the model that Hadoop had for data didn't work on block storage. Block storage is not as efficient as HGFS. So that was also another figure. >> Do you ever sit back and think about... So you think about how much money has poured in to separating compute from storage and cloud databases and you started it all. (interviewer laughing) >> Yeah. No, this is... >> Pretty amazing. >> Yeah. >> Right, so that's good. That means that you're onto a good idea, but a lot of people get confused that again, they think that you're a cloud data warehouse and you're not, I mean, you're much more than that. >> Yeah, I hate that. I have to say, because from day one we were not a cloud data warehouse. As I said, it was all about combining the big data, massive amount of unstructured data, petabytes stored as files. Okay, that's very important, store as files where it's very easy to drop data in the system without... Very low cost to combine with data warehouse, full multi statement transaction when people will tell you today, oh, now we are a data warehouse. They don't have multi statement transaction, right. So we had from day one multi statement transaction really efficient SQL. You could run your dashboard. So combining these two worlds was I think the crazy thing, that's the crazy innovation that Snowflake did initially. >> Yeah. >> And I know it's really easy to build data warehouse somewhere, because if you don't think about big data, petabytes, extremely structured data, you remove a lot of complexity. >> This is why Lisa, when you get excited about technology, but you always have to have a, somebody who really deeply understands technology to stink test it, all right so awesome. Thank you for sharing that story. >> Yeah. >> Fantastic. So over 5,900 customers now. I saw over 500 in the Forbes G2K, over almost 10,000 people here this year. If we think back to 2019, there was about what? Less than 2000 people. >> Yeah. >> What do you think is going to happen next year? >> I don't know. I don't like to think about next year. I mean, I always say, Snowflake is so exciting to me because it is like a TV show, right. Where you wait the next season and we have one season every year. So I'm really excited to know what is going to happen next year. And I don't want to project what I think will happen, but all these movements to the Snowflake being the platform for data application. I want to see what people are going to build on our platform. I mean, that's the excitement. >> Season 11 coming up. >> Yes. Season 11. Yes. >> No binge watching here. Benoit, it's been a pleasure to have you on the program. >> Thank you. >> Congratulations on incredible success, the momentum, the energy is contagious. We love it. (Benoit laughing) >> Thank you so much. >> Thank you. >> Bye bye. >> For Benoit Dageville and Dave Vellante, I'm Lisa Martin. You're watching theCUBE's coverage of Snowflake Summit '22. Dave and I will be right back with a wrap. (upbeat music)

>> Okay listen, we're gearing up for the start of the Snowflake Data Cloud Summit. And we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Munir, Ashish Motivala and Allison Lee. They're three individuals that were at Snowflake, in the early years and participated in many of the technical decisions. That led to the platform and is making Snowflake famous today. Folks great to see you. Thanks so much for taking some time out of your busy schedules. >> Thank you for having us- >> Same. >> It's got to be really gratifying to see this platform that you've built, taking off and changing businesses. So I'm sure it was always smooth sailing, right? There were no debates, where there ever? >> I've never seen an engineer get into a debate. >> Yeah alright, so seriously. So take us back to the early days, you guys choose whoever wants to start, but what was it like, early on we're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake. I just think of all of us sitting in one room at the time, we just had an office that was one room with 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code punctuated by somebody asking a question about hey, what should we do about this? Or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we were doing. >> So, Abdul was it just kind of heads down, headphones on just coding or? >> I think there was a lot of talking and followed by a lot of typing. And I think there were periods of time where anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away their keyboards. And one of my most vivid memory is actually I used to sit right across from Allison and there was these two huge monitors between us. And I would just hear her typing away at her keyboard. And sometimes I was thinking and all that typing got me nervous because it seemed like Allison knew exactly what she needed to do. And I was just still thinking about it. >> So Ashish was this like bliss for you as a developer or an engineer? Or was it a stressful time? What was the mood? >> Then when you don't have a whole lot of customers, there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us. We knew we had to build this in a certain timeframe. So one thing I'll add to what Allison and Abdul said is, we did a lot of whiteboarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune and there we have it. >> Yeah, it is a really exciting time. We can do it any start-up. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided which fork to take. Was there a Yoda in the room that served as the Jedi Master? How are those decisions made? Maybe you could talk about that a little bit. >> That's an interesting question. And as I think back one of the memories that sticks out in my mind is this epic meeting in one of our conference rooms called Northstar and many of our conference rooms are named after ski resorts because the founders are really into skiing. And that's where the Snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was the sign up flow and there were a few different options on the table. And one of the options that people were gravitating to, one of the founders didn't like it. And they said a few times that this makes no sense. There's no other system in the world that does it this way. And I think one of the other founders said, that's exactly why we should do it this way or at least seriously consider this option. So, I think there was always this tendency and this impulse that we needed to think big and think differently and not see the world the way it is, but the way we wanted it to be and then work our way backwards and try to make it happen. >> Allison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our column metadata. And I think it's funny that you that you mentioned Yoda, because we often make jokes about one of our founders Thierry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, wow, why didn't I think of that? Or what exactly does that mean? I never thought about it that way. So, when I think of the Yoda in the room, it was definitely Thierry, >> Ashish is there anything you can add to this conversation? >> I'll agree with Allison on the Yoda comment for sure. Another big fork in the road I recall was when we changed one of our meadow store, where we store and are willing to try and metadata. We used to use a tool called my SQL and we changed it to another database called foundation DV. I think that was a big game changer for us. And it was a tough decision. It took us a long time, for the longest time we even had our own little branch it was called foundation DV and everybody was developing on that branch, it's a little embarrassing but those are the kinds of decisions that have altered the shape of Snowflake. >> Yeah, these are really down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? You kind of maybe mentioned it a little bit before, but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage that is really core to our architecture. And there's so many features that we have today, for instance data sharing, zero-copy cloning, that we couldn't have without that architecture. And I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly- >> Yeah, anything that was like clearly obvious, maybe that was the least and the most that separation from compute and store, 'cause it allowed you to actually take advantage of cloud native, but was there an obvious one that is it sort of dogma that you philosophically live behind to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious the implications of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake that led to a lot of non-obvious decisions as a result of sticking to that principle. >> To wrap to that now you've gotten us thinking, I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that. And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were because they weren't built for the platforms that they were running on. And the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were going to build it from scratch and we weren't going to borrow a single line of code from any other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy. And it was, but this is how you build great products. >> That's awesome, all right, Ashish give your last word, we got like just 30 seconds left take, bring us home. >> Till date actually one of those that shocks people when you talk to them and they say, wow, you're not really using any other database? And you build this entirely yourself? The number of people who actually can build a database from scratch are fairly limited. The group is fairly small. And so it was really a humongous task. And as you've mentioned, it really changed the direction of how we designed the database. What does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks Dave. >> Thank you- >> Thank you.

>> Narrator: From theCUBE Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Hi everyone, this is Dave Vellante at theCUBE, and we're getting ready for the Snowflake Data Cloud Summit. four geographies, eight tracks, more than 40 sessions for this global event. starts on November 17th, where we're tracking the rise of the data cloud. You're going to hear a lot about that. Now, by now, you know the story of Snowflake or, you know what? Maybe you don't. But a new type of cloud-native database was introduced in the middle part of the last decade. And a new set of analytics workloads has emerged, that is powering a transformation within the organizations. And it's doing this by putting data at the core of businesses and organizations. For years, we marched to the cadence of Moore's law. That was the innovation engine of our industry, but now that's changed. It's data, plus machine intelligence, plus cloud. That's the new innovation cocktail for the technology industry and industries overall. And in the Data Cloud Summit, we'll hear from Snowflake executives, founders, technologists, customers, and ecosystems partners. And of course, you're going to hear from interviews on theCUBE. So let's dig in a little bit more. And to help me are two Snowflake experts. Felipe Hoffa is a data cloud advocate and Kent Graziano is a chief technical evangelist, both at Snowflake. Gents, great to see you, thanks for coming on. >> Thanks for having us on, this is great. >> Thank you. >> So guys, first, I got to congratulate you on getting to this point. You've achieved beyond escape velocity and obviously one of the most important IPOs of the year, but you got a lot of work to do and I know that. Felipe, let me start with you. Data cloud, what's a data cloud and what are we going to learn about it at the Data Cloud Summit? >> Oh, that's an excellent question. And, let me tell you a little bit about our story here. And I really, really, really admire what Kent has done. I joined Snowflake like less than two months ago and for me, it's been a huge learning experience. And I look up to Kent a lot on how we deliver the method here, how do we deliver all of that? So, I would love to hear his answer first. >> Dave: Okay, that's cool. Okay Kent, leader on. (Kent laughing) So we took it. Data cloud, that's a catchy phrase, right? But it vectors into at least two of the components of my innovation cocktail. What are the substantive aspects behind the data cloud? >> I mean, it's a new concept, right? We've been talking about infrastructure clouds and SaaS applications living in the application cloud, so data cloud is the ability to really share all that data that we've been collecting. We've spent what? How many da-- A decade or more with big data now, but have we been able to use it effectively? And that's really where the data cloud is coming in and Snowflake, in making that a more seamless, friendly, easy experience to get access to the data. I've been in data warehousing for nearly 30 years now. And our dream has always been to be able to augment an organization's analytics with data from outside their organization. And that's just been a massive pain in the neck with having to move files around and replicate the data and maybe losing track of where it came from or where it went. And the data cloud is really giving our customers the ability to do that in a much more governed way, a much more seamless way, and really make it push button to give anyone access to the data they need and have the performance to do the analytics in near real-time. It's a total game changer as you already know. And just, it's crazy what we're able to do today compared to what we could do when I started out in my career. >> Well, I'm going to come back to that 'cause I want to tap your historical perspective. But Felipe, let me ask you, so why did you join Snowflake? You're the newbie here, what attracted you? >> And finally, I'm the newbie. I used to work at Google until August. I was there for 10 years, I was a developer advocate there also for data, you might have heard about the BigQuery, I was doing a lot of that. And though as time went by, Snowflake started showing up more and more in my feeds, within my customers, in my community. And it came the time when I felt like-- Wherever you're working, once in a while you think, "I should leave this place, "I should try something new, "I should move my career forward." While at Google, I thought that so many times as anyone will do. And it was only when Snowflake showed up, like where Snowflake is going now, how Snowflake is being received by all the customers, that I saw this opportunity. And I decided that moving to Snowflake would be a step forward for me. And so far I'm pretty happy, like the timing has been incredible, but more than the timing and everything, it's really, really a great place for data. What I love first is data, sharing data, analyzing data and how Snowflake is doing it, its promising phenomena. >> So, Kent, I want to come back to you and I said, tap maybe your historical perspective here. And you said, it's always been a dream that you could do these other things, bring in external data. I would say this, that I would want to push a little bit on this because I have often said that the EDW marketplace really never lived up to its promises of 360 degree views of the customer, in real-time or near real-time analytics. And it really has been, as you kind of described it, a real challenge for a lot of organizations. When Hadoop came in, we had-- We got excited that it was going to actually finally live up to that vision and Hadoop did a lot. And don't get me wrong, I mean, the whole concept of, bring the computer data and lowering the cost and so forth. But it certainly didn't minimize complexity. And it seems like, feels like Snowflake is on the cusp of actually delivering on that promise that we've been talking about for 30 years. I wonder if you could share your perspective as an o-- Are we going to get there this time? >> Yeah. And as far as I can tell working with all of our customers, some of them are there. I mean, they thought through those struggles that you were talking about, that I saw throughout my career. And now with getting on Snowflake they're delivering customer 360, they're integrating weblogs and IOT data with structured data from their ERP systems or CRM systems, their supply chain systems and it really is coming to fruition. I mean, the industry leaders, Bill Inmon and Claudia Imhoff, they've had this vision the whole time, but the technology just wasn't able to support it and the cloud, as we said about the internet, changed everything. And then Benoit and Thierry in their vision in building the system, taking the best concepts from the Hadoop world and the data lake world and the enterprise data warehouse world, and putting it all together into this architecture, that's now Snowflake and the data cloud, solved it. I mean, it's-- The classic benefit of hindsight is 20/20, after years in the industry, they had seen these problems and said like, "How can we solve them? "Does the cloud let us solve these problems?" And the answer was, yes, but it did require writing everything from scratch and starting over with, because the architecture of the cloud just allows you to do things that you just couldn't do before. >> Yeah, I'm glad you brought up some of the originators of the data warehouse, because it really wasn't their fault, they were trying to solve a problem. It was the marketers that took it and really kind of made promises that they couldn't keep. But, the reality is when you talk to customers in the sort of the old EDW days, and this is the other thing I want to tap you guys' brains on, it was very challenging. I mean, and one customer one time referred to it as a snake swallowing a basketball. And what he meant by that is, every time there's a change, or Sarbanes-Oxley comes and we have to ingest all this new data. It's like aargh! It's just everything slows down to a grinding halt. Every time Intel came out with a new microprocessor they would go out and grab a new server as fast as they possibly could, he called it chasing the chips. And it was this endless cycle of pain. And so, the originators of the data warehouse, they didn't have the compute power, they didn't have the cloud. And so-- And of course they didn't have like 30, 40 years of pain to draw upon. But I wonder if you could maybe talk a little bit about the kinds of things that can be done now that we haven't been able to do here tofore. >> Well, yeah. I remember early on having a conversation with Bill about this idea of near real-time data warehousing and saying, "Is this real? "Is this something really people need?" And at the time, it was a couple of decades ago, he said, "No, to them, they just want to load their data "sooner than once a month." That was the goal. And they-- That was going to be near real-time for them. And, but now I'm seeing it with our customers. It's like, now we can do it. With things like the Kafka technology and Snowpipe in Snowflake, that people are able to get that refresh way faster and have near real-time analytics access to that data in a much more timely manner. And so it really is coming true. And the compute power that's there, as you said, we've now got this compute power in the cloud that we never dreamed of. I mean, you would think of only certain, very large, massive global companies or governments could afford supercomputers. And that's what it would have taken. And now we've got nearly the power of a super computer in our mobile device that we all carry around with us. So being able to harness all of that now in the cloud, is really opening up opportunities to do things with data and access data in a way that, again, really, we just kind of dreamed of before. Its like, we can democratize data when we get to this point. And I think that's where we are, we're at that inflection point, where now it's possible to do it. So the challenge on organizations is going to be how do we do it effectively? How do we do it with agility? And how do we do it in a governed manner? You mentioned Sarbanes-Oxley, GDPR, CCPA, all of those are out there. And so we have all of that as well. And so that's where we're going to get into it, ride us into the governance and being able to do that in a very quick, flexible, extensible manner. And Snowflakes really letting people do it now. >> Well, yeah. And again, we've been talking about Hadoop, and again, for all my fond thoughts of that era, and it's not like Hadoop is gone, but there was a lot of excitement around it, but governance was a huge problem. And it was kind of a bolt on. And now, Felipe I got to ask you, when you think about a company like Google, your former employer, data is at the core of their business. And so many companies, the data is not at the core of their business, something else is, it's a process or a manufacturing facility or whatever it is. And the data is sort of on the outskirts. We often talk about in stovepipes. And so we're now seeing organizations really, put data at the core of their... And it becomes central to their DNA. I'm curious as to your thoughts on that. And also, if you've got a lot of experience with developers, is there a developer angle here in this new data world? >> Oh, for sure. I mean, I love seeing every-- Like throughout my career at Google and my two months here, I'm talking to so many companies, that you never thought before, like these are database companies. But the ones that keep growing, the ones that keep moving to the next stage of their development is because they are focusing on data, they are adopting the processes, They are learning from it. And, me per-- I focus a lot on developers, so I mean, when I started this career as an advocate, first, I was a software engineer. And my work so far, has been... (mumbles) I really love talking to the engineers on the other companies, like... Maybe I'm not the one solving the business problem, but at the end of the day, when these companies have a business problem through out the world, they want to have data. There are other engineers that are scientists like me that are... That want to work for the company and bring the best technology to solve the problems. Yeah, for example, there's so much where data can help. If, as we evolve the systems for the company and also for us for understanding these systems, things like observability. And recently, there was a big company, a big launch on observability, on the company names of Cyberroam, where they are running all of their data warehousing needs and all of their data needs on Snowflake. Just because running these massive systems and being able to see how they're working, generates a lot of data. And then how do you manage it? How do you analyze it? Snowflake is ready there to help and support the two areas. >> It's interesting, my business partner, John Furrier, co-host of theCUBE, he said, gosh, I would say the middle of the last decade, maybe even around the time, 2013, when Snowflake was just coming out. He said... He predicted that data would be the new development kit. And, it's really at the center of a lot of the data life cycle, the-- What I call the data pipelines, I know people use that term differently. But, I'm very excited about the Data Cloud Summit and what we're going to learn there. And I get to interview a lot of really cool people. And so I appreciate you guys coming on. But Kent, who should attend the Data Cloud Summit? I mean, what are the-- What should they expect to learn? >> Well, as you said earlier Dave, there's so many tracks and there's really kind of something for everyone. So we've got a track on unlocking the value of the data cloud, which is really going to speak to the business leaders, as to what that vision is, what can we do from an organizational perspective with the data cloud to get them value from the data to move our businesses forward? But we've also got for the technicians, migrating to Snowflake. Training sessions on how to do the migration and modernizing your data lake, data science. How to do analytics with, and data science in Snowflake and in the data cloud. And even down to building apps, for the developers and building data products. So, we've got stuff for developers, we've got stuff for data scientists, we've got stuff for the data architects like myself and the data engineers, on how to build all of this out. And then there's going to be some industry solutions spotlights as well. So we can talk about different verticals, folks in FinTech and in healthcare, there's going to be stuff for them. And then for our data superheroes, we have a hallway track where we're going to get talks from the folks that are in our data superheroes, which is really our community advocacy program. So these are folks that are out there in the trenches using Snowflake, delivering value at their organizations. And they're going to talk down and dirty of how did they make this stuff happen? So there's going to be just really, something for everyone. Fireside chats with our executives, of course, something I'm really looking forward to myself. It's always fun to hear from Frank and Christian and Benoit, about what's the next big thing, what are we doing now? Where are we going with all of this? And then there is going to be some awards. We'll be giving out our Data Driver Awards for our most innovative customers. So there's going to be a lot for everybody to consume and enjoy and learn about this new space of the data cloud. >> Well, thank you for that Kent and I'll second that, and there's going to be a lot for everybody. If you're an existing Snowflake customer, there's going to be plenty of two of one content, where we can get in to the how tos and the best practice. If you're really not that familiar with Snowflake or you're not a customer, there's a lot of one-on-one content going on. If you're an investor and you want to figure out, "Okay, what is this vision? "And can, will this company grow into its massive valuation? "And how are they going to do that?" I think you're going to hear about the data cloud and really try to get a perspective and you can make your own judgment as to whether or not you think that it's going to be as large a market as many people think. So Felipe, I'd love to hear from you what people can expect at the Data Cloud Summit. >> Totally. So I would love to plus one to every one that Kent said, we have a phenomenal schedule that day, the executives will be there. But I really wanted to especially highlight the session I'm preparing with Trevor Noah. I'm sure you must have heard of him. And we are having him at the Data Cloud Summit, and we are going to have a session. We are going to talk about data. We are preparing a session that's all about how people that love data, that people that want to make that actionable, how can they bring storytelling and make it have more impact as he has well learned to do through his life. >> That's awesome. So, yeah, Trevor Noah, we're not just going to totally geek out here. We're going to have some great entertainment as well. So I want you to go to snowflake.com and click on Data Cloud Summit 2020. There's four geos. It starts on November 17th and then runs through the week and then the following week in Japan. So, check that out, we'll see you there. This is Dave Vellante for theCUBE. Thanks for watching. (upbeat music)

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Everybody, welcome to this CUBE conversation. I'm John Furrier, host of theCUBE here in Palo Alto, California in our studios where we have a quarantine crew and we're doing remote interviews with thought leaders in the industry and people who have been around the block, beat it through three industry cycles but also can share their perspectives on the COVID-19 situation that we're in, the challenges and the opportunities. And I have with me, Jeremy Burton, a good friend of theCUBE. Have been a CUBE alumni now for 10 years, now the CEO of Observe, it's a stealth startup. I got a little taste of it, it's a Cloud thing. It's going to be part of this whole new guard. Jeremy, great to see you. You're sheltering in place, we're sheltering in the studio. Thanks for joining me. >> No, thanks for the offer. I mean, it's funny these days I welcome chance to actually speak to somebody and particularly, somebody that's not at Observe. So this is a rare treat in the last three weeks. >> Telling the wife and kids, "Hey, I'm going to go talk to theCUBE guy." So you know, I'm going to have some fun for a while. Look, I want to just have a candid fun conversation 'cause I think one of the things that's interesting to me in one, things that we're spending a lot of time doing media on is getting the word out about some of the things that are going on. People do have anxiety, they're sheltering in place for the folks that've been in the tech industry, working at home and being virtual has been part of the thing. It's not a big thing but from some of the people it's like a first time thing. And also it's also highlighting a disruption that kind of is off the books if you will, the classic continuous operations and disaster recovery was also confined to power outages or hurricanes or all those things that we people are protected against. But this is just a surge of the herd of the people going home. It's causing an at scale problem and showing these challenges, but there's also opportunities. What's your take on this? How do you see this evolving? What's your view of the current situation and some of the comments? >> Yeah, I think for most of us we're in a little bit unchartered territory. I don't really know a whole lot about medicine or the details of the virus or how pandemics happen. But we obviously have to, we deal with the consequences of it. And so I think right now although, I think it's a fairly bad situation for a lot of people, just having been through a couple of recessions where we all went through 9/11. The world does turn around and you come out the other side. And so the key thing is you start like a very much as a cliche, but you've got to live in the moment, "What can I do right now? "What can I affect right now? "How can I make sure that what I'm working on "is a value for when we come out the other side "and when more curveballs come along?" I think you've got a reason about that with the best information you have at the time. So I almost feel like you very much, you've got to just live solid like day to day, week to week, listen to the data and adapt based on that. But it's certainly starting to reinvent how work is done. I think we've all worked from home at some point. We've all worked using our equipment at home. But the prospect of working that way for months on end and it maybe been the new way of working, is a whole new ballgame. So I'm a big believer that this will fundamentally change the way we work. I don't think we're going to go 100% back to the way that we were, and there's going to be quite a lot of readjustments, and I think in that world, there's going to be some new companies come along that are big winners. And by definition, there's going to be some big losers as well. >> Well, people who know theCUBE know that I'm a big fan of you as an executive. I've seen the vision, you have also great technical shops and product shops, but also a good operational view. You've always been a fan of digital. And I think if you look at video conferencing, for instance, WebEx as a Cisco thing, great bulletproof of the enterprise, but Zoom has come across the scene. I've never seen so many Zoom parties. I did one with my family that they actually liked it. They were having fun. We had cocktails raising the wineglasses up. So people are Zooming their CUBE in, we're doing interviews. So video now is not just a corporate thing. You're seeing the engagement of digital taking on a new life and this is a whole new roles and responsibilities that we might reimagine how people do their business because with the events being canceled that are going on, whether they're concerts or just industry or tech events or any event, that physical space is gone, now it's going to digital. So how do you replicate the business value or personal value from physical face to face to digital? It's a whole new venue, there's new roles. It's complicated, it's a complex system. What's your thought on that? >> It is though, but what I have been pleasantly surprised by, I'd love it going in the office. I love the engagement with people and hanging out in the office. And so I was not really a big fan of remote working and virtually working, but I have to say, not only now where we virtually work in and we do the Zoom meetings and that's all well and good. It's a big cultural thing with at Observe to do a game night. And so we thought, "Well, why can't we do a virtual game night "and lending some trade secrets here? "But our favorite game was Secret Hitler." >> Yeah, that's a great game. One of my family's favorite. >> Turns out there's an online Secret Hitler. And you know what? The first time we played it, one of the nice thing is we've got less than 20 people in the company. So you got 12 or 14 people online. It's actually manageable. But I have to say, I'm almost embarrassed to say, it was almost as good sitting there with a drink playing virtual Secret Hitler as it was sitting around the desk. And so now I'm thinking when we go back to work, maybe we don't need to leave our desks and go have a drink together. We can just sit there on Zoom and play the secret Hitler online. Then you start looking around, "Well, what are the games can I play online?" Not like for one or two players or five players and I'm not talking about playing kind of Halo or something like that, but good collaborative games for tens of people to play at once. There's not as many as you think. So I feel like the social aspect of it, I mean, online gaming I think is huge. But even the video conferencing software, you would have thought that we would be done WebEx by now, right? I mean Skype and WebEx, we've had those for years, right? And so how does Zoom, which does guess what, video conferencing come along and start to clear up. And Zoom is not perfect by the way, but this is almost the crisis that they needed to make a fabulous business. I do believe as we start to come out the other side, I think there's going to be much, much investment in the VC world, on improving that remote work experience Because as much as me and you can talk to a video session, we can't collaborate and work together. The tools for doing that, I think still are relatively poor. >> I think you're onto something. Zoom by the way, had 10 million active dailies in December. This month was 200 million rocket ship. They got 90,000 universities. They essentially made some good moves. I think that's going to be good, but you bring up a good point about these new kinds of opportunities that are going to come out the other side, which is, think about Secret Hitler. For the folks who don't know, is a great game that you play with people, in your family or in friend group like Cards Against Me. And if you know that game, it's a similar thing concept, but you have different games. It's really fun, you should get it. Check it out online. But think about that online gaming or just what engagement means socially. I mean the old web days or just like a couple of months ago was individual engagement, "Did you like my tweet? "Did you like my Facebook post?" You're getting at something that's little bit more of a social organizational construct of group engagement, intimacy. >> Right, and the thing is we would do game night once a month and we'd get videos in and get the teamed together. Once a month was good when everybody had their own life to deal with. Now people are craving like, "Hey can we do this like every week?" And I wouldn't be surprised if the frequency increases from that, but I think that just almost speaks to human beings and that we crave social interaction. And even though most of the people at Observe are engineers and by definition should not enjoy as much social interaction, they do. They love it, right? And to me, that gaming and social direction, that's part of work. And so you have to have a virtual environment that can reproduce that. >> I mean, it's very interesting to see some of the entrepreneurial exercises or pitches that come out of this because I think it's going to be a Renaissance, it's not Renaissance 'cause it's going to come back. It's always been there. But the new kind of entrepreneurial products coming out are going to address these things. And the question I want to ask you, 'cause you've been on the big company, you've done extremely well in your career, than you get back down to your roots to doing startup, you're launching, you haven't yet launched. So you got hit right here, you're working at home sheltering in place. I was talking to a couple of VC buddies, venture capitalists, and they're saying, "I'm reading books and I'm doing research "but I really can't meet people." So their work has changed. How do you see the investment community reacting to this? Certainly valuations might come down. Obviously, their limited partners are being hit with the stock market. You're seeing a disruption. What do you see going on in the VC world around this cold hard time? >> I mean certainly all VCs are not created equal. So I think there's going to be different perspectives based on the background of the DNA of the VC involved. I think certainly at Observe, I feel very fortunate that we've got a sort of Hill Ventures. So these guys were the investors behind Snowflake and behind Pure Storage and many other good companies but they're very longterm investors and their advice to me has been, "Well look, "some of the most innovative times if you like, "have been during and after a major crisis. "And so if you make short term decisions "to get you through those crisis, "they're all terrible but they don't last forever "and there will be another side. "And so make good business decisions "and good investment decisions through this "because there will be winners "that emerge on the other side." And that's really what I try and get the team focused on is, "Guys for now, we're sort of hunkered down "and it feels bad, "but we're probably more privileged than most. "And we have an opportunity maybe on the other side, "to take advantage, we don't have a revenue stream, "we don't have existing customers. "We can sort of take this Greenfield business "that we've got and you go on the offensive "when things returned to assemblance of normal." So The Hill had been fantastic. And I would hope that most VCs retain that perspective, which is if it was a good company three weeks ago, it's probably still a good company today. And the best way to create value is to sort of empower I think the CEOs and executive teams to make the right sort of longer term decisions. Try and capitalize when you come out the other side because there will be losers as well. And I think the wrong decisions now can put you on the losing end of that equation in three, four, five months time. >> Yeah, that's a good point. If you are a good company just a few months ago or even weeks ago or a year ago, you're still a good company. That's really going to be a tell sign to what happens in some of these companies. If I got to ask you a more focused question on this whole, which side of the street are you on? Are you riding the wave or are you going to get taken away and washed away with it? Because there are bets and well, I want to get into Observe in a minute, but you mentioned Snowflake there in the Cloud wave. Obviously, that's pretty bullish. We're still bullish on that. Obviously, it's going to be game changer. But is there a tell sign for the kind of bets that those good management teams need to make now? Because I agree with you, when the Dot-com bubble burst in 2000 and really 2004 kicked back up again. 2008, we saw that post and a lot of great companies were created. So what's your advice on which side of history do you need to be on here? I'll say Cloud is one. What is your view on that? >> Yeah, I mean we felt for many years, it's not just since I went to the startup, but I am a huge believer in this transition to digital businesses. Frictionless interactions, automation, yes, obviously people are required to run a business, but if you could run a business remotely, or the businesses automated in a way such that it doesn't require hands-on operation, then that's a beautiful thing. And my belief is that, this terrible situation will force people to really think seriously about what the digital business looks like. If you don't have one, then that you may not be able to be in business in a year, two, three years down the line, right? There'll be some carryover, but I think the smart businesses are going to be able to function in an environment such as this. >> Yeah, I think that's great. >> That's going to be playing on everybody's minds. Now more than ever, I think that the digital business is a necessity. >> Yeah, I was just talking to a colleague and we were just talking about how all of the events got canceled and you've had the history running some of those best events ever in the industry at EMC. And we participated in those and you know your staff when it comes to events, there's economic value in these physical events as a venue, Science Convention Center in Moscone here in San Francisco. I mean there's a lot of things that go on, a lot of decision-making that's been standardized over the years and there's an economic value that comes out of those events. Now that's gone, and then these little digital teams, some companies have like five people, two people, sometimes maybe if you're lucky you have 10 or more or a department. And then you've got demand generation. All these guys are being told now, "You have to make up for the shortfall "in not just leads but value." And this just has been a big burden for some of my friends out there who are like, "Wait a minute, you want to take that and move it over here?" It's been kind of a challenge. What is your view on this? Because a lot of people are trying to figure this particular problem out on how to make digital work today and have some extensibility and get success. What's your take? >> Well, I'm still a huge believer I mean, whereas sort of like we just saw digital marketing content is still very much King, right? If you can produce a compelling piece of content online, TV quality with a depth of knowledge that you're going to attract an audience, now can you then make that experience interactive? Can you engage the audience in a deeper way? Yeah, you're probably not going to have something which lasts for a full day or for three days online, but I think it's really going to force the creativity on the content side to another level, right? It can't just be talking heads and PowerPoint pictures. So that rethinking from first principles, what an online conference or an online experience actually looks like in a way that it engages the people who are watching. To me, those folks are going to go do very, very well. And the economics, I know how much it costs to put on a conference for 10 or 15,000 people. And by the way, I know how much it costs to put on a virtual event for 10 or 15,000 people. And the economics are astounding in that difference. Now if you're physically somewhere, you can feel things that you can't feel online. Come on though, this is a problem that requires some innovation to solve, right? We've talked about virtual reality and augmented reality, but it's still pretty clunky and relegated to sort of niche use cases and bad games. But at some point, that technology has to reach the point where it can be useful and engage in a new. You can approximate to that physical experience. But I think that is going to be critical but many businesses even beyond sort of marketing and virtual events and that kind of thing, many businesses are just going to have to reinvent how they engage and interact with their customers and the automation of their operations and how do you get by when you don't have as many people physically in an office or operating machines? Everybody's going to have to think through that. >> Yeah, I think that's great insight and that's going to be a great clip that I'll share and I think that's going to be inspirational for the folks trying to solve that problem. The things that we're focused in on, as you know, and this is something that we're doing a lot of work on, is the engagement with groups and you mentioned The Secret Hitler as the game, they're going to see some new clever things go on. And I think the group dynamic and having people in whether it's virtual and physical spaces exchanging credible things, ideas or jokes or whatever is going to be a new kind of dynamic. >> Yeah. >> Because that's going to have to fill the void. >> Yeah, I mean I've got a small company so we can play these individual games, but just think about some of these board type games where I want to have three teams and I want to divide the company up into three. The logistics of actually figuring that out is ridiculous and it shouldn't be that way, right? And so these are basics of human social interactions. We want to play a game together, we want to divide up into teams. But that sounds like a relatively trivial thing, but try and find the number of games available that allow you to easily do that and each team interaction independently of the others, it's almost impossible. >> It's going to be fun to watch and I think and I hope we're going to learn. Well, thanks for the device. Let's get back to your startup. Let's get a plug in for that, I want to get the plug in. I've seen you in stealth so you can't really go into great detail, but you have been talking to customers. You are obviously related, that's related to Snowflake, but you were going to do some things with Snowflake. You're in the Cloud. Can you just take a minute to give a plug for what you guys are doing for the people who want to know what you guys are leaning towards in terms of the value proposition? >> Yeah well, when I look back in my career, one of the times I enjoyed the most was the time at Oracle and working with data. And I've been fortunate enough for the last four and a half years or so to be on the board of Snowflake. Couple of ex Oracle guys, Benoit and Thierry founded the company and they've reinvented the database. And I felt like I've sat for 20 years looking for the second coming of the database and we all were sort of had fake thinking it was Hadoop. And turns out it wasn't. But I think Snowflake and the separation of storage and compute that allows them to sort of scale and have a usage-based pricing model, I just think is absolutely revolutionary and I think it's going to be one of the great companies of the new era. And so when I was there when I looked at Observe, really the thesis was that using a platform like Snowflake, you could potentially reason about unstructured log data. It's all like Splunk. You could reason about time series data, a little bit like Datadog or tracing data like AppDynamics or in fact any data, you could reason about it together. And today, if you look at the world, it's like if you want to do something with logs, you go get one product. If you want to do something with relational data, you get another, if you want to do time series data, you get another, you want to do tracing, you get an APM tool. And nobody has the big picture, right? Everybody's got their own little piece of data and their own perspective on where the issue might be in your company. But nobody really knows and it's usually put together in the brain of, of the smartest guy in the room. And so I thought it was quite simple. At Snowflake, you've got this commercial database that can do instruction data and time series data and relational data. And what if we could collect all data within an organization together, structure it, relate it, and then imagine what you could find out about your infrastructure, your applications, your business? >> Sort of unification? Does it have like unification kind of concept for users or IT? >> Yeah, I think the emerging category would be observability but it really is a collapsing of log analytics, metrics monitoring and tracing into this new category of observability. We don't necessarily just view that though as sort of data coming out of Kubernetes clusters or out of AWS or wherever. We actually could ingest security data. We could ingest data from people surfing using your app or surfing your website. We could take logs coming out of machines on a factory floor. So the way we built the product, it can be literally any kind of data. And we try and structure it and relate it and make sense of it and then make it very easy for people to navigate through it and determine issues and problems. So yeah, we're pretty excited about it. And like I said, we could not have built this even a couple of years ago because I don't think Snowflake would have been there. And in fact, that was one of the big risks when we started the company. Can we build it on Snowflake? And so here we are two years later and we think we can. Well, we're sure we can do it. >> Yeah, they've had a good run too. I mean, look at the growth of Snowflake. >> Yeah, it's crazy. I've never seen anything like it and in the last 20 years and B2B, I've never seen anything like it. So just like I felt in the mid 90s when I was at Oracle, people were making decisions to go with Oracle and then saying, "Hey, help me get all of my other data in that, "my mainframe data, my this, my that." I think Snowflake are going to go through the same sort of growth phase and hopefully with Observe, we can be like, "Hey, if you want to put "your unstructured data or time series data, "we can help you do that very easily." >> Well, this is exactly the current wave that you want to be on the right side of because like you said, just a year or so ago or a couple of years ago, it wasn't available. This is kind of the new capabilities. >> Yeah, I feel like there's going to be a lot of businesses, grow ridiculously. You talked about the Zoom numbers. These are ridiculous growth numbers and there are going to be companies come out the other side that take advantage of the new environment. And as they're growing, as they're scaling, as they build these new microservice-based applications, they're going to run into issues and we hope at least that it's products with our kind of architecture, that's going to be able to help these fast-growing businesses. So yeah, as I said, we're somewhat fortunate in that we don't have a product yet, but certainly on the other side of this, we think there's going to be plenty of opportunity to help a few folks. >> We know you got to do a launch and we're looking forward to hearing more and getting the briefing, and looking forward to hearing more about it when you go public. And yeah, thanks for coming on and taking the time today. I know you got your daughter's birthday party there and you're going to have some celebration. Thank you for sharing the insights on your vision of digital. I thought that was very compelling and great to see you and stay safe. >> Great to see you. Yeah, my 18-year-old, it's got a birthday party and she like always would worry, "What if no one shows up?" Well, today she knows no one's going to show up. >> Except for her family, yeah. >> It's going to be down in the family, yeah. So thanks for that and you guys stay safe and been great the last 10 years knowing theCUBE been that long but hopefully, here is the next 10 years after this current situation is over. >> Yeah, looking forward to it, it's going to be a lot of fun rye and get the content out there. And again, thanks for coming on during this important time and sharing your insights and also just making some entertainment here. We're getting some conversations so people can fill the void and play some games and have some fun. Jeremy, thanks. Great to see you. Jeremy Burton, senior executive in the industry. I've known him for years, been a CUBE alumni since theCUBE was formed. Now the CEO of Observe, sharing his insights on the industry but more importantly, how to be successful, how to come out the other side. Don't be too optimistic. Be focused on today and get through it. That's his advice. Of course, we're theCUBE bringing you all the data as we can now with remote interviews during this time. Thanks for watching, I'm John furrier. (soft music)

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Everybody, welcome to this CUBE conversation. I'm John Furrier, host of theCUBE here in Palo Alto, California in our studios where we have a quarantine crew and we're doing remote interviews with thought leaders in the industry and people who have been around the block, beat it through three industry cycles but also can share their perspectives on the COVID-19 situation that we're in, the challenges and the opportunities. And I have with me, Jeremy Burton, a good friend of theCUBE. Have been a CUBE alumni now for 10 years, now the CEO of Observe, it's a stealth startup. I got a little taste of it, it's a Cloud thing. It's going to be part of this whole new guard. Jeremy, great to see you. You're sheltering in place, we're sheltering in the studio. Thanks for joining me. >> No, thanks for the offer. I mean, it's funny these days I welcome chance to actually speak to somebody and particularly, somebody that's not at Observe. So this is a rare treat in the last three weeks. >> Telling the wife and kids, "Hey, I'm going to go talk to theCUBE guy." So you know, I'm going to have some fun for a while. Look, I want to just have a candid fun conversation 'cause I think one of the things that's interesting to me in one, things that we're spending a lot of time doing media on is getting the word out about some of the things that are going on. People do have anxiety, they're sheltering in place for the folks that've been in the tech industry, working at home and being virtual has been part of the thing. It's not a big thing but from some of the people it's like a first time thing. And also it's also highlighting a disruption that kind of is off the books if you will, the classic continuous operations and disaster recovery was also confined to power outages or hurricanes or all those things that we people are protected against. But this is just a surge of the herd of the people going home. It's causing an at scale problem and showing these challenges, but there's also opportunities. What's your take on this? How do you see this evolving? What's your view of the current situation and some of the comments? >> Yeah, I think for most of us we're in a little bit unchartered territory. I don't really know a whole lot about medicine or the details of the virus or how pandemics happen. But we obviously have to, we deal with the consequences of it. And so I think right now although, I think it's a fairly bad situation for a lot of people, just having been through a couple of recessions where we all went through 9/11. The world does turn around and you come out the other side. And so the key thing is you start like a very much as a cliche, but you've got to live in the moment, "What can I do right now? "What can I affect right now? "How can I make sure that what I'm working on "is a value for when we come out the other side "and when more curveballs come along?" I think you've got a reason about that with the best information you have at the time. So I almost feel like you very much, you've got to just live solid like day to day, week to week, listen to the data and adapt based on that. But it's certainly starting to reinvent how work is done. I think we've all worked from home at some point. We've all worked using our equipment at home. But the prospect of working that way for months on end and it maybe been the new way of working, is a whole new ballgame. So I'm a big believer that this will fundamentally change the way we work. I don't think we're going to go 100% back to the way that we were, and there's going to be quite a lot of readjustments, and I think in that world, there's going to be some new companies come along that are big winners. And by definition, there's going to be some big losers as well. >> Well, people who know theCUBE know that I'm a big fan of you as an executive. I've seen the vision, you have also great technical shops and product shops, but also a good operational view. You've always been a fan of digital. And I think if you look at video conferencing, for instance, WebEx as a Cisco thing, great bulletproof of the enterprise, but Zoom has come across the scene. I've never seen so many Zoom parties. I did one with my family that they actually liked it. They were having fun. We had cocktails raising the wineglasses up. So people are Zooming their CUBE in, we're doing interviews. So video now is not just a corporate thing. You're seeing the engagement of digital taking on a new life and this is a whole new roles and responsibilities that we might reimagine how people do their business because with the events being canceled that are going on, whether they're concerts or just industry or tech events or any event, that physical space is gone, now it's going to digital. So how do you replicate the business value or personal value from physical face to face to digital? It's a whole new venue, there's new roles. It's complicated, it's a complex system. What's your thought on that? >> It is though, but what I have been pleasantly surprised by, I'd love it going in the office. I love the engagement with people and hanging out in the office. And so I was not really a big fan of remote working and virtually working, but I have to say, not only now where we virtually work in and we do the Zoom meetings and that's all well and good. It's a big cultural thing with at Observe to do a game night. And so we thought, "Well, why can't we do a virtual game night "and lending some trade secrets here? "But our favorite game was Secret Hitler." >> Yeah, that's a great game. One of my family's favorite. >> Turns out there's an online Secret Hitler. And you know what? The first time we played it, one of the nice thing is we've got less than 20 people in the company. So you got 12 or 14 people online. It's actually manageable. But I have to say, I'm almost embarrassed to say, it was almost as good sitting there with a drink playing virtual Secret Hitler as it was sitting around the desk. And so now I'm thinking when we go back to work, maybe we don't need to leave our desks and go have a drink together. We can just sit there on Zoom and play the secret Hitler online. Then you start looking around, "Well, what are the games can I play online?" Not like for one or two players or five players and I'm not talking about playing kind of Halo or something like that, but good collaborative games for tens of people to play at once. There's not as many as you think. So I feel like the social aspect of it, I mean, online gaming I think is huge. But even the video conferencing software, you would have thought that we would be done WebEx by now, right? I mean Skype and WebEx, we've had those for years, right? And so how does Zoom, which does guess what, video conferencing come along and start to clear up. And Zoom is not perfect by the way, but this is almost the crisis that they needed to make a fabulous business. I do believe as we start to come out the other side, I think there's going to be much, much investment in the VC world, on improving that remote work experience Because as much as me and you can talk to a video session, we can't collaborate and work together. The tools for doing that, I think still are relatively poor. >> I think you're onto something. Zoom by the way, had 10 million active dailies in December. This month was 200 million rocket ship. They got 90,000 universities. They essentially made some good moves. I think that's going to be good, but you bring up a good point about these new kinds of opportunities that are going to come out the other side, which is, think about Secret Hitler. For the folks who don't know, is a great game that you play with people, in your family or in friend group like Cards Against Me. And if you know that game, it's a similar thing concept, but you have different games. It's really fun, you should get it. Check it out online. But think about that online gaming or just what engagement means socially. I mean the old web days or just like a couple of months ago was individual engagement, "Did you like my tweet? "Did you like my Facebook post?" You're getting at something that's little bit more of a social organizational construct of group engagement, intimacy. >> Right, and the thing is we would do game night once a month and we'd get videos in and get the teamed together. Once a month was good when everybody had their own life to deal with. Now people are craving like, "Hey can we do this like every week?" And I wouldn't be surprised if the frequency increases from that, but I think that just almost speaks to human beings and that we crave social interaction. And even though most of the people at Observe are engineers and by definition should not enjoy as much social interaction, they do. They love it, right? And to me, that gaming and social direction, that's part of work. And so you have to have a virtual environment that can reproduce that. >> I mean, it's very interesting to see some of the entrepreneurial exercises or pitches that come out of this because I think it's going to be a Renaissance, it's not Renaissance 'cause it's going to come back. It's always been there. But the new kind of entrepreneurial products coming out are going to address these things. And the question I want to ask you, 'cause you've been on the big company, you've done extremely well in your career, than you get back down to your roots to doing startup, you're launching, you haven't yet launched. So you got hit right here, you're working at home sheltering in place. I was talking to a couple of VC buddies, venture capitalists, and they're saying, "I'm reading books and I'm doing research "but I really can't meet people." So their work has changed. How do you see the investment community reacting to this? Certainly valuations might come down. Obviously, their limited partners are being hit with the stock market. You're seeing a disruption. What do you see going on in the VC world around this cold hard time? >> I mean certainly all VCs are not created equal. So I think there's going to be different perspectives based on the background of the DNA of the VC involved. I think certainly at Observe, I feel very fortunate that we've got a sort of Hill Ventures. So these guys were the investors behind Snowflake and behind Pure Storage and many other good companies but they're very longterm investors and their advice to me has been, "Well look, "some of the most innovative times if you like, "have been during and after a major crisis. "And so if you make short term decisions "to get you through those crisis, "they're all terrible but they don't last forever "and there will be another side. "And so make good business decisions "and good investment decisions through this "because there will be winners "that emerge on the other side." And that's really what I try and get the team focused on is, "Guys for now, we're sort of hunkered down "and it feels bad, "but we're probably more privileged than most. "And we have an opportunity maybe on the other side, "to take advantage, we don't have a revenue stream, "we don't have existing customers. "We can sort of take this Greenfield business "that we've got and you go on the offensive "when things returned to assemblance of normal." So The Hill had been fantastic. And I would hope that most VCs retain that perspective, which is if it was a good company three weeks ago, it's probably still a good company today. And the best way to create value is to sort of empower I think the CEOs and executive teams to make the right sort of longer term decisions. Try and capitalize when you come out the other side because there will be losers as well. And I think the wrong decisions now can put you on the losing end of that equation in three, four, five months time. >> Yeah, that's a good point. If you are a good company just a few months ago or even weeks ago or a year ago, you're still a good company. That's really going to be a tell sign to what happens in some of these companies. If I got to ask you a more focused question on this whole, which side of the street are you on? Are you riding the wave or are you going to get taken away and washed away with it? Because there are bets and well, I want to get into Observe in a minute, but you mentioned Snowflake there in the Cloud wave. Obviously, that's pretty bullish. We're still bullish on that. Obviously, it's going to be game changer. But is there a tell sign for the kind of bets that those good management teams need to make now? Because I agree with you, when the Dot-com bubble burst in 2000 and really 2004 kicked back up again. 2008, we saw that post and a lot of great companies were created. So what's your advice on which side of history do you need to be on here? I'll say Cloud is one. What is your view on that? >> Yeah, I mean we felt for many years, it's not just since I went to the startup, but I am a huge believer in this transition to digital businesses. Frictionless interactions, automation, yes, obviously people are required to run a business, but if you could run a business remotely, or the businesses automated in a way such that it doesn't require hands-on operation, then that's a beautiful thing. And my belief is that, this terrible situation will force people to really think seriously about what the digital business looks like. If you don't have one, then that you may not be able to be in business in a year, two, three years down the line, right? There'll be some carryover, but I think the smart businesses are going to be able to function in an environment such as this. >> Yeah, I think that's great. >> That's going to be playing on everybody's minds. Now more than ever, I think that the digital business is a necessity. >> Yeah, I was just talking to a colleague and we were just talking about how all of the events got canceled and you've had the history running some of those best events ever in the industry at EMC. And we participated in those and you know your staff when it comes to events, there's economic value in these physical events as a venue, Science Convention Center in Moscone here in San Francisco. I mean there's a lot of things that go on, a lot of decision-making that's been standardized over the years and there's an economic value that comes out of those events. Now that's gone, and then these little digital teams, some companies have like five people, two people, sometimes maybe if you're lucky you have 10 or more or a department. And then you've got demand generation. All these guys are being told now, "You have to make up for the shortfall "in not just leads but value." And this just has been a big burden for some of my friends out there who are like, "Wait a minute, you want to take that and move it over here?" It's been kind of a challenge. What is your view on this? Because a lot of people are trying to figure this particular problem out on how to make digital work today and have some extensibility and get success. What's your take? >> Well, I'm still a huge believer I mean, whereas sort of like we just saw digital marketing content is still very much King, right? If you can produce a compelling piece of content online, TV quality with a depth of knowledge that you're going to attract an audience, now can you then make that experience interactive? Can you engage the audience in a deeper way? Yeah, you're probably not going to have something which lasts for a full day or for three days online, but I think it's really going to force the creativity on the content side to another level, right? It can't just be talking heads and PowerPoint pictures. So that rethinking from first principles, what an online conference or an online experience actually looks like in a way that it engages the people who are watching. To me, those folks are going to go do very, very well. And the economics, I know how much it costs to put on a conference for 10 or 15,000 people. And by the way, I know how much it costs to put on a virtual event for 10 or 15,000 people. And the economics are astounding in that difference. Now if you're physically somewhere, you can feel things that you can't feel online. Come on though, this is a problem that requires some innovation to solve, right? We've talked about virtual reality and augmented reality, but it's still pretty clunky and relegated to sort of niche use cases and bad games. But at some point, that technology has to reach the point where it can be useful and engage in a new. You can approximate to that physical experience. But I think that is going to be critical but many businesses even beyond sort of marketing and virtual events and that kind of thing, many businesses are just going to have to reinvent how they engage and interact with their customers and the automation of their operations and how do you get by when you don't have as many people physically in an office or operating machines? Everybody's going to have to think through that. >> Yeah, I think that's great insight and that's going to be a great clip that I'll share and I think that's going to be inspirational for the folks trying to solve that problem. The things that we're focused in on, as you know, and this is something that we're doing a lot of work on, is the engagement with groups and you mentioned The Secret Hitler as the game, they're going to see some new clever things go on. And I think the group dynamic and having people in whether it's virtual and physical spaces exchanging credible things, ideas or jokes or whatever is going to be a new kind of dynamic. >> Yeah. >> Because that's going to have to fill the void. >> Yeah, I mean I've got a small company so we can play these individual games, but just think about some of these board type games where I want to have three teams and I want to divide the company up into three. The logistics of actually figuring that out is ridiculous and it shouldn't be that way, right? And so these are basics of human social interactions. We want to play a game together, we want to divide up into teams. But that sounds like a relatively trivial thing, but try and find the number of games available that allow you to easily do that and each team interaction independently of the others, it's almost impossible. >> It's going to be fun to watch and I think and I hope we're going to learn. Well, thanks for the device. Let's get back to your startup. Let's get a plug in for that, I want to get the plug in. I've seen you in stealth so you can't really go into great detail, but you have been talking to customers. You are obviously related, that's related to Snowflake, but you were going to do some things with Snowflake. You're in the Cloud. Can you just take a minute to give a plug for what you guys are doing for the people who want to know what you guys are leaning towards in terms of the value proposition? >> Yeah well, when I look back in my career, one of the times I enjoyed the most was the time at Oracle and working with data. And I've been fortunate enough for the last four and a half years or so to be on the board of Snowflake. Couple of ex Oracle guys, Benoit and Thierry founded the company and they've reinvented the database. And I felt like I've sat for 20 years looking for the second coming of the database and we all were sort of had fake thinking it was Hadoop. And turns out it wasn't. But I think Snowflake and the separation of storage and compute that allows them to sort of scale and have a usage-based pricing model, I just think is absolutely revolutionary and I think it's going to be one of the great companies of the new era. And so when I was there when I looked at Observe, really the thesis was that using a platform like Snowflake, you could potentially reason about unstructured log data. It's all like Splunk. You could reason about time series data, a little bit like Datadog or tracing data like AppDynamics or in fact any data, you could reason about it together. And today, if you look at the world, it's like if you want to do something with logs, you go get one product. If you want to do something with relational data, you get another, if you want to do time series data, you get another, you want to do tracing, you get an APM tool. And nobody has the big picture, right? Everybody's got their own little piece of data and their own perspective on where the issue might be in your company. But nobody really knows and it's usually put together in the brain of, of the smartest guy in the room. And so I thought it was quite simple. At Snowflake, you've got this commercial database that can do instruction data and time series data and relational data. And what if we could collect all data within an organization together, structure it, relate it, and then imagine what you could find out about your infrastructure, your applications, your business? >> Sort of unification? Does it have like unification kind of concept for users or IT? >> Yeah, I think the emerging category would be observability but it really is a collapsing of log analytics, metrics monitoring and tracing into this new category of observability. We don't necessarily just view that though as sort of data coming out of Kubernetes clusters or out of AWS or wherever. We actually could ingest security data. We could ingest data from people surfing using your app or surfing your website. We could take logs coming out of machines on a factory floor. So the way we built the product, it can be literally any kind of data. And we try and structure it and relate it and make sense of it and then make it very easy for people to navigate through it and determine issues and problems. So yeah, we're pretty excited about it. And like I said, we could not have built this even a couple of years ago because I don't think Snowflake would have been there. And in fact, that was one of the big risks when we started the company. Can we build it on Snowflake? And so here we are two years later and we think we can. Well, we're sure we can do it. >> Yeah, they've had a good run too. I mean, look at the growth of Snowflake. >> Yeah, it's crazy. I've never seen anything like it and in the last 20 years and B2B, I've never seen anything like it. So just like I felt in the mid 90s when I was at Oracle, people were making decisions to go with Oracle and then saying, "Hey, help me get all of my other data in that, "my mainframe data, my this, my that." I think Snowflake are going to go through the same sort of growth phase and hopefully with Observe, we can be like, "Hey, if you want to put "your unstructured data or time series data, "we can help you do that very easily." >> Well, this is exactly the current wave that you want to be on the right side of because like you said, just a year or so ago or a couple of years ago, it wasn't available. This is kind of the new capabilities. >> Yeah, I feel like there's going to be a lot of businesses, grow ridiculously. You talked about the Zoom numbers. These are ridiculous growth numbers and there are going to be companies come out the other side that take advantage of the new environment. And as they're growing, as they're scaling, as they build these new microservice-based applications, they're going to run into issues and we hope at least that it's products with our kind of architecture, that's going to be able to help these fast-growing businesses. So yeah, as I said, we're somewhat fortunate in that we don't have a product yet, but certainly on the other side of this, we think there's going to be plenty of opportunity to help a few folks. >> We know you got to do a launch and we're looking forward to hearing more and getting the briefing, and looking forward to hearing more about it when you go public. And yeah, thanks for coming on and taking the time today. I know you got your daughter's birthday party there and you're going to have some celebration. Thank you for sharing the insights on your vision of digital. I thought that was very compelling and great to see you and stay safe. >> Great to see you. Yeah, my 18-year-old, it's got a birthday party and she like always would worry, "What if no one shows up?" Well, today she knows no one's going to show up. >> Except for her family, yeah. >> It's going to be down in the family, yeah. So thanks for that and you guys stay safe and been great the last 10 years knowing theCUBE been that long but hopefully, here is the next 10 years after this current situation is over. >> Yeah, looking forward to it, it's going to be a lot of fun rye and get the content out there. And again, thanks for coming on during this important time and sharing your insights and also just making some entertainment here. We're getting some conversations so people can fill the void and play some games and have some fun. Jeremy, thanks. Great to see you. Jeremy Burton, senior executive in the industry. I've known him for years, been a CUBE alumni since theCUBE was formed. Now the CEO of Observe, sharing his insights on the industry but more importantly, how to be successful, how to come out the other side. Don't be too optimistic. Be focused on today and get through it. That's his advice. Of course, we're theCUBE bringing you all the data as we can now with remote interviews during this time. Thanks for watching, I'm John furrier. (soft music)