>>president >>so called big data promised to usher in a new era of innovation where companies competed on the basis of insights and agile decision making. There's little question that social media giants, search leaders and e commerce companies benefited. They had the engineering shops and the execution capabilities to take troves of data and turned them into piles of money. But many organizations were not as successful. They invested heavily in data architecture is tooling and hyper specialized experts to build out their data pipelines. Yet they still struggle today to truly realize they're busy. Did data in their lakes is plentiful but actionable insights aren't so much chaos. Search is a cloud based startup that wants to change this dynamic with a new approach designed to simplify and accelerate time to insights and dramatically lower cost and with us to discuss his company and its vision for the future is cuba Lem Ed Walsh had great to see you. Thanks for coming back in the cube. >>I always love to be here. Thank you very much. It's always a warm welcome. Thank you. >>Alright, so give us the update. You guys have had some big funding rounds, You're making real progress on the tech, taking it to market what's new with chaos surgery. >>Sure. Actually even a lot of good exciting things happen. In fact just this month we need some, you know, obviously announced some pretty exciting things. So we unveiled what we consider the industry first multi model data late platform that we allow you to take your data in S three. In fact, if you want to show the image you can, but basically we allow you to put your data in S three and then what we do is we activate that data and what we do is a full index of the data and makes it available through open a P. I. S. And the key thing about that is it allows your end users to use the tools are using today. So simply put your data in your cloud option charge, think Amazon S three and glacier think of all the different data. Is that a natural act? And then we do the hard work. And the key thing is to get one unified delic but it's a multi mode model access so we expose api like the elastic search aPI So you can do things like search or using cabana do log analytics but you can also do things like sequel, use Tableau looker or bring relational concepts into cabana. Things like joins in the data back end. But it allows you also to machine learning which is early next year. But what you get is that with that because of a data lake philosophy, we're not making new transformations without all the data movement. People typically land data in S. Three and we're on the shoulders of giants with us three. Um There's not a better more cost effective platform. More resilient. There's not a better queuing system out there and it's gonna cost curve that you can't beat. But basically so people store a lot of data in S. Three. Um But what their um But basically what you have to do is you E. T. L. Out to other locations. What we do is allow you to literally keep it in place. We index in place. We write our hot index to rewrite index, allow you to go after that but published an open aPI S. But what we avoid is the GTL process. So what our index does is look at the data and does full scheme of discovery normalization, were able to give sample sets. And then the refinery allows you to advance transformations using code. Think about using sequel or using rejects to change that data pull the dead apartheid things but use role based access to give that to the end user. But it's in a format that their tools understand cabana will use the elasticsearch ap or using elasticsearch calls but also sequel and go directly after data by doing that. You get a data lake but you haven't had to take the three weeks to three months to transform your data. Everyone else makes you. And you talk about the failure. The idea that Alex was put your data there in a very scalable resilient environment. Don't do transformation. It was too hard to structure for databases and data. Where else is put it there? We'll show you how value out Largely un delivered. But we're that last mile. We do exactly that. Just put it in s. three and we activated and activate it with a piece that the tools of your analysts use today or what they want to use in the future. That is what's so powerful. So basically we're on the shoulders of giants with street, put it there and we light it up and that's really the last mile. But it's this multi model but it's also this lack of transformation. We can do all the transformation that's all to virtually and available immediately. You're not doing extended GTL projects with big teams moving around a lot of data in the enterprise. In fact, most time they land and that's three and they move it somewhere and they move it again. What we're saying is now just leave in place well index and make it available. >>So the reason that it was interesting, so the reason they want to move in the S three was the original object storage cloud. It was, it was a cheap bucket. Okay. But it's become much more than that when you talk to customers like, hey, I have all this data in this three. I want to do something with it. I want to apply machine intelligence. I want to search it. I want to do all these things, but you're right. I have to move it. Oftentimes to do that. So that's a huge value. Now can I, are you available in the AWS marketplace yet? >>You know, in fact that was the other announcement to talk about. So our solution is one person available AWS marketplace, which is great for clients because they've been burned down their credits with amazon. >>Yeah, that's that super great news there. Now let's talk a little bit more about data. Like you know, the old joke of the tongue in cheek was data lakes become data swamps. You sort of know, see no schema on, right. Oh great. I can put everything into the lake and then it's like, okay, what? Um, so maybe double click on that a little bit and provide a little bit more details to your, your vision there and your philosophy. >>So if you could put things that data can get after it with your own tools on elastic or search, of course you do that. If you don't have to go through that. But everyone thinks it's a status quo. Everyone is using, you know, everyone has to put it in some sort of schema in a database before they can get access to what everyone does. They move it some place to do it. Now. They're using 1970s and maybe 1980s technology. And they're saying, I'm gonna put it in this database, it works on the cloud and you can go after it. But you have to do all the same pain of transformation, which is what takes human. We use time, cost and complexity. It takes time to do that to do a transformation for an user. It takes a lot of time. But it also takes a teams time to do it with dBS and data scientists to do exactly that. And it's not one thing going on. So it takes three weeks to three months in enterprise. It's a cost complexity. But all these pipelines for every data request, you're trying to give them their own data set. It ends up being data puddles all over this. It might be in your data lake, but it's all separated. Hard to govern. Hard to manage. What we do is we stop that. What we do is we index in place. Your dad is already necessary. Typically retailing it out. You can continue doing that. We really are just one more use of the data. We do read only access. We do not change that data and you give us a place in. You're going to write our index. It's a full rewrite index. Once we did that that allows you with the refinery to make that we just we activate that data. It will immediately fully index was performant from cabana. So you no longer have to take your data and move it and do a pipeline into elasticsearch which becomes kind of brittle at scale. You have the scale of S. Three but use the exact same tools you do today. And what we find for like log analytics is it's a slightly different use case for large analytics or value prop than Be I or what we're doing with private companies but the logs were saving clients 50 to 80% on the hard dollars a day in the month. They're going from very limited data sets to unlimited data sets. Whatever they want to keep an S. Three and glacier. But also they're getting away from the brittle data layer which is the loosen environment which any of the data layers hold you back because it takes time to put it there. But more importantly It becomes brittle at scale where you don't have any of that scale issue when using S. three. Is your dad like. So what what >>are the big use cases Ed you mentioned log analytics? Maybe you can talk about that. And are there any others that are sort of forming in the marketplace? Any patterns that you see >>Because of the multi model we can do a lot of different use cases but we always work with clients on high R. O. I use cases why the Big Bang theory of Due dad like and put everything in it. It's just proven not to work right? So what we're focusing first use cases, log analytics, why as by way with everything had a tipping point, right? People were buying model, save money here, invested here. It went quickly to no, no we're going cloud native and we have to and then on top of it it was how do we efficiently innovate? So they got the tipping point happens, everyone's going cloud native. Once you go cloud native, the amount of machine generated data that you have that comes from the environment dramatically. It just explodes. You're not managing hundreds or thousands or maybe 10,000 endpoints, you're dealing with millions or billions and also you need this insight to get inside out. So logs become one of the things you can't keep up with it. I think I mentioned uh we went to a group of end users, it was only 60 enterprise clients but we asked him what's your capture rate on logs And they said what do you want it to be 80%, actually 78 said listen we want eight captured 80 200 of our logs. That would be the ideal not everything but we need most of it. And then the same group, what are you doing? Well 82 had less than 50%. They just can't keep up with it and every everything including elastic and Splunk. They work harder to the process to narrow and keep less and less data. Why? Because they can't handle the scale, we just say landed there don't transform will make it all available to you. So for log analytics, especially with cloud native, you need this type of technology and you need to stop, it's like uh it feels so good when you stop hitting your head against the wall. Right? This detail process that this type of scale just doesn't work. So that's exactly we're delivering the second use case uh and that's with using elastic KPI but also using sequel to go after the same data representation. And we come out with machine learning. You can also do anomaly detection on the same data representation. So for a log uh analytic use case series devops setups. It's a huge value problem now the same platform because it has sequel exposed. You can do just what we use the term is agile B. I people are using you think about look or tableau power bi I uh metabolic. I think of all these toolsets that people want to give and uh and use your business or coming back to the centralized team every single week asking for new datasets. And they have to be set up like a data set. They have to do an e tail process that give access to that data where because of the way just landed in the bucket. If you have access to that with role based access, I can literally get you access that with your tool set, let's say Tableau looker. You know um these different data sets literally in five minutes and now you're off and running and if you want a new dataset they give another virtual and you're off and running. But with full governance so we can use to be in B I either had self service or centralized. Self service is kind of out of control, but we can move fast and the centralized team is it takes me months but at least I'm in control. We allow you do both fully governed but self service. Right. I got to >>have lower. I gotta excel. All right. And it's like and that's the trade off on each of the pieces of the triangle. Right. >>And they make it easy, we'll just put in a data source and you're done. But the problem is you have to E T L the data source. And that's what takes the three weeks to three months in enterprise and we do it virtually in five minutes. So now the third is actually think about um it's kind of a combination of the two. Think about uh you love the beers and diaper stories. So you know, think about early days of terror data where they look at sales out data for business and they were able to look at all the sales out data, large relational environment, look at it, they crunch all these numbers and they figured out by different location of products and the start of they sell more sticker things and they came up with an analogy which everyone talked about beers and diapers. If you put it together, you sell more from why? Because afternoon for anyone that has kids, you picked up diapers and you might want to grab a beer of your home with the kids. But that analogy 30 years ago, it's now well we're what's the shelf space now for approximate company? You know it is the website, it's actually what's the data coming from there. It's actually the app logs and you're not capturing them because you can't in these environments or you're capturing the data. But everyone's telling, you know, you've got to do an E. T. L. Process to keep less data. You've got to select, you got to be very specific because it's going to kill your budget. You can't do that with elastic or Splunk, you gotta keep less data and you don't even know what the questions are gonna ask with us, Bring all the app logs just land in S. three or glacier which is the most it's really shoulders of giants right? There's not a better platform cost effectively security resilience or through but to think about what you can stream and the it's the best queuing platform I've ever seen in the industry just landed there. And it's also very cost effective. We also compress the data. So by doing that now you match that up with actually relatively small amount of relational data and now you have the vaccine being data. But instead it's like this users using that use case and our top users are always, they start with this one then they use that feature and that feature. Hey, we just did new pricing is affecting these clients and that clients by doing this. We get that. But you need that data and people aren't able to capture it with the current platforms. A data lake. As long as you can make it available. Hot is a way to do it. And that's what we're doing. But we're unique in that. Other people are making GTL IT and put it in a in 19 seventies and 19 eighties data format called a schema. And we avoided that because we basically make S three a hot and elected. >>So okay. So I gotta I want to, I want to land on that for a second because I think sometimes people get confused. I know I do sometimes without chaos or it's like sometimes don't know where to put you. I'm like okay observe ability that seems to be a hot space. You know of course log analytics as part of that B. I. Agile B. I. You called it but there's players like elastic search their star burst. There's data, dogs, data bricks. Dream EOS Snowflake. I mean where do you fit where what's the category and how do you differentiate from players like that? >>Yeah. So we went about it fundamentally different than everyone else. Six years ago. Um Tom hazel and his band of merry men and women came up and designed it from scratch. They may basically yesterday they purposely built make s free hot analytic environment with open A. P. I. S. By doing that. They kind of changed the game so we deliver upon the true promises. Just put it there and I'll give you access to it. No one else does that. Everyone else makes you move the data and put it in schema of some format to get to it. And they try to put so if you look at elasticsearch, why are we going after? Like it just happens to be an easy logs are overwhelming. You once you go to cloud native, you can't afford to put it in a loose seen the elk stack. L is for loosen its inverted index. Start small. Great. But once you now grow it's now not one server. Five servers, 15 servers, you lose a server, you're down for three days because you have to rebuild the whole thing. It becomes brittle at scale and expensive. So you trade off I'm going to keep less or keep less either from retention or data. So basically by doing that so elastic we're not we have no elastic on that covers but we allow you to well index the data in S. Tree and you can access it directly through a cabana interface or an open search interface. Api >>out it's just a P. >>It's open A P. I. S. It's And by doing that you've avoided a whole bunch of time cost, complexity, time of your team to do it. But also the time to results the delays of doing that cost. It's crazy. We're saving 50-80 hard dollars while giving you unlimited retention where you were dramatically limited before us. And as a managed service you have to manage that Kind of Clunky. Not when it starts small, when it starts small, it's great once at scale. That's a terrible environment to manage the scale. That's why you end up with not one elasticsearch cluster, dozens. I just talked to someone yesterday had 125 elasticsearch clusters because of the scale. So anyway, that's where elastic we're not a Mhm. If you're using elastic it scale and you're having problems with the retired off of cost time in the, in the scale, we become a natural fit and you don't change what your end users do. >>So the thing, you know, they had people here, this will go, wow, that sounds so simple. Why doesn't everybody do this? The reason is it's not easy. You said tom and his merry band. This is really hard core tech. Um and it's and it's it's not trivial what you've built. Let's talk about your secret sauce. >>Yeah. So it is a patented technology. So if you look at our, you know, component for architecture is basically a large part of the 90% of value add is actually S. Three, I gotta give S three full kudos. They built a platform that we're on shoulders of giants. Um But what we did is we purpose built to make an object storage a hot alec database. So we have an index, like a database. Um And we basically the data you bring a refinery to be able to do all the advanced type of transformation but all virtually done because we're not changing the source of record, we're changing the virtual views And then a fabric allows you to manage and be fully elastic. So if we have a big queries because we have multiple clients with multiple use cases, each multiple petabytes, we're spending up 1800 different nodes after a particular environment. But even with all that we're saving them 58%. But it's really the patented technology to do this, it took us six years by the way, that's what it takes to come up with this. I come upon it, I knew the founder, I've known tom tom a stable for a while and uh you know his first thing was he figured out the math and the math worked out. Its deep tech, it's hard tech. But the key thing about it is we've been in market now for two years, multiple use cases in production at scale. Um Now what you do is roadmap, we're adding a P. I. So now we have elasticsearch natural proofpoint. Now you're adding sequel allows you open up new markets. But the idea for the person dealing with, you know, so we believe we deliver on the true promise of Data Lakes and the promise of Data lakes was put it there, don't focus on transferring. It's just too hard. I'll get insights out and that's exactly what we do. But we're the only ones that do that everyone else makes you E. T. L. At places. And that's the innovation of the index in the refinery that allows the index in place and give virtual views in place at scale. Um And then the open api is to be honest, uh I think that's a game. Give me an open api let me go after it. I don't know what tool I'm gonna use next week every time we go into account they're not a looker shop or Tableau Sharp or quick site shop there, all of them and they're just trying to keep up with the businesses. Um and then the ability to have role based access where actually can give, hey, get them their own bucket, give them their own refinery. As long as they have access to the data, they can go to their own manipulation ends up being >>just, >>that's the true promise of data lakes. Once we come out with machine learning next year, now you're gonna rip through the same embassy and the way we structured the data matrices. It's a natural fit for things like tensorflow pytorch, but that's, that's gonna be next year just because it's a different persona. But the underlining architecture has been built, what we're doing is trying to use case that time. So we worked, our clients say it's not a big bang. Let's nail a use case that works well. Great R. O. I great business value for a particular business unit and let's move to the next. And that's how I think it's gonna be really. That's what if you think about gardener talks about, if you think about what really got successful in data, where else in the past? That's exactly it wasn't the big bang, it was, let's go and nail it for particular users. And that's what we're doing now because it's multi model, there's a bunch of different use cases, but even then we're focusing on these core things that are really hard to do with other relational only environments. Yeah, I >>can see why you're still because you know, you haven't been well, you and I have talked about the api economy for forever and then you've been in the storage world so long. You know what a nightmare is to move data. We gotta, we gotta jump. But I want to ask you, I want to be clear on this. So you are your cloud cloud Native talked to frank's Lukman maybe a year ago and I asked him about on prem and he's like, no, we're never doing the halfway house. We are cloud all the >>way. I think >>you're, I think you have a similar answer. What what's your plan on Hybrid? >>Okay. We get, there's nothing about technology, we can't go on, but we are 100 cloud native or only in the public cloud. We believe that's a trend line. Everyone agrees with us, we're sticking there. That's for the opportunity. And if you can run analytics, There's nothing better than getting to the public cloud like Amazon and he was actually, that were 100 cloud native. Uh, we love S three and what would be a better place to put this is put the next three and we just let you light it up and then I guess if I'm gonna add the commercial and buy it through amazon marketplace, which we love that business model with amazon. It's >>great. Ed thanks so much for coming back in the cube and participating in the startup showcase. Love having you and best of luck. Really exciting. >>Hey, thanks again, appreciate it. >>All right, thank you for watching everybody. This is Dave Volonte for the cube. Keep it right there.

>>from the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around >>the world. This is a cute conversation high, but this is Day Volonte. And as you know, we've been tracking the next generation of clouds. Sometimes we call it Cloud to two point. Frank's Lukman is here to really unpack this with me. Frank. Great to see you. Thanks for coming on. >>Yeah, you as well. They could see it >>s o obviously hot off your AIPO A lot of buzz around that. Uh, that's fine. We could we could talk about that, but I really want to talk about the future. What? Before we get off the I p o. That was something you told me when you're CEO service. Now you said, hey, we're priced to perfection, so it looks like snowflakes gonna be priced to perfection. It's a marathon, though. You You made that clear. I presume it's not any different here for you. Yeah, >>well, I think you know the service now. Journey was different in the sense that we were kind of under the underdogs, and people sort of discovered over the years the full potential of the company and I think there's stuff like they pretty much discovered a day. One. It's a little bit more, More sometimes it's nice to be an underdog. Were a bit of an over dog in this, uh, this particular scenario, but, you know, it is what it is, Andre. You know, it's all about execution delivering the results, delivering on our vision, Uh, you know, being great with our customers. And, uh, hopefully the chips will fall where they where they may. At that point, >>yeah, you're you're You're a poorly kept secret at this point, Frank. After a while, I wanted, you know, I've got some excerpts of your book that that I've been reading. And, of course, I've been following your career since the two thousands. You're off sailing. You mentioned in your book that you were kind of retired. You were done, and then you get sucked back in now. Why? I mean, are you in this for the sport? What's the story here? >>Uh, actually, that that's not a bad way of characterizing it. I think I am in that, uh, you know, for the sport, uh, you know the only way to become the best version of yourself is to be to be under the gun and, uh, you know, every single day. And that's that's certainly what we are. It sort of has its own rewards building great products, building great companies, regardless off you know what the spoils. Maybe it has its own rewards. And I It's hard for people like us to get off the field and, you know, hang it up. So here we are. >>You know, you're putting forth this vision now the data cloud, which obviously it's good marketing, but I'm really happy because I don't like the term Enterprise Data Warehouse. I don't think it reflects what you're trying to accomplish. E D. W. It's slow on Lee. A few people really know how to use it. The time value of data is gone by the time you know, your business is moving faster than the data in the D. W. And it really became a savior because of Sarbanes Oxley. That's really what it came a reporting mechanism. So I've never seen What you guys are doing is is e d w. So I want you to talk about the data cloud. I want to get into the to the vision a little bit and maybe challenge you on a couple things so our audience can better understand it. Yes. So >>the notion of a data cloud is is actually, uh, you know, type of cloud that we haven't had. I mean, data has been been fragmented and locked up in a million different places in different clouds. Different cloud regions, obviously on premise, um, And for data science teams, you know, they're trying thio drive analysis across datasets, which is incredibly hard, Which is why you know, a lot of this resorts to, you know, programming on bond things of that sort of. ITT's hardly scalable because the data is not optimized. The economics are not optimized. There's no governance model and so on. But a data cloud is actually the ability thio loosely couple and lightly Federated uh, data, regardless of where it is. So it doesn't have scale limitations or performance limitations. Uh, the way traditional data warehouses have had it. So we really have a fighting chance off really killing the silos and unlocking the bunkers and allowing the full promise of data sciences and ml On day I thio really happen. I mean, a lot of lot of the analysis that happens on data is on the single data set because it's just too damn hard, you know, to drive analysis across multiple data sets. And, you know, when we talk to our customers, they have very precise designs on what they're trying to do. They say, Look, we are trying to discover, you know, through through through deep learning You know what the patterns are that lead to transactions. You know, whether it's if you're streaming company. Maybe it's that you're signing up for a channel or you're buying a movie or whatever it is. What is the pattern you know, of data points that leads us to that desired outcome. Once you have a very accurate description of the data relationships, you know that results in that outcome, you can then search for it and scale it, you know, tens of million times over. That's what digital enterprises do, right? So in order to discover these patterns enriched the data to the point where the patterns become incredibly predictive. Uh, that's that's what snowflake is formed, right? But it requires a completely Federated Data mo because you're not gonna find a data pattern in the in the single data set per se right? So that's that's what it's all about. I mean, the outcomes of a data cloud are very, very closely related to the business outcomes that the user is seeking, right? It's not some infrastructure process. It has a very remote relationship with business outcome. This is very, very closely related. >>So it doesn't take a brain surgeon to look at the Trillion Years Club. And so I could see that I could see the big you know, trillion dollars apple $2 trillion market cap companies. They got data at the core, whereas most companies most incumbents. Yeah, it might be a bottling plant that the core, some manufacturing or some other processes they put, they put data around it in these silos. It seems like you're trying toe really? Bring that innovation and put data at the core. And you've got an architecture to do that. You talk about your multi cluster shared storage architecture. You mentioned you mentioned data sharing it. Will this, in your opinion, enable, for instance, incumbents to do what a lot of the startups were able to do with the cloud days? I mean they got access to data centers, which they they couldn't have before the cloud you're trying to do with something similar with data. >>Yeah, so So, you know, obviously there's no doubt that the cloud is a critical enabler. This wouldn't be happening. Uh, you know what? I was at the same time, the trails that have been blessed by the likes of Facebook and Google. Uh, e the reason those enterprises are so extraordinary valuable is is because of what they know. Uh, you know, through data and how they can monetize what they know through data. But that is now because that power is now becoming available, you know, to every single enterprise out there. Right, Because the data platform, the underlying cloud capabilities, we are now delivering that to anybody who wants it. Now, you still need to have strong date engineering data science capabilities. It's not like falling off a log, but fundamentally, those capabilities are now, you know, broadly accessible in the marketplace. >>So we're talking upfront about some of the differences between what you've done earlier in your career. Like I said, you're the worst kept secret, you know, Data domain. I would say it was sort of somewhat of a niche market. You you blew it up until it was very disruptive, but it was somewhat limited in what could be done. Uh, and and maybe some of that limitation, you know, wouldn't have occurred if you stay the price, uh, independent company service. Now you mop the table up because you really had no competition there, Not the case here. You you've got some of the biggest competitors in the world, so talk about that. And what gives you confidence that you can continue to dominate, >>But, you know, it's actually interesting that you bring up these companies. I mean, data. The man was a scenario where we were constrained on market and literally we were a data backup company. As you recall, we needed to move into backup software. Need to move the primary storage. While we knew it, we couldn't execute on it because it took tremendous resource is which, back in the day, it was much harder than one of this right now. So we ended up selling the company to E M. C and and now part of Dell. But way short, uh, we're left with some trauma from that experience, Uh, that, you know, why couldn't we, you know, execute on that transformation? So coming to service now, we were extremely. I'm certainly need personally, extremely attuned to the challenges that we have endured in our prior company. One of the reasons why you saw service now break out at scale at tremendous growth rights is because of what we have learned from the prior journey. We're not gonna ever get caught again in a situation where we could not sustain our markets and sustain our growth. So if service I was very much the execution model was very much a reaction to what we had encountered in the prior company. Now coming into snowflake totally different deal. Because not only is there's a large market, this is a developing market. I think you've pointed out in some of your broadcasting that this market is very much in flux on the reason is that you know, technology is now capable of doing things for for people and enterprises that they could never do before. So people are spending way mawr resource is than they ever thought possible on these new capability. So you can't think in terms of static markets and static data definitions, it means nothing. Okay, These things are so in transition right now, it's very difficult for people you know to to scope that the scale of this opportunity. >>Yeah. I wanna understand you're thinking around and, you know, I've written about the TAM, and can Snowflake grow into its valuation and the way I drew it, I said, Okay, you got data Lakes and you got Enterprise Data Warehouse. That's pretty well understood. But I called it data as a service to cover the closest analogy to your data cloud. And then even beyond that, when you start bringing in the edge and real time data, uh, talk about how you're thinking about that, Tam. And what what you have to do to participate. You have toe, you know, bring adjacent capabilities, ISAT this read data sharing that will get you there. In other words, you're not like a transaction system. You hear people talking about converge databases, you hear? Talk about real time inference at the edge that today anyway, isn't what snowflake is about. Does that vision of data sharing and the data cloud does that allow you to participate in that massive, multi $100 billion tam that that I laid out and probably others as well. >>Yeah, well, it is always difficult. Thio defined markets based on historical concept that probably not gonna apply whole lot for much longer. I mean, the way we think of it is that data is the beating heart of the digital enterprise on, uh, you know, digital enterprises today. What do you look at? People against the car door dash or so on. Um, they were built from the ground up to be digital on the prices and data Is the beating heart off their operation Data operations is their manufacturing, if you will, um, every other enterprise out there is is working very hard to become digital or part digital and is going to learn to develop data platforms like what we're talking about here to data Cloud Azaz. Well, as the expertise in terms of data engineering and data scientist to really fully become a digital enterprise, right. So, you know, we view data as driving operations off the digital enterprise. That's really what it iss right data, and it's completely data driven. And there's no people involved. People are developing and supporting the process. But in the execution, it is end to end. Data driven. Being that data is the is the signal that initiates the process is technol assess. Their there being a detective, and then they fully execute the entire machinery probe Problematic machinery, if you will, um, you know, of the processes that have been designed, for example, you know, I may fit a certain pattern. You know, that that leads to some transactional context. But I've not fully completed that pattern until I click on some Lincoln. And all of a sudden proof I have become, you know, a prime prospect system, the text that in the real time and then unleashes Oh, it's outreach and capabilities to get me to transact me. You and I are experiencing this every day. You know, when we're when we're online, you just may not fully re election. That's what's happening behind the scenes. That's really what this is all about. So and so to me, this is sort of the new online transaction processing is enter and, uh, you know, data digital. Uh, no process that is continually acquiring, analyzing and acting on data. >>Well, you've talked about the time time value of of data. It loses value over time. And to the extent that you can actually affect decisions, maybe before you lose the customer before you lose the patient even even more importantly or before you lose the battle. Uh, there's all kinds of, you know, mental models that you can apply this. So automation is a key part of that. And then again, I think a lot of people like you said, if you just try to look at historical markets, you can't really squint through those and apply them. You really have toe open up your mind and think about the new possibilities. And so I could see your your component of automation. I I see what's happening in the r P. A space and and I could see See these this massive opportunities Thio really change society, change business, your last thoughts. >>There's just there's just no scenario that I can envision where data is not completely core in central to a digital enterprise, period. >>Yeah, I think I really do think, Frank, your your your Your vision is misunderstood somewhat. I think people say Okay. Hey, we'll bet on salute men Scarpelli the team. That's great to do that. But I think this is gonna unfold in a way that people may be having predicted that maybe you guys, yourselves and your founders, you know, haven't have aren't able to predict as well. But you've got that good, strong architectural philosophy that you're pursuing and it just kind of feels right, doesn't it? >>You know, I mean, one of the 100 conversations and, uh, you know, things is the one of the reasons why we also wrote our book. You know, the rights of the data cloud is to convey to the marketplace that this is not an incremental evolution, that this is not sort of building on the past. There is a real step function here on the way to think about it is that typically enterprises and institutions will look at a platform like snowflakes from a workload context. In other words, I have this business. I have this workload. This is very much historically defined, by the way. And then they benchmark us, you know, against what they're what they're already doing on some legacy platform. And they decided, like, Yeah, this is a good fit. We're gonna put Snowflake here. Maybe there, but it's still very workload centric, which means that we are essentially perpetuating the mentality off the past. Right? We were doing it. Wanna work, load of the time We're creating the new silos and the new bunkers of data in the process. And we're really not approaching this with level of vision that the data science is really required to drive maximum benefit from data. So our arguments and this is this is not an easy arguments is to say, toc IOS on any other sea level person that wants to listen to that look, you know, just thinking about, you know, operational context and operational. Excellent. It's like we have toe have a platform that allows us unfettered access to the data that, you know, we may need to, you know, bring the analytical power to right. If you have to bring in political power to a diversity of data sets, how are we going to do that right? The data lives in, like, 500 different places. It's just not possible, right, other than with insane amounts of programming and complexity, and then we don't have the performance, and we don't have to economics, and we don't have the governance and so on. So you really want to set yourself up with a data cloud so that you can unleash your data science, uh, capabilities, your machine learning your deep learning capabilities, aan den, you really get the full throttle advantage. You know of what the technology can do if you're going to perpetuate the silo and bunkering of data by doing it won't work. Load of the time. You know, 5, 10 years from now, we're having the same conversation we've been having over the last 40 years, you know? >>Yeah. Operationalize ing your data is gonna require busting down those those silos, and it's gonna require something like the data cloud to really power that to the next decade and beyond. Frank's movement Thanks so much for coming in. The Cuban helping us do a preview here of what's to come. >>You bet, Dave. Thanks. >>All right. Thank you for watching. Everybody says Dave Volonte for the Cube will see you next time

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all >>around the world. This is a cube conversation, Everyone. Welcome to this week's Cube insights, powered by ET are My name is Dave Volante, and we've been reporting every week really on the code. 19. Impact on Budgets Docker Korakia is back in with me soccer. It's great to see you really >>again for having >>your very welcome. Soccer is, of course, the director of research, that we are our data partner and man. I mean, you guys have just been digging into the data or a court reiterate We're down, you know, roughly around minus 5% for the year. The thing about what we're doing here and where they want to stress in the audience that that's going to change. The key point is we don't just do ah, placeholder and update you in December. Every time we get new information, we're going to convey it to you. So let's get right into it. What we want to do today is you kind of part two from the takeaways that we did last week. So let's start with the macro guys. If you bring up the first chart, take us through kind of the top three takeaways. And just to reiterate where we're at >>Yeah, no problem. And look, as you mentioned, uh, what we're doing right now is we're collecting the pulse of CIOs. And so things change on and we continue to expect them to change, you know, in the next few weeks, in the next few months, as things change with it. So just kind of give a recap of the survey and then kind of going through some of our top macro takeaways. So in March mid March, we launched our Technology Spending Intention Survey. We had 1250 CIOs approximately. Take that survey. They provided their updated 2020 verse 2019 spending intentions, right? So effectively, they first Davis, those 20 21st 19 spending intentions in January. And then they went ahead and up state of those based on what happened with move it and then in tandem with that, we did this kind of over 19 drill down survey where we asked CEOs to estimate the budget impact off overnight in versus what they originally forecast in the year. And so that leads us to our first take away here, where we essentially aggregated the data from all these CIOs in that Logan 19 drill down survey. And we saw a revision of 900 basis points so down to a decline of 5%. And so coming into the year, the consensus was about 4% growth. Ah, and now you can see we're down about 5% for the year. And again, that's subject to change. And we're going again re measure that a Z kind of get into June July and we have a couple of months under our belt with the folks at night. The second big take away here is, you know, the industries that are really indicating those declines and spend retail, consumer airlines, financials, telco I key services in consulting. Those are the verticals, as we mentioned last week, that we're really seeing some of the largest Pullbacks and spend from consumers and businesses. So it makes sense that they are revising their budgets downwards the most. And then finally, the last thing we captured that we spoke about last week as well as a few weeks before that, and I think that's really been playing out the last kind of week in 1/2 earnings is CIOs are continuing to press the pedal on digital transformation. Right? We saw that with Microsoft, with service now last night, right, those companies continued the post good numbers and you see good demand, what we're seeing and where those declines that we just mentioned earlier are coming from. It's it's the legacy that's the on premise that your place there's such a concentration of loss and deceleration within some of those companies. And we'll kind of get into that more a Z go through more slides. But that's really what kind of here, you know, that's really what we need to focus on is the declines are coming from very select vendors. >>Yeah, and of course you know where we were in earning season now, and we're paying close attention to that. A lot of people say I just ignore the earnings here, you know, you got the over 19 Mulligan, but But that's really not right. I mean, obviously you want to look at balance sheets, you want to look at cash flows, but also we're squinting through some of the data your point about I t services and insulting is interesting. I saw another research firm put out that you know, services and consulting was going to be OK. Our data does, you know, different. Uh, and we're watching. For instance, Jim Kavanaugh on IBM's earnings call was very specific about the metrics that they're watching. They're obviously very concerned about pricing and their ability. The book business. There we saw the cloud guys announced Google was up in the strong fifties. The estimate is DCP was even higher up in the 80% range. Azure, you know, we'll talk about this killing it. I mean, you guys have been all over of Microsoft and its presence, you know, high fifties aws solid at around 34% growth from a larger base. But as we've been reporting, you know, downturns. They've been they've been good to cloud. >>That's right. And I think, you know, based on the data that we've captured, um, you know, it's people are really pressing the pedal on cloud and SAS with this much remote work, you need to have you know, that structure in place to maintain productivity. >>Okay, let's bring up the next slide. Now. We've been reporting a lot on this sort of next generation work loads Bob one Dato all about storage and infrastructures of service. Compute. There's an obviously some database, but there's a new analytics workload emerging. Uh, and it's kind of replacing, or at least disinter mediating or disrupting the traditional e d ws. I've said for years. CDW is failed to live up to its expectations of 360 degree insights and real time data, and that's really what we're showing here is some of the traditional CDW guys are getting hit on Some of the emerging guys, um, are looking pretty good. So take us through what we're looking at here. Soccer. >>Yeah, no problem. So we're looking at the database data warehousing sector. What you're looking at here is replacement rates. Um And so, as example, if you see up in with roughly 20% replacement, what that means is one out of five people who took the survey for that particular sector for that vendor indicated that they were replacing, and so you can see here for their data. Cloudera, IBM, Oracle. They have very elevated and accelerating replacement rates. And so when we kind of think about this space. You can really see the bifurcation, right? Look how well positioned the Microsoft AWS is. Google Mongo, Snowflake, low replacements, right low, consistent replacements. And then, of course, on the left hand side of the screen, you're really seeing elevated, accelerating. And so this space is It kind of goes with that theme that we've been talking about that we covered last week by application, right when you think about the declines that you're seeing and spend again, it's very targeted for a lot of these kind of legacy legacy vendors. And we're again. We're seeing a lot of the next gen players that Microsoft AWS in your post very strong data. And so here, looking within database, it's very clear as to which vendors are well positioned for 2020 and which ones look like they're being ripped out and swapped out in the next few months. >>So this to me, is really interesting. So you know, you you've certainly reported on the impact that snowflake is having on Terra data. And in some of IBM's business, the old man, he's a business. You can see that here. You know, it's interesting. During the Hadoop days, Cloudera Horton works when they realize that it didn't really make money on Hadoop. They sort of getting the data management and data database and you're seeing that is under pressure. It's kind of interesting to me. Oracle, you know, is still not what we're seeing with terror data, right, Because they've got a stranglehold on the marketplace That's right, hanging in there. Right? But that snowflake would no replacements is very impressive. Mongo consistent performer. And in Google aws, Microsoft AWS supports with Red Shift. They did a one time license with Park Cell, which was an MPP database. They totally retooled a thing. And now they're sort of interestingly copycatting snowflake separating compute from storage and doing some other moves. And yet they're really strong partners. So interesting >>is going on and even, you know, red shift dynamodb all. They all look good. All these all these AWS products continue screen Very well. Ah, in the data warehousing space, So yeah, to your point, there's a clear divergence of which products CIOs want to use and which ones they no longer want in their stack. >>Yeah, the database market is very much now fragment that it used to be in an Oracle db two sequel server. As you mentioned, you got a lot of choices. The Amazon. I think I counted, you know, 10 data stores, maybe more. Dynamodb Aurora, Red shift on and on and on. So a really interesting space, a lot of activity in that new workload that I'm talking about taking, Ah, analytic databases, bringing data science, pooling into that space and really driving these real time insights that we've been reporting on. So that's that's quite an exciting space. Let's talk about this whole workflow. I t s m a service now. Just just announced, uh, we've been consistently crushing it. The Cube has been following them for many, many years, whether, you know, from the early days of Fred Luddy, Bruce Lukman, the short time John Donahoe. And now Bill McDermott is the CEO, but consistent performance since the AIPO. But what are we actually showing here? Saga? Yeah, You bring up that slot. Thank you. >>So our key take away on kind of the i t m m i t s m i t workflow spaces. Look, it's best in breed, which is service now, or some of the lower cost providers. Right There's really no room for middle of the pack, so >>this is an >>interesting charts. And so what you're looking at here, there's a few directives, so kind of walk you through it and then I'll walk through. The actual results is we're looking within service now accounts. And so we're seeing how these companies are doing within or among customers that are using service. Now, today, where you're looking at on the ex, access is essentially shared market share our shared customers, and then on the Y axis you're seeing essentially the spend velocity off those vendors within service. Now's outs, right? So if the vendor was doing well, you would see them moving up into the right, right? That means they're having more customer overlap with service now, and they're also accelerating Spend, but you can see if you will get zendesk. If you look at BMC, it's a managed right. You can see there either losing market share and spend within service now accounts or they're losing spend right and zendesk is another example Here, Um, and what's actually interesting is, and we've had a lot of anecdotal evidence from CIOs is that look they start with service. Now it's best in breed, but a few of them have said, Look, it's got expensive, Um, and so they would move over Rezendes. And then they would look at it versus a conference that last year, and we had a few CEO say, Look at last quarter of the price of zendesk. Andi moved away from Zendesk and subsequently well, with last year. And so it's just it's interesting that, you know, during these times where you know CIOs are reducing their budgets on that look, it's either best of breed or low cost. There's really no room in the middle, and so it's actually kind of interesting. In this space, it's It's an interesting dynamic and being usually it's best of breed or low cost. Rarely do you kind of see both win, and I think that's what kind of makes the space interesting. >>I've been following service now for a number of years. I just make a few comments there. First of all, you know, workday was the gold standard in enterprise software for the longest time and, you know, company and and and I I always considered service now to be kind of part of that you know Silicon Valley Mafia with Frank's Loop. But what's happened is, you know, Sluman did a masterful job of identifying the total available market and executing with demand, and now you know, his successors have picking it beyond there. You know, service now has a market cap that's not quite double, but I mean, I think workday last I checked was in the mid thirties. Service now is market valuation is up in the 60 billion range. I mean, they announced, um uh, just recently, very interestingly, they be expectations. They lowered their guidance relative to consensus guide, but I think the street hose, first of all, they beat their numbers and they've got that SAS model, that very predictable model. And I think people are saying, Look there, just leaving meat on the bone so they can continue to be because that's been their sort of m o these last several years. So you got to like their positioning and you get to talk to customers. They are pricey. You do hear complaints about that, and they've got a strong lock spec. But generally I got my experiences. If people can identify business value and clear productivity, they work through the lock in, you know, they'll just fight it out in the negotiations with procurement. >>That's right, and two things on that. So with service now and and even Salesforce, right, they are a platform like approach type of vendors right where you build on them. And that's what makes them such break companies, right? Even if they have, you know, little nicks and knacks here and there. When they report people see past that right, they understand their best of breed. You build your companies on the service now's and the sales forces of the world. And to the second point, you're exactly right. Businesses want to maintain consistent productivity on, and I think that, you know, is it kind of resonates with the theme, right, doubling down on Cloud and sas. Um, as as you have all this remote work, as you have kind of, you know, questionable are curating marquee a macro environment organizations want to make sure that their employees continue to execute that they're generating consistent productivity. And using these kind of best of breed tools is the way to go. >>It's interesting you mentioned, uh, salesforce and service now for years I've been saying they're on a collision course we haven't seen yet because they're both platforms. I still, uh I'm waiting for that to happen. Let's bring up the next card and let's get into networking way talk. Um Ah. Couple of weeks ago, about the whole shift from traditional Mpls moving to SD win. And this sort of really lays it out. Take us through the data here, please. >>Yeah, no problem. So we're just looking at a handful of vendors here. Really? We're looking at networking vendors that have the highest adoption rates within cloud accounts. And so what we did was we looked inside of aws azure GCC, right. We essentially isolated just those customers. And then we said which networking vendors are seeing the best spend data and the most adoptions within those cloud accounts. And so you get you can kind of see some, uh, some themes here, right? SD lan. Right. You can see Iraqi their VM. Where nsx. You see some next gen load balance saying are they're on the cdn side right then. And so you're seeing a theme here of more next gen players on You're not really seeing a lot of the mpls vendors here, right? They're the ones that have more flattening, decreasing and replacing data. And so the reason just kind of going on this slide is you know, when you kind of think about the networking space as a whole, this is where adoptions are going. This is this is where spends billing and expanded, arise it. And what we just talked about >>your networking such a fascinating space to me because you got you got the leader and Cisco That has helped 2/3 of the market for the longest time, despite competitors like Arista, Juniper and others trying to get in the Air Force and NSX. And the big Neisseria acquisition, you know, kind of potentially disrupted that. But you can see, you know, Cisco, they don't go down without a fight. And ah, there, let's take a look at the next card on Cdn. You know, this is interesting. Uh, you know, you think with all this activity around work from home and remote offices, there's a hot area, But what are we looking at here? >>Yeah, no problem. And that's right, right? You would think. And so we're looking at Cdn players here you would think with the uptake in traffic, you would see fantastic. That scores right for all the cdn vendor. So what you're looking at here and again there's a few lenses on here, so I kind of walk. You kind of walk the audience through here is first we isolated only those individuals that were accelerating their budgets due to work from home. Right. So we've had this conversation now for a few weeks where support employees working from home. You did see a decent number of organizations. I think it was 20 or 30% of organizations at the per server that indicated they're actually accelerate instead. So we're looking at those individuals. And then what we're doing is we're seeing how are how's Cloudflare and aka my performing within those accounts, right? And so we're looking at those specific customers and you could just see within Cloudflare and we practice and security and networking which by more the Cdn piece, How consistent elevated the date is right? This is spend in density, right? Not overall market share is obviously aka my you know, their brand father CD ends. They have the most market share and if you look at optimized to the right. Now you can see the spend velocity is not very good. It's actually negative across boats sector. So you know it's not. We're not saying that. Look, there's a changing of the guard that's occurring right now. We're still relatively small compared talk my But there's just such a start on trust here and again, it kind of goes to what we're talking about. Our macro themes, right? CIOs are continuing to invest in next gen Technologies, and better technologies on that is having an impact on some of these legacy. And, you know, grandfather providers. >>Well, I mean, I think as we enter this again, I've said a number of times. It's ironic overhead coming into a new decade. And you're seeing this throughout the I T. Stack, where you've got a lot of disruptors and you've got companies with large install bases, lot of on Prem or a lot of historical legacy. Yeah, and it's very hard for them to show growth. They often times squeeze R and D because they gotta serve Wall Street. And this is the kind of dilemma they're in, and the only good news with a comma here is there is less bad security go from negative 20% to a negative 8% net score. Um, but wow, what a what a contrast, but to your point, much, much smaller base, but still very relevant. We've seen this movie before. Let's let's wrap with another area that we've talked about. What is virtualization? Desktop virtualization? Beady eye again. A beneficiary of the work from home pivot. Um, And we're focused here, right on Fortune 500 net scores. But give us the low down on this start. >>Yeah, So this is something that look, I think it's it's pretty obvious to into the market you're seeing an uptake and spend across the board versus three months ago in a year ago and spending, etc. Among your desktop virtualization players, there's FBI, right? So that's gonna be your VPN right now. Obviously, they reported pretty good numbers there, so this is an obvious slide, but we wanted to kind of throw it in there. Just say, look, you know, these organizations are seeing nice upticks incent, you know, within the virtualization sectors, specifically within Fortune 500 again, that's kind of, you know, work from home spend that we're seeing here, >>right? So, I mean, this is really a 100% net score in the Fortune 500 for workspaces is pretty amazing. And I think the shared in on this that the end was actually quite large. It wasn't like single digits, Many dozens. I remember when Workspaces first came out, it maybe wasn't ready for prime time. But clearly there's momentum there, and we're seeing this across the board saga. Thanks so much for coming in this week. Really appreciate it. We're gonna be in touch with with you with the TR. We're gonna continue to report on this, but start Dr stay safe. And thanks again. >>Thanks again. Appreciate it. Looking for to do another one. >>All right. Thank you. Everybody for watching this Cube insights Powered by ET are this is Dave Volante for Dr Sadaaki. Remember, all these episodes are available as podcasts. I published weekly on wiki bond dot com Uh, and also on silicon angle dot com Don't forget tr dot Plus, Check out all the action there. Thanks for watching everybody. We'll see you next time. Yeah, yeah, yeah, yeah, yeah

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. Hello, everyone, and welcome to this week's Cuban sites, powered by ET are in this breaking analysis, we want to accomplish three things. First thing I'll do is we'll recap the current spending outlook. Next, we want to share some of the priorities and sentiments and the outlook that we're hearing from leading tech execs that we've been interviewing in the past couple of weeks on the remote cube. And finally, we'll take a look at really what's going on in the market place, a little bit of a look forward and what we expect in the coming weeks and months ahead. Now, as you know, E. T. R was really the first to quantify with real survey data the impact of covert 19 on I t spend. So I just want to review that for a moment. This CTR graphic right here shows that results from more than 1200 CIOs and I T practitioners. That shows that they expect their I t spending how they're they're spending on the change in 2020 now, look at the gray bar shows a very large number of organizations that they're plowing ahead without any change. In overall, I spend about 35% now shown in the green bars before 21% of respondents are actually increase their budgets this year. And the red bars, of course, they show the carnage. Really, 28% of customers are expecting a decrease of more than 10% year on year. Now, as we've reported, the picture would look a lot worse were it not for the work from home infrastructure, offset by E spending on collaboration tools and related networking security. VPN, VD I interest infrastructure, etcetera. Now remember each year launched this survey on March 11th and ran it through early April. So it caught the change in sentiment literally in real time on a daily basis. And that's what I'm showing here in this graphic. What it does is it overlays key events that occurred during that time frame and what E. T. R did was they modeled and rear end the data excluding the responses prior to each event. So, of course, the forecast got progressively worse over time. But as you can see on the Purple Line. There was a little bit of an uptick in sentiment from the stimulus package, and it looked like, you know, there's another. It looks like there's another economic cash injection coming soon. Now, as we've reported, the card forecast calls for around 4% decline in I t spend from 2020. That's down from plus 4% prior to Corona virus. It's ER has now entered its self imposed quiet period for two weeks. But what we're doing here is showing some of the sectors that we're watching closely for big changes. We're gonna drill into these over the next several weeks. Now, of course, is we've reported we're seeing a substantial cut in I t spend across the board. Capex will be down. We would expect sectors like I t consulting and outsourcing to be way, way down as organizations put a lot of projects on the back burner. But there are bright spots is shown here in the green. One that we really haven't highlighted to date is cloud really haven't dug into that and also data center related services around Cloud Cloud, we think, is definitely going to remain strong and these related services to get connect clouds via Coehlo services and really reducing latency across clouds and on Prem, we think will remain strong. Now I want to shift gears a little bit and talk about some of the learnings and takeaways from our conversations with CSOs over the past couple of weeks. One of the great things about the Cube is we get to build relationships with many, many people. Over the past 10 years, I've probably personally interviewed close to 5000 people, so we've reached out to a number of those execs over the last couple of weeks to really try and understand how they're managing through this cove in 19 Crisis. So let me summarize just some of the things that we heard. And then I'll let the execs speak to you directly first, of course, like tech execs, are there half full people perpetual optimist, if you will. It was interesting to hear how many of the people that I spoke with, that they actually had early visibility on this crisis. Why? Because a lot of our operations, we're actually in China and other parts of Asia, so they saw this coming to an extent, and they saw it coming to the U. S. And so you know, there were somewhat ready and you're here. They all had on air of confidence about their long term viability and putting their put their employees ahead of profits. But the same time, once they see that their employees are okay, they want to get them focused and productive. Now what they've also done is they've increased the cadence and the frequency of their communications. Yeah, and most, if not all, are trying to get back with a free no strings attached software and other similar programs. But the bottom line is, they really don't know what's coming. They don't know when this thing will end. They don't know what a recovery really is gonna look like when people are going to feel safe traveling again what the overall economic impact is gonna be. So I think it's best summarized to say they're hoping for the best, but planning for the worst. But let's listen to this highlight clip that we put together of five execs that I talked to along with John Furrier Melissa DiDonato of Susa. Frank Sluman, who had snowflake and he's formerly the chairman and CEO of service. Now Jeremy Burton is the CEO of a company called Observe. He used to be the CMO of Dell and EMC. Before that, brand products Sanjay Poonam as the CEO of VM Ware and ST ST Vossen heads up Cisco's collaboration business. Roll the clip. >>What keeps me up at night now and how I wake up every morning is wondering about the health of my employees, that a couple of employees, one that was quite ill in Italy. We were phoning him and calling and emailing him from his hospital bed. And that's what's really keeping me going. What's inspiring me to leave this incredible company is the people and the culture that they built that I'm honoring and taking forward as part of the open source value system. My first movers, Let's not overreact. Take a deep breath. Let's really examine what we know. Let's not jump to conclusions. Let's not try to project things that were not capable of projecting death hard because, you know, we tend to have sort of levels off certainty about what's gonna happen in the next week in the next month, and so on. All of a sudden that's out of the window creates enormous anxiety with people. So, in other words, you've got a sort of a reset to Okay, what do we know? What can we do? What we control, Um, and and not let our minds sort of, you know, go out of control. So I talk to are people time of maintain a sense of normalcy focused on the work. Stay in the state in the moment. And ah, I don't turn the news feed off. Right, Because the hysteria you get through that through the media really not helpful. Just haven't been through, you know, a couple of recessions where, you know, we all went through 9 11 You know, the world just turn around and you come out the other side. And so the key thing is, you said it very much is a cliche, but you gotta live in the moment. What can I do right now? What can I affect right now? How can I make sure that you know what I'm working on is a value for when we come out the other side. And when you know more code balls come along. I think you'd better reason about that with the best information you have at the time. I always tell people the profits of VM Ware wheat. If you are not well, if your loved ones not well, if you take a picture of that first, we will be fine. You know this to show fast, but if you're healthy, let's turn our attention because we're not going to just sit in a little mini games. We're gonna so, customers, How do we do that? A lot of our customers are adjusting to this pool, and as a result they have to, you know, either order devices, but the laptop screens things were the kinds to allow work for your environment to be as close to productive as they're working today. I do see some, some things coming. Problem right? Do I expect the volumes off collaboration to go down? You know, it's never going to go back to the same level. The world as we know it is going to change forever. We are going to have a post code area, and that's going to be changed for the better. There's a number of employees who have been skeptical, reticent, working from home were suddenly going to say just work from home. Thing is not so bad after all. >>So you can hear from the execs who all either currently or one point of lead large companies in large teams. They're pretty optimistic now. The other thing that's Lukman told me, by the way, is he approves investments in engineering with no qualms because that's the future of the company. But he's much more circumspect with regard to go to market investments because he wants to see a high probability of yield from the sales teams before making investments there. I also want to share some perspectives that I've learned from small early stage companies, and we've all seen the Sequoia Black Swan memo and you might remember there onerous rest in peace, good times the alert that they put out in 2008. It basically they're essentially advising companies to stop spending on non essential items. By the way, another slew of society also somewhat scoffed at this advice, and he told me on the Cube, you should always stop spending money on non essential items. At any rate, I've talked to a number of early stage investors and portfolio companies, and I'll share a little bit of their play Bach playbook that they're using during this crisis, and it might have some value to the cut, cut cut narrative that you're hearing out there. I think the summary for these early stage startups is first focus on those customers that got you to where you are today. In other words, don't lose sight of your core. The second thing is, try to hone your go to market and align it with current conditions. In other words, paint a picture of the ideal customer and the value proposition that you deliver specifically in the context of the current market. The third thing is, they're updating their forecast more frequently and running sensitivity analysis much more often so that they can better predict outcomes. I e. Reset. You're likely best case and worst case models. The third is essentially reset your near term and midterm plans and those goals and re balance your expense portfolio to reflect these new targets. And this is important by the way, to communicate to your investors. When I've seen is those companies with annual recurring revenue there actually in pretty good shape, believe it or not, in almost all cases, I've seen targets lowered. But there are some examples of startups that are actually increasing their outlook. Think, Zoom, even those who is not a startup anymore. But generally I've seen resets of between 5 to 10% downward, which you know what often is in pretty much in line with the board level goals. And I've seen more drastic reductions as well of up to 50% now. So we've heard some pretty good stories from larger tech companies and some of these VC funded startups. Now I want to talk about small business broadly and what we're hearing from small business owners and also the banks that serve them. Look, I'm not going to sugar coat this many small businesses, as you well know, in deep trouble. They're gonna go out of business. They're laying off people on. There are a number of unemployed the aid package that the government's putting forth the small businesses. It's not working its way through the banking system. Not nearly fast enough, despite the Treasury secretaries efforts, The bottom line is banks don't want to make these loans to small businesses. Right now, there's too much that they don't understand. They're making no money on these loans they're being overwhelmed with. Volume will give you some examples. Bank of America, when the small business payroll program first hit signal that would Onley help companies with both ah banking relationship and an existing lending relationship with the bank UPS is another example said it was only gonna directly help companies with over 500 employees. And for small businesses, it was outsourcing that relationship to another firm, which, of course, meant you had to go through a new rectal exam, if you will, with that new firm. In a way, you can't blame the banks. They're being asked to execute on these programs without clear guidance on how they're supposed to enforce guidelines. And what happens if they make a mistake? Is the federal government gonna pull their guaranteed backing? What are those guidelines? They seem to be changing all the time. And what's the banks, liability and authority to enforce them? Why don't I spend time talking about this? Well, nearly half of US employees work for small businesses, and nearly 17 million workers as of this date have filed for unemployment, and I'll say the banks got bailed out in the financial crisis of 2008 and they need to step up, period, and the government needs to help them, all right. The other buzz kill data that I want to bring up is our national debt. Now many have invoked that there's no such thing as a free lunch, including the famous Milton Friedman, the Economist who I'm gonna credit. Others have said it, but I'll give it to him. Why? Because he espoused controlling the money supply and letting the market's fix themselves bailouts. The banks, airlines, Boeing, automakers, etcetera, those air antithetical to his underlying philosophy. Currently, the U. S national debt is $24 trillion. That's $194,000. Protects player Americans. Personal debt is now 20 trillion. Our unfunded liabilities, like Social Security, Medicare, etcetera now stands at a whopping 139 trillion. And that equates to about 422,000 per citizen. Think about this. The average liquid savings for US family is 15 K, and the U. S debt is now 111% of GDP. So we've been applying Kenzie and Economics for a while now. I'm gonna say it seems to have been working. Think about the predictions of inflation after the 8 4000 and nine crisis. They proved to be wrong. But my concern is I don't see how we grow our way out of this debt, and I worry about that. I've worried about this for a long time, but look, we're knee deep into it and it looks like there's no turning back so well, I'll try to keep my rhetoric to a minimum and stay positive here because I think there is light at the end of the tunnel. We're starting to see some some good opportunities emerging here just in terms of flattening the curve and the like. One of the things that pretty positive about is there gonna be some permanent changes from Cove it. It's kind of ironic that this thing hit as we're entering a new decade decade and as I said before, I expect digital transformations to be accelerated because of this crisis and the many companies that have talked digital from the corner office. But I haven't necessarily really walked the walk, I think will now I think is going to be more cloud more subscription less wasted labor, more automation, more work from home unless big physical events, at least in the next couple of years. So that's kind of the new expectation. As always, we're going to continue to report from our studios in Palo Alto and Boston, and we really welcome and appreciate your feedback. Remember, these segments are all available as podcasts, and we're publishing regularly on silicon angle dot com and on wiki bond dot com. Check out ctr dot plus for all the spending action, and you can feel free to comment on my LinkedIn post or DME at development or email me at David Volante Wiki. Sorry, David Vellante is silicon angle dot com. This is Dave Volante for the Cube Insights powered by CTR. Thanks for watching everyone. We'll see you next time. >>Yeah, yeah, yeah, yeah.

>> wait. >> Okay, We're back. Live a V M. World twenty twelve. I'm John for the founder's silicon angle dot com. This is the Cube silicon angle dot TV's flagship telecast. We go out to the events and extracted signal from the noise CEOs, entrepreneurs, analysts, marketing people, developers, whoever has the signal, we want extract that share that with you. We have a special guest today. Frank's Leutnant is a sea of service. Now again, I'm John Furry. I'm joined my co host >> of Dave Alonso, a wicked bond dog. Frank, Last time we saw Europe on the stage, you had these glasses on the hat. Remember that, Elwood? So, uh, welcome to the Cube. First time on Thank you. Too many of'Em worlds. I'm sure. A little different angle now. Yeah, Service now. Very exciting. Just went public solving a big problem on DH. Added again? Yes. So tell us. How do you feel? >> That's interesting. A lot of people ask me, how did you end up in, you know, in a in an application software tap a category you spent all this time in storage. The reality is that most of my life, you know, being in the application, development, dusting and system management. So this is actually close to my wheelhouse. Stories was actually a pretty good diversion for me. Careerwise >> service now, relatively, you know, not not a household name but solving that problem. Really, There's no system of record for i t. What activities air doing? Whether it's finance, it's whether it's application portfolio project portfolio. You guys were attacking that whole nut with a software service model. I mean, it used to be a lot of point tools to do that. And you guys seem to be having a lot of success bringing that all to the cloud. >> Yeah, the irony is, is that you look at all the corporate functions, you know, finance, sales, marketing HR, I sort of ranks, you know, last or near last in terms of management sophistication, right compared to the other functional areas, because the most mighty organization have to show for themselves. They helped US management system for their work. For right now, they are to keep track of what's running in their their operation, and that service model is typical of infrastructure providers. Right? You see it, you know, with tell coast like looking t you see it with power. You tell these, like PG and E their infrastructure providers first and the service model. It is not particularly compelling, right? So what we tried to dio it's really take it from a D M V style service model standing in line waiting to be helped. Do you want this more like amazon dot com, where I help myself, It's into it. If it's online, it's productive. It's where I want to go. Teo to make requests as well. Let's receive service >> So you're selling primarily to the organization. Who you sell to in the theory is that the CEO is that the project management offices all the above >> as the servicers management is a very well defined center of responsibility in i t organization. So there's always a group of people who is in charge of that that disciplined. They're easy to find, But CEOs are always involved, and the reason is these air very high profile system rollout because everybody in it is an actor or participant, the workflow as well as the broader employee population, the enterprise, touchy systems, So you better believe that people are sensitive about this being a successful practical and it looks more like a neo system. Dan. It does an infrastructure type system >> without the AARP complexity of it. >> Yes, it's it's a mixed >> metaphor, but so So here are your roughly a hundred fifty million dollar company, you know, annualized, you nice market. >> Either way, we've we've guided to about two. Thirty five, >> thirty five this year. Okay, Great. That's >> want to make sure that their investors don't get >> background. We're sorry about that. Es to thirty five, which is why your market cap about three point six billion. I think >> way had about ninety eight percent growth and buildings in the last quarter. So the high growth, obviously it's what drives >> what's driving that. So how big is the business that you guys playing? What's your tan? >> So we think that the tam just for the narrow definition around service management is a is a multi billion dollar opportunity Because of the nature ofthe work flows, we're also expanding into the operations management area. Right? This is this is where HP lives and BMC and IBM and CIA with these very large open view Tivoli Well, because their work flows between services system management are all becoming integrator that used to be suffered spheres. Not anymore. >> And that's an enormous market. >> It i d. C. Thanks. It's about a thirteen fourteen doing dollar market, and then you have the platform is a service opportunity because our customers have just gone wild, building all kinds of spoke applications on a platform just because they could. So >> you kind of betting on the intersection of systems management, operations, management >> and the platform. >> Okay, and it's kind of jump ball, really, with the dynamic of the cloud coming in, isn't it? In terms of the competitive, it's >> Ah, it's interesting because we look another assassin categories like HR marketing. You see a whole host of players you're looking in our category on the only breakout play there has been serviced now way have predominately compete against legacy vendors, people that I just mentioned. So >> you've got some experience doing that I want >> I want to ask you about the discipline side of the market. You guys are public companies, so yeah, you're out there is all exposed and then talk about some of the product directions because out yesterday they were really showcasing the vision within VM where old way a new way, a access APS infrastructure. You know the classic in the old way. New Way, Modern era. We've been calling it in your world. You're actually replacing some pretty old stuff. I mean, I remember back in the late eighties, early nineties health testing people had that's headsets on and, you know, homegrown software developers and quit a lot of this legacy kind of mindset. So first question is, Is that true? Is there still that much baggage in that services business? From an infrastructure standpoint? And the second part, the question is, what's the new stuff that's really disrupting the market? So in the new way, what is the key features that that's happening in the services industry? >> So, you know, I already started to allude to it, right. So you want to evolve that service model from that help death centric DNP style of service experience to one that's on the line looks more consumer style. You know, the way we've learned from Apple and Yahoo and Google and people like that help yourself. If you have a problem at home with your apple TV, you're really gonna try and call Apple know you're going to go online and you find years of communities you get Teo answers ten times faster, that weight and then following these needy old models the way you reference there is an awful lot of that still living in the world off because they're focuses infrastructure, not service. That's change it, right? I mean, CEOs, I read somewhere, have a shelf life of about eighteen months, right? There's incredible impatience and dissatisfaction with how that function is running. It's costing too much money in the service is not exactly to to write home about. People are really ready to move their service malls. >> The largest answer was, Just hire someone else to do it. That was the outsourcing boom, right? So that's still brought problems, right? Legacy. So how is that still in play? So if the notion is okay, outsource it, and then the outsources has some warts on it that's got to be tweaked. What's the new version? Because you know amazon dot com and you know this new environment availability, instant access, the information we don't service etcetera is that changing it >> way believed that the move to cloud computing is really going to change the role of the CIA, all right, because infrastructure is going to become something that's behind Courtney, and it's becoming less of an infrastructure centric job. CEOs and T organizations become Mohr service engineering organizations, people that understand work flows. People understand how to automate work, flows right out. And, you know, I know how to run a database or a network or, you know, all the security dimensions and so on because we're just breaking as an industry. There just isn't enough competency and skill sets for everybody to be confident at the level that we need to be at structure. It's not scaling, right. It's sort of the way telephone switching centers were in the nineteen fifties >> means one of those things to with the CIA. Attention, I'LL get to that later. But now, with big data in real time analytics is more pressure on the service delivery side. As a business driver, you seeing that pressure as well, or is it more? We just gotta fix it now. I got to do it >> Well, nighty organizations in the lift from one crisis to the next, completely event driven, you know we haven't out its were all over it. Trying to restore service on DH. You know, we sort of live that life day in, day out. But I've never changes right So waken get ahead of this game. You know, if we start structuring, you know, the interaction model that we have with our users how we communicate with them. I mean, simple things, right when you were, you haven't out it. It would be helpful if we were able to pull status. You know, every twenty minutes us to what? What we're doing, What's going on. Right? But having infrastructure be ableto push data out? No, like that. Most organizations don't do that. They live pretty much in the dark, >> so share with our audience out there. That's watching. We have a lot of professionals and data scientists and analyst type audience that we've that we've that follows. Looking angle with Yvonne on DH. Some CEOs as well on early adopters share the folks out there. The pitch, How bad is it that their environment and how easy is it to change? It is just a norther. A magnitude sense of is a turnkey. How do you guys roll in? What's he engagement look like? It's not as hard as the things that most people might have the opinion. I don't want to get just ugly. It's painful or is it not painful? Is it quick pop now? Is it like how fast a roll in and out the infrastructure that you >> the's are extraordinarily sticky systems the system that were that we replace >> your systems of the old systems. >> The old systems are on the reason that they've been around for ten, fifteen years. They're very difficult to replace. And if you look at our girls, that's certainly testament to our compelling. The value proposition has been people have said, you know, a pain is becoming unbearable and be the view of the promised Land is looking pretty good, right? So there's both an incentive to change and to move, and secondly, there is something to move towards that is this compelling inspiring. And it really is going to change my game right, because now we tell people said, Look, if you just tryingto get to a snazzier, more modern help desk, we're not your guy, okay? Because we don't find out a compelling vision of the world. We wantto wholesale transform how you deliver service just >> take us to some of those cats you were talking before you came on about your growth tripling inside. But talk about a zoo company, which is a whole nother conversation. We could talk about it yet you have expertise in, but talk more about the customer deployments. You got some fresh funding with the AIPO. You're geared up. You go out to the market place. What are the conversations like, What are some of the stats and one of the conversation with the CIA? >> Well, the CIA is obviously are interested, first and foremost of the transformation of the service model, right? I mean, we have to get Teo service experience that's more reminiscent of people experience on the consumer side. Now we typically have to do that, that an economic equation that's very similar to what they're having right now. They're not interested in spend more. They just want to get completely refreshed, you know, platform for similar amounts of money that they're already spending because Versace, you know, we're not just taking the software, not off the after after table. We're also taking the entire infrastructure, all the operating staff, everything it takes to run that environment becomes ours, right? It's no longer in the I T department, so that looks pretty compelling to them. >> How about some of the numbers in terms of uptake with customers recently? What's the growth rate was? Can you share some numbers? >> Way have about twelve hundred price customers? We had about one hundred twenty seven the last quarter. That's that is a huge number of customers. Tio Tio ad we have. Most of our focus is on global two thousand enterprises. We have about two hundred thirty global two thousand enterprises, and they're all you know who's who names that, that people recognize Starting up Ticket's been been strong. We're running very, very hard to make sure that we have two services infrastructure. Both there's people and infrastructure to be able to accommodate that. >> Well, I'm excited to interview you because I want to ask you kind of more of a personal question. And although we just met for the first time here, your name's been kicked around as kind of a maverick operational executive who knows how to scale organization. So we're in kind of living in an era where the business value focused, whether startups and has been a lot of talk about, you know, the Facebook idea, the young kids under thirty running a billion dollar market gap, companies trying to actually move from hyped to real scale. And Palmer. It's made a comment yesterday kind of dissing Facebook of in terms of the value proposition relative to say, you know, bm where. But the question I want to ask you is, um, what's your success model for scaling an organization on DH for the younger execs out there? And for people who don't know you just chairs up on the camera? What's your philosophy as the repeatable sales, lower cost leverage model? I mean variety of different kind of ingredients. What's the Franks Lukman formula for success and scaling? Bringing a product to market and growing it? >> Well, the first order of business for for a start up venture of any sort is growth. I find that a lot of people come on a business school in trying to balance girl for profitability. Um, that mentality makes no sense to me, right? It's economics. Before accounting, accounting becomes the bastardization of economics, we run our ventures cash on booking their economic concepts, not accounting constructs, right people are trying to show profit prematurely when they can invest that money to grow. We tripled our head count over the last year. We got very far over our skis. No, we're burning a hole in our gas pals but were very clear with investors that look, we are still increasing our productivity for head. Why, when we apply to resource is to grow this franchise Growth expands our multiples, expands valuation. That's what everybody is in the business for, so so sort of summarize. Knowing your question. Most people hold back on growth, and they don't really know why they're not all out trying to drive growth and the reason that growth is so important. You need to be a breakout player. Nobody wants to be the in between player. That's neither fish nor fowl and doesn't become a dominant entity into space that it wants to be in >> and have the financing in the dry powder behind you that you were a venture capital Greylock, which no something into about investing. So that's also important part right? >> Well, you don't. That's why I said to you manage on cash you managed on bookings. Those are the economics in the business essentially, >> and you've been looking up, have some really good finances behind you, trust you who get the concepts and that's key well, continue in the right >> way went public. We also explain to investors Look, this is what we're trying to do, and this is what we need you to buy into. Otherwise, find somebody else's talk. So >> what is the going public affect? You know the perception amongst the CEO's when you chose to list on the way we had them on earlier this week? But how is that affected? The brand perception? >> That was the whole reason for us to go public, right? We didn't need to cash liquidity. Obviously, it's good for employees and investors when I pose fundamentally a branding event. You know, I used the analogy. We went from playing on Saturday to playing on Sunday. You know, all of a sudden you know you're transparent, you know, all the all the thud that gets spread about you by competition. People cannot punch you up on Iand. See what the truth is around your balance sheet. You know how abot your last quarter was? It's been three. I po was tremendous for us from a branding standpoint, >> and you've been known Teo have a reputation of really getting the product in this case, the service, right? And then really getting aggressive on the sales side. Can you talk about what you've done in the sales side? I know you've aggressively hired. >> Yeah, we You know, as I said, we tripled our head count. We went from three shells. Reasons to twelve insight. One year we spread out all over Europe today. This is a ground war. You need an army to fight it. This is not Facebook. We cannot sign up annoying people in a week. It is a business that runs over the ground so you cannot scale and drive growth business unless you have two people to run it. >> And you're selling belly to belly. That right? Absolutely. So you know, >> we're going through the front door of the elevator >> way. Okay, We're getting the hook here. We're getting hooked, but I have to quit final questions. One is just put a plug out there for service's angle dot com that Silicon Angles separate publication. We launched last year, thanks to E m. C. For helping us sponsor that but really dedicated to the new era of services. And there is some disruption. We're excited to cover you guys, so I just wanted to say Go, go check out sources angle. So Franklin asked two questions. One. What's the big disruption in the services business that most people aren't getting right now? General, you know, man and tech on the street, not the insider inside the ropes. So that's the first question. The second question. What's your goals for the year? For the business? >> Well, the interesting thing about the services business is how it's one of these areas that is sort of the least automated. Write. It runs on the concept of institutional knowledge. Phone conversations, informal communications, email and the frontier in service management is that those become software automated structure processes that is not just happening in I t able sticks. It's happening everywhere, right? What do you want to request? Food. You know, from the hotel you knew what a Virgin America, right? You know, request from your seat, something that's just, you know, on an example of how >> that's the story, you know, debate about that. >> That's how it's gonna go, right? So services it's going to become, really that I call the service fabric right? Essentially how thes processes get conducted. So we're super excited because our platform sits right in the middle of that trend and we're going to try and make that trend. >> It's eleven. Platform to the economics are fantastic and no real customs agents were brought up exactly so good margins. >> And it's just >> like the stock immediately. >> It's much more scalable in the district. Disintermediation. You know, all the all the manual effort goes into this. >> Okay, so now I know your public CEO and everything now, so you really can't be as wild as you could have you a private. But what's the outlook for year? Your personal goals for the year >> Wait, given guns from or get one quarter for years. So check with your favorite analysts. >> Okay? Growth is on the horizon. Congratulations. Frank's been great to have your leadership in the Cube. Thank you. Time Cuban great to have you. This is silicon angle dot coms. The cube will be right back with our next guest, Cynthia Stoddard from Netapp CIA, Another CIA. We're gonna get into the trenches and hear about the transformation again. We'LL be right back