(upbeat music) >> Announcer: Live from Munich, Germany, it's the Cube covering DataWorks Summit Europe, 2017. Brought to you by Hortonworks. >> Hey, welcome back everyone. We're here live in Munich, Germany, at the DataWorks 2017 Summit. I'm John Furrier, my co-host Dave Vellante with the Cube, and our next two guests are Gianthomas Volpe, head of customer development e-media for Alation. Welcome to the Cube. And we have Bertrand Cariou, who's the director of solution marketing at Trifecta with partners. Guys, welcome to the Cube. >> Thank you. >> Thank you for having us. >> Big fans of both your start-ups and growing. You guys are doing great. We had your CEO on our big data SV, Joe Hellerstein, he talked about the rang, all the cool stuff that's going on, and Alation, we know Stephanie has been on many times, but you guys are start ups that are doing very well and growing in this ecosystem, and, you know, everyone's going public. Cloud Air has filed their S1, great news for those guys, so the data world has changed beyond Hadoop. You're seeing it, obviously Hadoop is not dead, but it's still going to be a critical component of a larger ecosystem that's developing. You guys are part of that. So I want to get your thoughts of why you're here in Europe, okay? And how you guys are working together to take data to the next level, because, you know, we're hearing more and more data is a foundational conversation starter, because now there's other things happening, IOT, business analysts, you guys are in the heart of it. Your thoughts? >> You know, going to be you. >> All in, yeah, sure. So definitely at Alation what we're seeing is more and more people across the organization want to get access to the data, and we're kind of breaking out of the traditional roles around IP managing both metadata, data preparation, like Trifecta's focused on. So we're pretty squarely focused on how do we bring that access to a wider range of people? How do we enable that social and collaborative approach to working with that data, whether it's in a data lake so, or here at DataWorks. So clearly that's one of the main topics. But also other data sources within the organization. >> So you're freeing the data up and the whole collaboration thing is more of, okay, don't just look at IT as this black box of give me some data and now spit out some data at me. Maybe that's the old way. The new way is okay, all of the data's out there, they're doing their thing, but the collaboration is for the user to get into that data you know, ingestion. Playing with the data, using the data, shaping the data. Developing with the data. Whatever they're doing, right? >> It's just bringing transparency to not only what IT is doing and making that accessible to users, but also helping users collaborate across different silos within an organization, so. We look at things like logs to understand who is doing what with the data, so if I'm working in one group, I can find out that somebody in a completely different group in the organization is working with similar data, bringing new techniques to their analysis, and can start leveraging that and have a conversation that others can learn from, too. >> So basically it's like a discovery platform for saying hey, you know, Mary in department X has got these models. I can leverage that. Is that kind of what you guys are all about? >> Yeah, definitely. And breaking through that, enabling communication across the different levels of the organization, and teaching other people at all different levels of maturity within the company, how they can start interacting with data and giving them the tools to up skill throughout that process. >> Bertrand, how about the Trifecta? 'Cause one of the things that I find exciting about Europe value proposition and talking to Joe, the founder, besides the fact that they all have GitHub on their about page, which is the coolest thing ever, 'cause they're all developers. But the more reality is is that a business person or person dealing with data in some part of a geography, could be whether it's in Europe or in the US, might have a completely different view and interest in data than someone in another area. It could be sales data, could be retail data, it doesn't matter but it's never going to be the same schema. So the issue is, got to take that away from the user complexity. That is really fundamental change. >> Yeah. You're totally correct. So information is there, it is available. Alation helps identify what is the right information that can be used, so if I'm in marketing, I could reuse sales information, associating maybe with web logs information. Alation will give me the opportunity to know what information is available and if I can trust it. If someone in finance is using that information, I can trust that data. So now as a user, I want to take that data, maybe combine the data, and the data is always a different format, structure, level of quality, and the work of data wrangling is really for the end user, you can be an analyst. Someone in the line of business most of the time, these could be like some of the customers we are here in Germany like Munich Re would be actuaries. Building risk models and or claimed for casting, payment for casting. So they are not technologies at all, but they need to combine these data sets by themselves, and at scale, and the work they're doing, they are producing new information and this information is used directly to their own business, but as soon as they share this information, back to the data lake, Alation will index this information, see how it is used, and put it to this visibility to the other users for reuse as well. >> So you guys have a partnership, or is this more of a standard API kind of thing? >> So we do have a partnership, we have plan development on the road map. It's currently happening. So I think by the end of the quarter, we're going to be delivering a new integration where whether I'm in Alation and looking for data and finding something that I want to work with, I know needs to be prepared I can quickly jump into Trifecta to do that. Or the other way around in Trifecta, if I'm looking for data to prepare, I can open the catalog, quickly find out what exists and how to work with it better. >> So basically the relationship, if I get this right is, you guys pass on your expertise of the data wrangling all the back processes you guys have, and advertise that into Alation. They discover it, make it surfaceable for the social collaboration or the business collaboration. >> Exactly. And when the data is wrangled, it began indexed and so it's a virtual circle where all the data that is traded and combined is exposed to the user to be reused. >> So if I were Chief Data Officer, I'd say okay, there's three sequential things that I need to do, and you can maybe help me with a couple of them. So the first one is I need to understand how data contributes to the monetization of my company, if I'm a public company or a for profit company. That's, I guess my challenge. But then, there are other two things that I need to give people access to that data, and I need quality. So I presume Alation can help me understand what data's available. I can actually, it kind of helps with number one as well because like you said, okay, this is the type of data, this is how the business process works. Feed it. And then the access piece and quality. I guess the quality is really where Trifecta comes in. >> GianThomas: Yes. >> What about that sequential flow that I just described? Is that common? >> Yeah >> In your business, your customer base. >> It's definitely very common. So, kind of going back to the Munich Re examples, since we're here in Munich, they're very focused on providing better services around risk reduction for their customers. Data that can impact that risk can be of all kinds from all different places. You kind of have to think five, ten years ahead of where we are now to see where it might be coming from. So you're going to have a ton of data going in to the data lake. Just because you have a lot of data, that does not mean that people will know how to work with it they won't know that it exists. And especially since the volumes are so high. It doesn't mean that it's all coming in at a greatly usable format. So Alation comes in to play in helping you find not only what exists, by automating that process of extraction but also looking at what data people are actually using. So going back to your point of how do I know what data's driving value for the organization, we can tell you in this schema, this is what's actually being used the most. That's a pretty good starting point to focus in on what is driving value and when you do find something, then you can move over to Trifecta to prepare it and get it ready for analysis. >> So keying on that for a second, so in the example of Munich Re, the value there is my reduction in expected loss. I'm going to reduce my risk, that puts money in my bottom line. Okay, so you can help me with number one, and then take that Munich Re example into Trifecta. >> Yes, so the user will be the same user using Alation and Trifecta. So is an actuary. So as soon as the actuary items you find the data that is the most relevant for what you'll be planning, so the actuaries are working with terms like development triangles over 20 years. And usually it's column by column. So they have to pivot the data row by row. They have to associate that with the paid claims the new claims coming in, so all these information is different format. Then they have to look at maybe weather information, or additional third party information where the level of quality is not well known, so they are bringing data in the lake that is not yet known. And they're combining all this data. The outcome of that work, that helps in the Reese modeling so that could be used by, they could use Sass or our older technology for the risk modeling. But when they've done that modeling and building these new data sets. They're, again, available to the community because Alation would index that information and explain how it is used. The other things that we've seen with our users is there's also a very strong, if you think about insurances banks, farmer companies, there is a lot of regulation. So, as the user, as you are creating new data, said where the data coming from. Where the data is going, how is it used in the company? So we're capturing all that information. Trifecta would have the rules to transform the data, Alation will see the overall eye level picture from table to the source system where the data is come. So super important as well for the team. >> And just one follow up. In that example, the actuary, I know hard core data scientists hate this term, but the actuaries, the citizen data scientist. Is that right? >> The actuaries would know I would say statistics, usually. But you get multiple level of actuaries. You get many actuaries, they're Excel users. They have to prepare data. They have to pin up, structure the data to give it to next actuary that will be doing the pricing model or the next actuary that will risk modeling. >> You guys are hitting on a great formula which is cutting edge, which is why you guys are on the startups. But, Bertrand I want to talk to you about your experience at Informatica. You were the founder the Informatica France. And you're also involved in some product development in the old, I'd say old days, but like. Back in the days when structured data and enterprise data, which was once a hard problem, deal with metadata, deal with search, you had schemes, all kinds of stuff to deal with. It was very difficult. You have expertise. I want you to talk about what's different now in this environment. Because it's still challenging. But now the world has got so much fast data, we got so much new IOT data, especially here in Europe. >> Oh yes. >> Where you have an industrialized focus, certainly Germany, like case in point, but it's pretty smart mobility going on in Europe. You've always had that mobile environment. You've got smart cities. A lot of focus on data. What's the new world like now? How are people dealing with this? What's your perspective? >> Yes, so there's and we all know about the big data and with all this volume, additional volume and new structure of data. And I would say legacy technology can deal as you mentioned, with well structured information. Also you want to give that information to the masses. Because the people who know the data best, are the business people. They know what to do with the data, but the access of this data is pretty complicated. So where Trifecta is really differentiating and has been thinking through that is to say whatever the structure of the data, IOT, Web Logs, Value per J son, XML, that should be for an end user, just metrics. So that's the way you understand the data. The next thing when play with data, usually you don't know what the schema would be at the end. Because you don't know what the outcome is. So, you are, as an end user, you are exploring the data combining data set and the structure is trading as you discover the data. So that is also something new compared to the old model where an end user would go to the data engineer to say I need that information, can you give me that information? And engineers would look at that and say okay. We can access here, what is the schema? There was all this back and forth. >> There was so much friction in the old way, because the creativity of the user is independent now of all that scaffolding and all the wrangling, pre-processing. So I get that piece of the Citizen's Journal, Citizen Analyst. But the key thing here is you were shrecking with the complexity to get the job done. So the question then comes in, because it's interesting, all the theme here at DataWorks Summit in Europe and in the US is all the big transformative conversations are starting with business people. So this a business unit so the front lines if you will, not IT. Although IT now's got to support that. If that's the case, the world's shifting to the business owners. Hence your start up. Is that kind of getting that right? >> I think so. And I think that's also where we're positioning ourselves is you have a data lake, you can put tons of data in it, but if you don't find an easy way to make that accessible to a business user, you're not going to get a value out of it. It's just going to become a storage place. So really, what we've focused on is how do you make that layer easily accessible? How do you share around and bring some of the common business practices to that? And make sure that you're communicating with IT. So IT shouldn't be cast aside, but they should have an ongoing relationship with the business user. >> By the way, I'll point out that Dave knows I'm not really a big fan of the data lake concept mainly because they've turned it into data swamps because IT deploys it, we're done! You know, check the box. But, data's getting stale because it's not being leveraged. You're not impacting the data or making it addressable, or discoverable or even wrangleable. If that's a word. But my point is that's all complexities. >> Yes, so we call it sort of frozen data lake. You build a lake, and then it's frozen and nobody can go fishing. >> You play hockey on it. (laughs) >> You dig and you're fishing. >> And you need to have this collaboration ongoing with the IT people, because they own the infrastructure. They can feed the lake with data with the business. If there is no collaboration, and we've seen that multiple times. Data lake initiatives, and then we come back one year after there is no one using the lake, like one, two person of the processing power, or the data is used. Nobody is going to the lake. So you need to index the data, catalog the data to know what is available. >> And the psychology for IT is important here, and I was talking yesterday with IBM folks, Nevacarti here, but this is important because IT is not necessarily in a position of doing it because doing the frozen lake or data swamp because they want to screw over the business people, they just do their job, but here you're empowering them because you guys are got some tech that's enabling the IT to do a data lake or data environment that allows them to free up the hassles, but more importantly, satisfy the business customer. >> GeanThomas: Exactly. >> There's a lot of tech involved. And certainly we've talked to you guys about that. Talk about that dynamic of the psychology because that's what IT wants. So what's that dev ops mindset for data, data ops if you will or you know, data as code if you will, constantly what we've been calling it but that's now the cloud ethos hits the date ethos. Kind of coming together. >> Yes, I think data catalogs are subtly different in that traditionally they are more of an IT function, but to some extent on the metadata side, where as on the business side, they tended to be a siloed organization of information that business itself kept to maintain very manually. So we've tried to bring that together. All the different parties within this process from the IT side to the govern stewardship all the way down to the analysts and data scientists can get value out of a data catalog that can help each other out throughout that process. So if it's communicating to end users what kind of impact any change IT will make, that makes their life easier, and have one way to communicate that out and see what's going to happen. But also understand what the business is doing for governance or stewardship. You can't really govern or curate if you don't know what exists and what matters to the business itself. So bring those different stages together, helping them help each other is really what Alation does. >> Tell about the prospects that you guys are engaging in from a customer standpoint. What are some of the conversations of those customers you haven't gotten yet together. And and also give an example of a customer that you guys have, and use cases where they've been successful. >> Absolutely. So typically what we see, is that an organization is starting up a data lake or they already have legacy data warehouses. Often it's both, together. And they just need a unified way of making information about those environments available to end users. And they want to have that better relationship. So we're often seeing IT engaged in trying to develop that relationship along with the business. So that's typically how we start and we in the process of deploying, work in to that conversation of now that you know what exists, what you might want to work with, you're often going to have to do some level of preparation or transformation. And that's what makes Trifecta a great fit for us, as a partner, is coming to that next step. >> Yeah, on Mobile Market Share, one of our common customers, we have DNSS, also a common customer, eBay, a common customer. So we've got already multiple customers and so some information about the issue Market Share, they have to deal with their customer information. So the first thing they receive is data, digital information about ads, and so it's really marketing type of data. They have to assess the quality of the data. They have to understand what values and combine the value with their existing data to provide back analytics to their customers. And that use case, we were talking to the business users, my people selling Market Share to their customers because the fastest they can unboard their data, they can qualify the quality of the data the easiest it is to deliver right level of quality analytics. And also to engage more customers. So it was really was to be fast onboarding customer data and deliver analytics. And where Alatia explain is that they can then analyze all the sequel statement that the customers, maybe I'll let you talk about use case, but there's also, it was the same users looking at the same information, so we engage with the business users. >> I wonder if we can talk about the different roles. You hear about the data scientists obviously, the data engineer, there might be a data quality professional involved, there's certainly the application developer. These guys may or may not even be in IT. And then you got a DVA. Then you may have somebody who's statistician. They might sit in the line of business. Am I overcomplicating it? Do larger organizations have these different roles? And how do you help bring them together? >> I'd say that those roles are still influx in the industry. Sometimes they sit on IT's legs, sometimes they sit in the business. I think there's a lot of movement happening it's not a consistent definition of those different roles. So I think it comes down to different functions. Sometimes you find those functions happening within different places in the company. So stewardship and governance may happen on the IT side, it might happen on the business side, and it's almost a maturity scale of how involved the two sides are within that. So we play with all of those different groups so it's sometimes hard to narrow down exactly who it is. But generally it's on the consumptions side whether it's the analyst or data scientists, and there's definitely a crossover between the two groups, moving up towards the governance and stewardship that wants to enable those users or document curing the data for them all the way to the IT data engineers that operationalize a lot of the work that the data scientists and analysts might be hypothesizing and working with in their research. >> And you sell to all of those roles? Who's your primary user constituency, or advocate? >> We sell both to the analytics groups as well as governance and they often merge together. But we tend to talk to all of those constituencies throughout a sales cycle. >> And how prominent in your customer base do you see that the role of the Chief Data Officer? Is it only reconfined within regulated industries? Does he seep into non-regulated industries? >> I'd say for us, it seeps with non-regulated industries. >> What percent of the customers, for instance have, just anecdotally, not even customers, just people that you talk to, have a Chief Data Officer? Formal Chief Data Officer? >> I'd say probably about 60 to 70 percent. >> That high? >> Yeah, same for us. In regulated industries (mumbles). I think they play a role. The real advantage a Chief Data and Analytical Officer, it's data and analytics, and they have to look at governance. Governance could be for regulation, because you have to, you've got governance policy, which data can be combined with which data, there is a lot. And you need to add that. But then, even if you are less regulated, you need to know what data is available, and what data is (mumbles). So you have this requirement as well. We see them a lot. We are more and more powerful, I would say in the enterprise where they are able to collaborate with the business to enable the business. >> Thanks so much for coming on the Cube, I really appreciate it. Congratulations on your partnership. Final word I'll give you guys before we end the segment. Share a story, obviously you guys have a unique partnership, you've been in the business for awhile, breaking into the business with Alation. Hot startups. What observations out there that people should know about that might not be known in this data world. Obviously there's a lot of false premises out there on what the industry may or may not be, but there's a lot of certainly a sea change happening. You see AI, it gives a mental model for people, Eugene Learning, Autonomous Vehicles, Smart Cities, some amazing, kind of magical things going on. But for the basic business out there, they're struggling. And there's a lot of opportunities if they get it right, what thing, observation, data, pattern you're seeing that people should know about that may not be known? It could be something anecdotal or something specific. >> You go first. (laughs) >> So maybe there will be surprising, but like Kaiser is a big customer of us. And you know Kaiser in California in the US. They have hundreds or thousands of hospitals. And surprisingly, some of the supply chain people where I've been working for years, trying to analyze, optimizing the relationship with their suppliers. Typically they would buy a staple gun without staples. Stupid. But they see that happening over and over with many products. They were never able to sell these, because why? There will be one product that have to go to IT, they have to work, it would take two months and there's another supplier, new products. So how to know- >> John: They're chasing their tail! >> Yeah. It's not super excited, they are now to do that in a couple of hours. So for them, they are able, by going to the data lakes, see what data, see how this hospital is buying, they were not able to do it. So there is nothing magical here, it's just giving access to the data who know the data best, the analyst. >> So your point is don't underestimate the innovation, as small as it may seem, or inconsequential, could have huge impacts. >> The innovation goes with the process to be more efficient with the data, not so much building new products, just basically being good at what you do, so then you can focus on the value you bring to the company. >> GianThomas what's your thoughts? >> So it's sort of related. I would actually say something we've seen pretty often is companies, all sizes, are all struggling with very similar, similar problems in the data space specifically so it's not a big companies have it all figured out, small companies are behind trying to catch up, and small companies aren't necessarily super agile and aren't able to change at the drop of a hat. So it's a journey. It's a journey and it's understanding what your problems are with the data in the company and it's about figuring out what works best for your solution, or for your problems. And understanding how that impacts everyone in the business. So it's really a learning process to understand what's going- >> What are your friends who aren't in the tech business say to you? Hey, what's this data thing? How do you explain it? The fundamental shift, how do you explain it? What do you say to them? >> I'm more and more getting people that already have an idea of what this data thing is. Which five years ago was not the case. Five years ago, it was oh, what's data? Tell me more about that? Why do you need to know about what's in these databases? Now, they actually get why that's important. So it's becoming a concept that everyone understands. Now it's just a matter of moving its practice and how that actually works. >> Operationalizing it, all the things you're talking about. Guys, thanks so much for bringing the insights. We wrangled it here on the Cube. Live. Congratulations to Trifecta and Alation. Great startups, you guys are doing great. Good to see you guys successful again and rising tide floats all boats in this open source world we're living in and we're bringing you more coverage here at DataWowrks 2017, I'm John Furrier with Dave Vellante. Stay with us, more great content coming after this short break. (upbeat music)

>> from Boston, Massachusetts. It's the queue covering active eo 2019. Data driven you by activity. >> We're back with the Cuban active FiO Data driven day one day Volante with student a man you're watching The Cube. Steve Duplessis here is the, uh, let's see. Uh, I'm going to say benevolent. Dictator of Enterprise Strategy Group. Chief analyst, Founder Welcome. Welcome back to the Cube. >> Thanks. Nice friend. Nice to be here, you fellows, and we don't Great. Congratulations. Newly newly closed. That's awesome. I want Yeah, thank you very much. >> Great. Looking good. You're here for your honeymoon. >> He said this is it? After a few marriages. This is the honeymoon. >> Yeah. That's good to know that the honeymoon's not over. So let's talk data, Tio. It's happening. >> That is a terrible question, Dave. >> So yeah, Data. Okay, everybody talks. Data you here, bro. My data is the new oil. Fate is a competitive advantage. And >> you like that. >> You do like what Data's in oil. >> So it's funny because we're I think I'm way older than you. You look better. >> God, no. >> But if you go back in time as long as we were doing this, it's been kind of hilarious, really. In retrospect, when you watch way watch these massive industries get created like the AMC just created because all they were about building bigger buckets to put data, zeros and ones. But no context, completely useless, just big buckets. So we valued Wow, you built a big fast bucket. Then IBM and her tachy whoever was gonna leap frog your next built a faster, bigger bucket. And that was with the world considered valuable. And it's now fast forward to the modern day and oh, maybe with the thing that's really valuable with those zeros and he's in contact. Maybe it's not really the bucket. It's, uh so valuable anymore. So >> So, do you think the with the bucket builders still bucket builders air they actually becoming data Insite creators? Or is it just still build a better bucket? That's cheaper. Faster >> till it's a great question. I think >> that we're first of all, you You still have to have the buckets, right? It's a relative who's going to make a smarter bucket builder. I don't know. >> You need someplace to put it, so >> you're gonna have to put it some place and you're gonna have to deliver it in the good news, you know, storage and or infrastructural say is the most brilliant business ever. From a capacity demand perspective, no one ever needs less, right. You always need Mauritz justa matter what you're gonna do with it, how you're going to address that. So it's we've propagated for 50 years and infrastructure business that build a bigger, faster bucket. Build a bigger, faster processor, build a bigger, faster. And every time you you solve one of those particular problems as long as data doesn't abate and it never does, is only is there's more versus Les. It's just every time we fix one problem way, you stick your finger in the dike and another poll springs out. So right now we're at the we've got more processing capabilities that week, ever possible. Use not true, right? We'll figure out a way to use it so that the last five years of and for the >> next five years waiting talk about analytics, wouldn't talk about io ti. We didn't talk about any of those things that are all just precursors to folk crap. We could make a whole bunch more NATO and do stuff with >> so So computers. Kind of a similar dynamic. It's sort of sensational. But is the relatively crappy business compared to storage rights? Storage is 60% plus gross margin. Business servers. I don't know. You're lucky if you get in in a low twenty's. Um, why is that? >> Hello, Number one. It's essentially monogamous. So 20% is wonderful if your intel and you get it. All right. Well, it sells. Got great gross margins, right? Everybody else's does it. You go down the supply chain. That's where you're gonna add value. So that's difficult for anything. Hard to get gross margins out of like spending. She had a box. >> So, Steve Yes, she's now 20 years old. >> I know >> when I think back 20 years ago. You know, short. You know this capacity price per dollar price per gigabyte. You know, all that stuff has changed a lot. The other thing, You know, I think back 20 years talk about automation and intelligent infrastructure. We were using those terms back that sure, one of things that they did. That that's right. Well, that's what I wanted to ask you about is like, right back then when you talked about well, how intelligent wasn't what could it do? And automation was There was a lot of times, you know, I'm just building a little script. I'm doing something like that. At least you know, from what we see, it feels like, you know, today's automation and intelligence is light times away from what we were talking about. 20 years. Sure, and it's true. What do you see in that? Well, >> so remember where we came from When we were talking originally about automation and orchestration, we were talking about how to manage a box, how to expand a box, how to manage infrastructure. Now it's data operations. Right now it's that that's the whole point of activity. Right to be in with is all right, if you are good enough and smart enoughto have the data sort of everything. What kind of matters? There you've gotta have the data and what can you up? What can you automate an orchestra from a data out perspective? Not from a box, not from a Let's scale out or scale up or something like that again, that's just a bigger bucket. It's a better bucket, but to be able to actually take data and say, You know what? I don't even know necessarily what I'm going to want to use this for, but I know that I gotta have. It's gotta be You have to be able to go click, click, click and get it. If if and when I figure out who I want to find out how lowering the price of Sharman and Seattle at a Wal Mart is going to affect my revenue or my supply chain or whatever. >> So one of the things I've talked with you in the past about is the pace of change of the industry. And, you know, I've said, you know, we know things are changing rather fast, but the average company, how much were they? Actually are they good at adopting change? And you've called me on stupid enterprises slow getting any faster, you know? Are they Are they open to change? Mohr. You know, what do you see in 2019? Is is it any different than it was in, You know, two thousand nine? >> That's a great question. So thie answer is yes, they're getting better. We are finally getting better. Problem, though, is a CZ industry insider watcher or a Boyar is ur is you see it and know what should happen 10 years. It takes 10 years in general for the world to actually catch upto the stuff that we're talking about. So it's not really that helpful to the poor schlub that's running on operation that build sneakers in Kansas, right? That's not really that helpful that we're talking about. This is what you could be doing and should be doing. The pace of change is much faster now because and give the em where most of the credit. Because once that went into place, all of the sudden and that you gotta remember there, everyone thinks vm where was an instant home run? It was 10 years of the same cold sitting in the corner in a queue, a environment before. Finally, we ran out of room in the data center, and that's the only reason they were able to come out. But once it was there, and it enabled you to stop associating the physical to the to the logical once, we could just just dis aggregate that stuff that I think opened up a tidal wave of kind of what else can we do? And people have adopted now. Now it's pervasive. So VM where's everywhere? Now? We're moving in the next level of kind of woman. Why can't I just build a containerized app that I can execute anywhere? No matter of fact, I don't even want it in my data center on. No one has to know that necessarily. So as modernization exercises have started to take off, they just they pick up, they actually pick up steam. So what we know empirically is those that are are halfway down. Call it the transformation or the modernization curve are going three times faster than those just starting. And those guys are going three times faster than the ones that are sitting there in idle doing stuff. The same >> city with the inertia going on. What do you make of this Bubblicious Back up market. Let's talk about that a little bit. You got these big install bases? The veritas, Conmebol, Delhi emcee, IBM, Tivoli install base. Everybody wants a piece of that action. Well, I guess cohesive rubric also want a piece of each other. Sure, which is kind of, you know, they get that urinary Olympics going on. I'd like to say And then you got these guys, which is kind of, you know, playing. Uh, I said to Ashleigh kind of East Coast, West Coast, There's no no, it's not East Coast, West Coast, but there's definitely more conservativism on this side of the of the flyover states. What's your take on what's going on in the landscape right now? >> So back up is awesome from the again, still probably the single most consistently line item budget thing for five decades. It's a guaranteed money in and out, and by and large it still sucks. My general rule is still it's crazy that we haven't been able to solve that particular problem. But regardless, the reason that it's so important is, besides the obvious. Yeah, you need to protect stuff, case. Something goes away and something bad happened good. But really, it's That's the inn. Just point for everything you do, you create data today. I'm backing it up on our later so that backup becomes the injust engine and it also is kicking off point. So at tapioca it started as wow, this is a better backup, most trap for lack of a better term. But really what? It was is didn't matter what with was back up or something else. It's I need tohave the data in order to do other stuff with it, and back up is just a natural, easiest way to be able to do that. So I think what's finally happening is we're moving from Christophe Would would say it's really about intelligence intelligence more so than just capturing those bits and being able to assemble and put it back together. It's understanding the context of those bits so that I can say stew in test. Dev has a different use case than Dave in whatever analytics, etcetera, etcetera. But they both need a copy of the exact scene data, the exact same state at the exact same point in time, etcetera. So if lungs backup's going to be kind of a tip of the spear in terms of going from what I will say, production or live data to the first copy, there's almost always back up. It's gonna matter. >> Christoph, Christoph Bertrand want your analyst? And so we saw, uh, c'mon, Danni Allen put a slideshow $15,000,000,000 tam and back up being a big chunk of that, probably half of it um, how does that jibe with your gut feel in terms of the opportunity beyond backup Dev ops? You know, I don't know. Ransomware insights. So you think that's low? High? Makes sense. >> I think I could justify the number. And what history has taught me is that it's probably low because we we're only talking about a handful of use cases that we've all glommed onto. But there will be remembered, like 11 years ago, there was no iPhone. You know what? How bad that changed. Everything that we do over there. And when did you know at some point during that particular journey, the phone became Who gives a shit about the phone? Excuse. But it's a text machine and it's an instagram thing, and it's a video production facility and all these other things, and the phone's almost dead. I only use it when my mom calls me kind of thing. So, you know, really, it's difficult to imagine. I certainly don't have the mental capabilities to imagine what the next 10 things after Dev Ops and this that and the other. But it's still all predicated on the same you got Somebody's gonna have a copy of that data and you're gonna be able to access it. You've got to be able to put it where you need it for whatever the reason again, a disaster is an important thing to recover from. But so is being ableto farm That data for nuggets of gold. >> Well, I guess I asked the question because, you know, it's a logical question is, is the market big enough to support all these companies that are in, You know, that gardener thing that they do? And I hope so because we love competition. >> I think I >> can answer it >> this way. Everything. Even the oldest guard Veritas, for God's sakes, 1000 years old, t sm 1000 years old con vault code base, 1000 years old. You're all big companies, right? And they're not perishing anytime soon. And I don't run. Love the startup Love the active FiOS or the cohesive sees coming in. But what they're really trying to do is not, you know, they might have started, as in a common ground, backup is a common warzone, but because there's money there like this consistent money there go get. But they soon turn in Teo other value propositions. And that's not is true with the incumbent back up guys because of their own legacy, right? It's hard to turn 1,000,000 year 1,000,000 lines of code into something. It wasn't designed, innit? >> Yeah, and it's not trivial to disrupt that base. But I guess if you get, you know, raising I don't know how much the industry is raised, but it's well over $1,000,000,000 now. I mean, activity has raised 200,000,000 and that's like chump change. Compared to some of the other races that you've seen. Cody City was to 60 and their last rubric was even, you know, crazy, crazy, even >> count the private money that beam God is that, you know, that was half 1,000,000,000 >> right? Well, that's a That's an off camera discussion. All right, we gotta go. So, Steve, thanks so much for for coming. Thank you. Great to >> have you. All right. All right, everybody. We'll be back with our next guest. You wanted the Cube from active field data driven from Boston, right on the harbor. Right back

(upbeat techno music) >> Live, from Las Vegas, it's theCUBE covering VMworld 2018, brought to you by VMware and it's ecosystem partners. >> Okay, welcome back everyone, we're here live in Las Vegas for VMworld 2018 coverage. It's the final analysis, the final interview of three days, 94 interviews, two CUBE sets, amazing production, our ninth year covering VMworld. We've seen the evolution, we've seen the trials and tribulations of VMware and it's ecosystem and as it moves into the modern era, the dynamics are changing. We heard quotes like, "From playing tennis "to playing soccer," it's a lot of complicated things, the cloud certainly a big part of it. I'm John Furrier your host, Stu Miniman couldn't be here for the wrap, he had an appointment. I'm here with Dave Vallente and Jim Kobielus who's with Wikibon and SiliconANGLE and theCUBE team. >> Guys, great job, I want to say thanks to you guys and thanks to the crew on both sets. Amazing production, we're just going to have some fun here. We've analyzed this event, ten different ways from Sunday. >> So many people working so hard for such a steady clip as we have here the last three days, amazing. >> Just to give some perspective, I want to get, just lay out kind of what's going on with theCUBE. I've get a lot of people come up and ask me hey what's going on, you guys are amazing. It's gotten so much bigger, there's two sets. But every year, Dave, we always try to at VMworld, make VMworld our show to up our value. We always love to innovate, but we got a business to run. We have no outside finance, we have a great set of partners. I'm proud of the team, what Jeff Frick did and the team has done amazing work. Sonia's here's, the whole analyst team's here, our whole team's here. But we have an orchestrated system now, we have the blogging at SilconANGLE.com and Rob Hof leading the editorial. Working on a content immersion program. Jim you were involved in with Rob and Peter in the team, bringing content on the written word side, as fast as possible, the best quality, fast as possible, the analysts getting the pre-briefing and the NDAs, theCUBE team setting it up. Pretty unique formula at full stride right now, only going to get better. New photography, better pictures, better video, better guests, more content. Now with the video clipper tool and our video cloud service and we did a tech preview of our block chain, token economics, a lot of the insiders of VMworld, the senior executives and the community, all with great results, they all loved it, they want to do more. Opening up our platform, opening up the content's been a big success, I want to thank you guys for that. >> And I agree, I should point out that one of the things we have that say an agency doesn't offer, I used to be with a large multi national solutions provider doing kind of similar work but in a thought leadership market kind of, let me just state something here, what we've got is unique because we have analysts, market researchers, who know this stuff at the core of our business model, including, especially the content immersion program. Peter Boroughs did a bit, I did a fair amount on this one. You need subject matter experts to curate and really define the themes that the entire editorial team, and I'm including theCUBE people on the editorial team, are basically, so we're all aligned around we know what the industry is all about, the context, the vendor, and somebody's just curating making sure that the subject matter is on target was what the community wants to see. >> So I got to day, first of all, VMware set us up with two stages here, two sets, amazing. They've been unbelievable partners. They really put their money with their mouth is. They allow us to bring in the ecosystem, do our own thing, so that's phenomenal and our goal is to give back to the community. We had two sets, 94 guests this week, 70 interview segments, hundreds and hundreds of assets coming out, all free. >> It was amazing. >> SiliconANGLE.com, Wikibon.com, theCUBE.net, all free content was really incredible. >> It's good free content. >> It's great free content. >> We dropped a true private cloud report with market shares, that's all open and free. Floyer did a piece on VMware's hybrid cloud strategy, near to momentum, ice bergs ahead. Jim Kobelius, first of all, every day here you laid out here's what happened today with your analysis plus you had previews plus you have a trip report coming. >> Plus I had a Wikibon research note that had been in the pipeline for about a month and I held off on publishing until Monday at the show, the AI ready IT infrastructure because it's so aligned with what's going on. >> And then Paul Gillan and Rob Hof did a series in their team on the future of the data center. Paul Gillan, the walls are tumbling down, I mean that thing got amazing play, check that out. It's just a lot of detail in there. >> And more importantly, that's our content. We're linking, we're open, we're linking to other people's content, from Tech Field Day what Foskett's doing to vBrownBag to linking to stories, sharing, quoting other analysts, Patrick Moorehead for more insights. Anyone who has content that we can get it in fast, in real time, out to the marketplace, is our mission and we love doing it so I think the formula of open is working. >> Yeah Charles King, this morning I saw Charles, I thanked him for, he had great quotes. >> Yeah, great guy. >> He's like, "I love with Paul Gillan calls me." John, talk about the tech preview because the tech preview was an open community project that's all about bringing the community together, helping them and helping get content out into the marketplace. >> Well our goal for this event was to use the VMworld to preview some of our innovations and you're going to start to hear more from the siliconANGLE media, CUBE and siliconANGLE team around concepts like the CUBE cloud. We have technology we're going to start to surface and bring out to the marketplace and we want to make it free and open and allow people to use and share in what we do and make theCUBE a community brand and a community concept and continue this mission and treat theCUBE like an upstream project. Let's all co-create together because the downstream benefits in communities are significantly better when there's co-creation and self governance. Highest quality content, from highly reputable people, whether it's news, analysis, opinion, commentary, pontification, we love it all, let the content stand on it's own and let's the benefits come down so if you're a sponsor, if you're a thought leader, you're a news maker, you're an analyst, we love to do that and we love talking with the executives so that's great. The tech preview is about showcasing how we want to create a new network. As communities are growing and changing, VMware's community is robust, Dave, it's it's own subnet, but as the world grows in those multiple clouds, Azure has a community, Google has a community, and people have been trained to sit in these silos, okay? >> Mm-hmm. >> We go to so many events and we engage with so many communities, we want to connect them all through the CUBE coin concept of block chain where if someone's in a community, they can download the wallet and join theCUBE network. Today there's no mechanism to join theCUBE network. You can go to theCUBE.net and subscribe, you can go to YouTube and subscribe, you can get e-mail marketing but that's not acceptable to us we want a subscribe button that's going to add value to people who contribute value, they can capture it. That was the tech preview, it's a block chain based community. We're calling it the Open Community Project. >> Wow. >> Open Community Project is the first upstream content software model that's free to use, where if the community uses it, they can capture value that they create. It's a new concept and it's radical and revolutionary. >> In some ways were analogous to what VMware has evolved into where they bridge clouds and they say that, "We bridge clouds." We bridge communities all around thought leadership and to provide a forum for conversations that bridge the various siloed communities. >> Well Jim you and I talked about this, we've seen the movie and media. In the old school media days and search engine marketing and e-mail marketing and starting a blog, which we were part of, the blogging was the first generation of sharing economy where you linked to other bloggers and shared your traffic, because you were working together against the mainstream media. >> It's my major keyboard, by the way, I love blogs. >> And if you were funded you had to build an audience. Audience development, audience development. Not anymore, the audience is already there. They are now in networks so the new ethos, like blogging, is joining networks and not making it an ownership, lock in walled garden. So the new ethos is not link sharing, community sharing, co-creation and merging networks. This is something that we're seeing across all event communities and content is the nutrients and the glue for those communities. >> You got multi cloud, you got multi content networks. Making it together, it's exciting. I mean there were some people that I saw this week, I mean Alan Cohen as a guest host, amazingly articulate, super smart guy, plugged in to Silicon Valley. Christophe Bertrand, analyst at ESG, a great analysis today on theCUBE, bringing those guys, nominate them into the community for the Open Community Project. >> You know what I like, Dave, was also Jeff Frick, Sonia and Gabe were all at the front there, greeting the guests. We had great speakers, it all worked. The stages worked but it's for the community, by the community, this is the model, right? This is what we want to do and it was a lot of fun, I had a lot of great interviews from Andy Bechtolsheim, Michael Dell, Pat Gellsinger to practitioners and to the vendors and suppliers all co-creating here in real time, it was really a lot of fun. >> Oh yes, amen. >> Well Dave, thanks for everything. Thanks for the crew, great job everybody. >> Awesome. >> Jim, well done. >> Thanks to Stu Miniman, Peter Burris and all the guests, Justin Warren, John Troyer, guest host Alan Cohen, great community participation. This is theCUBE signing off from Las Vegas, this is VMworld 2018 final analysis, thanks for watching. (upbeat techno music)