 at Big Data SV 2014 is brought to you by headline sponsors, WAN Disco. We make Hadoop invincible and Actian, accelerating Big Data 2.0. Okay, welcome back everyone to Big Data Silicon Valley. I'm John Furrier, the founder of Silicon Angle. I'm joined by co-host Dave Vellante, co-founder of Wikibon.org. This is theCUBE, our flagship program. We go out to the events, extract the signal from the noise. We're excited to continue the Big Data tradition from Big Data NYC to Big Data SV. Hashtag Big Data SV. Go to crowdchat.net slash Big Data SV. Be part of the conversation with our new preview of our crowd chat application. And we have a full on the record transcript there for any kind of questions or commentary with posting videos there. We'll open that up to everyone. My next guest is Alan Salisday, who's a VP of marketing at Cloudera. Welcome back to theCUBE. And thanks for coming on, really appreciate it. Thank you. Thank you for having us. Cloudera, the leader in the space. You guys mean the history for us with theCUBE. Started at Cloudera. So we're proud to always have you guys on. But what a difference the market is now. It's maturing significantly. What's the latest messaging? What's the latest Cloudera focus? Share with the folks the update on Cloudera, the positioning. You guys have the enterprise hub, which was announced in Paula, set the standard for SQL over Hadoop. You're filling in the platform, the market's growing. We're hearing budgets. Budgets are out there now here at the show, being talked about. What's the latest? What's the positioning at Cloudera? Yeah, so we just launched last week, officially the enterprise data hub, which is the way we're describing our solution now. I think we've spent, I've been at Cloudera two years, and you're right, it's dramatically different. Two years ago and even one year ago, most of the talk was about the Hadoop distribution and what was in your distribution and what was out of it. Who's more open source, all those kinds of issues and frankly, I think we just concluded most customers who actually wanna solve business problems don't care about that stuff. And they found the complexity of Hadoop pretty overwhelming. So, at the same time, we've invested a tremendous amount of money and time and engineering in a lot of proprietary software around the open source core to make this thing that people want more deployable and more secure and more governable. And at the end of the day, we decided we need to simplify our own product packaging and simplify the positioning. And so we settled on describing the enterprise data hub not as a Cloudera thing, but really as the thing that all of us, I think all of the vendors are really trying to get to, which is a new way to store, process and analyze unlimited amounts of data in new and novel ways. So that's really what we're talking about. I always said when we started all this BS around, oh, this, cause you guys were the only ones, Cloudera was the only one in the market, then Hortons came to Avogado and MapR came up with their approach. I always said from day one, there's plenty of beachhead for everybody and that the rising tide floats all boats. The market growth right now is so massive, you're seeing great valuations in the market on the private side, you're seeing companies go public, certainly we're in a growth market. Talk about that positioning now as the market matures, when you talk to customers, I don't see them having the same conversations. I do agree with you, but when you go in and say, this is the new Cloudera, it's not a change for Cloudera. You're just simplifying the messaging. Yeah, and the pricing and positioning of our solution. So there's different segments of customers. I don't think anyone would argue too much about it. There's the customers who are completely self-supporting, largely here in the Valley, who they're helping to develop Hadoop, they don't really need. Drop it off, I'll take care of the rest. And they will probably exist forever, the Facebooks of the world and whatever. Then there's a bunch of customers who want support, but they don't yet either because they're not mature enough in their implementation or the problem they're trying to solve doesn't require it yet, but they don't care about things like SQL and Hadoop or they don't care about using search or they just want basically a very inexpensive place to store lots of data, but they want some support. So that's kind of one group. Then the next group we feel like is those who want to build a cluster to solve one specific problem, maybe like a no SQL kind of implementation. And then the last group are the, maybe larger companies who really get the idea, the power of Hadoop and the concepts like bring your workloads to the data, multi-structured data, and they want to build what we are now calling an enterprise data hub. So we've really set our product offering up in those three things and we've renamed it so we have now have Cloudera Enterprise remains the same name, but then we have three editions, the basic edition, which is really, you could think of it as almost like a supportive Hadoop cluster with no bells and whistles. And you know, there are other vendors who provide obviously Hadoop distributions and we will compete aggressively with them for that segment. Then there's the special purpose cluster, which we're calling Cloudera Enterprise Flex Edition and you get to pick one of several kind of special pieces of the framework whether it's Impala or HBase or Search or Navigator, but only one per cluster and that's kind of the middle offering and then the flagship offering is Cloudera Enterprise Data Hub Edition where for one price you get all the software that Cloudera provides and that's really what we, it's got tremendous traction. We really just began talking about it informally last quarter, kind of the end of last quarter and it's been incredibly popular not only financially but people get it. You have a very different conversation. You really don't get into the details of Hadoop frankly. You have a completely different conversation with a different type of person and they're trying to solve business problems and that's really what we're doing. So if I could just follow up on the packaging. So the components, so you got the distro which I think you call Cloudera Express now. The distro by itself, we still call CDH. That's just naked. You can still download that for free and people do it. And then you got a management console and then you got other components in there. You mentioned Spark, you mentioned Search. I presume HBasis is part of that. Yeah, it is still somewhat, so all of the software is included in the distribution. So if you don't care about support, you can still go download CDH and get all the software. Now, if you want support. So that's, now you're to Flex. Basic, Flex and data-holding. So basic, you get support for basic. Basic, you get support for the core Hadoop framework but not for Spark. None of the components that Enterprise puts. None of the kind of special components, HBasis. I can pick one component. For Flex. And Enterprise. Data Hub, I get support for all. Yeah, that's right. Okay, and then the pricing goes up is obviously, I guess. Yeah, but it's, you know, we've kind of set the pricing so that it's a lot cheaper compared to the old model where you really had to, it was really Alucard and you really had to kind of pick, okay, I want to add Search, okay, now I want to add Impala, now I want to add HBasis, now I want to add this. And each time you had to pay more and we just found A, it was confusing for our customers and frankly. Transaction must have been complicated, right? And you know, the real strength of Cladera is we do have all of these things available and we think the customers benefit by using more of them together. The power of Hadoop isn't just storing a bunch of data, it's doing SQL on Hadoop, search on the same data, SQL on some of it, search on some of it, combining those in novel ways, introducing Spark now. So if you're having to make a financial decision about whether it's worth it or not to try to use Impala, for example, you're, it's an unnecessary obstacle. And we just want people to use these frameworks together on the same data and get in the habit of bringing workloads to the data not moving their data around. So Enterprise Data Hub is less expensive than if I were to buy all the piece parts. Yes, exactly. But what you're saying is not everybody would necessarily buy all the piece parts but you're gonna drive usage up. It's like the Lexus, when the Lexus came out, those were old enough to remember that. You know, one of the big things they came up was, look, there's no options, you get everything. You just, you know, sunroof, FM radio, heated seats, whatever, you know, that's my simple analogy. So the segmentation, it's a segmentation product map, flagship is Enterprise Hub, and those are real. If you're not ready for that. And some people are, and they just, they don't want to get in the nuances of what did I buy, what support it's all in. But now the conversation will switch to helping people actually exploit what's there that they may or may not be using. Yeah, and that's the power, right? I mean, once you're building an Enterprise Data Hub, then you can do the things that are really the exciting part, which is, wow, can I offload workloads and data out of my existing infrastructure? You know, whether it's a data warehouse, or a mainframe, or any number of other things into this Enterprise Data Hub. And because I have a license now to use all these different workloads and different frameworks, I don't have to make any. Yeah, I mean Dave, we were talking about yesterday, it makes the conversation shift to, you know, pricing, tactical pricing, product decisions, positioning usage to outcomes, right? So you have literally a conversation, okay, you fit into this bucket, you're an Enterprise Hub customer, or hey, you're doing a POC or whatever your unique environment is, you can pick flex, or if you want to just do some ingest on HBase and use some basic stuff, you go with the basic, right? And then you can move your efforts on those kinds of conversations. Yeah, yeah, it just helps us have a clearer conversation and, you know, there are just customers who aren't there yet. You know, as we all know, this is still early market, there's still a lot of people learning about Hadoop and what is possible and how to integrate it. And, you know, some of them want to get started, they want support, but they're just not there yet. They're not, you know, they're not mature enough, but they will, it's changing very much. We heard from Hortonworks yesterday with Microsoft on them. We were seeing the SQL HG insights, they were pitching that and talking about that. And we just had another startup on InfinityDB and some other ones. The SQL market just seems ready to explode. Obviously Impala was there first, you had kind of this idea, you got search, all these multi-functions built in, now you kind of extract away that complexity and call enterprise up. But the SQL movement is happening, right? And some pretenders that are dropping out of the race, you've seen some startups that kind of aren't making it and the winners are emerging. So you guys are one of them. Talk about how you guys are looking at that market. Is this, because education's involved, you have a pre-existing massive market that wants, hey, I got old stuff, I got to get it into the new hub. How do you talk to those folks? What are some of the trends? Do you agree it's about the breakout? Do you feel it? Yeah, oh yeah. So Impala is the open source project that we developed. And it is, I think, A, you have to start distinguishing between SQL and Hadoop technology that's actually available and generally available and deployable versus SQL and Hadoop, that is PowerPoint slide or maybe- Vaporware. Vaporware. This is the tech industry, after all. Marketecher. Right. Another word. That, you know, one big distinction right off the bat is Impala has been GA for quite a while. It's widely deployed and heavily used and it's integrated with some of our key partners like SAS. And you can actually do it. So that's probably the biggest differentiator. But I think the important thing that it did was it opened people's eyes to, wow, this Hadoop thing isn't just a storage and map reduce, you know, massive data processing thing. It is a potential, you know, disruptor of, you know, the data warehouse, for example, enterprise data warehouse because it's, you know, an order of magnitude or two less expensive. It often can outperform depending on the dependent demo workload. It's more flexible because you can combine structured and unstructured data in ways that you just can't do in enterprise data warehouse. Now, you know, we, all of our customers who are using an enterprise data hub as a way to offload an EDW are not getting rid of their EDW. So that's one thing we really wanna make clear. We are not, as it's sometimes portrayed, saying to our customers, hey, throw that thing away, put this thing in. That's not it at all. The point is, you have, you know, if you're a large bank or a large credit card company or a large, whoever, any large company has one or many enterprise data warehouses which cost a lot of money. They're under continual pressure to expand and have multi-million dollar expansions. And often you can say, instead of taking $10 million or 20 million or 100 million and increasing the size of your existing EDW, you can look at that objectively and say, well, there's a lot of data and workloads in this EDW that we could move very effectively into an enterprise data hub. And that will not only save us a ton of money, it will free up our EDW to do what it's best at. You know, run our core critical, mission critical, you know, financial analysis or whatever. And we can grow the massive amount of the big data in this enterprise data hub at a fraction of the cost and do all the flexible analysis. So you're still gonna have a big EDW. Our largest customers have massive enterprise data warehouse implementations that are not going anywhere. But they're building this EDH next to it and it's growing the amount of data and it's growing much faster. But I mean, I hear what you're saying, I agree with what you're saying. But the reality is the same thing with mainframes and people, you know, when we saw that big movement didn't throw them out, you know? They're still there by the way. They're still there and there's good business for IBM. At the same time, you know, which business would you rather be in? So when Mike was up on stage last year at this event at Strada and you guys announced enterprise data hub, he said that Hadoop is moving from the periphery to the center of the data center's architecture and that's happening. And so you just pointed out, Alan, is that essentially you can cut your cost quite dramatically. I mean, you know. Well, it's at least one if not two orders of magnitude. I mean, it's a 10th, the 20th, the 30th, the 50th. 10x plus better price performance. And so if you're a CIO, where are you gonna put your investment in your portfolio? You're gonna put it into this new world. So while I agree with you that enterprise data warehouse not gonna go away, it's gonna be selective about what you put in. You mean much more selective, right? And the other thing I would point out, like your comment on this, what you guys are promising and maybe even delivering, I think are delivering, you guys being the Hadoop community, you're delivering on the promises that the EDW guys never delivered on. That's right. And that is I think very powerful and is what is bringing a lot of momentum to the business. Yeah. And I think people are getting, yeah, that's exactly right. In fact, we tell customers that, you know, for customers who are old enough, like I am, you can, it's a very similar story. Take all your data from these different sources, put it in one place, mix it up, do the reporting. And that's true. Enterprise data warehouses did that to a degree, but only for certain types of data and only with a lot of money and very careful planning and schema design and all that stuff, which Hadoop frees you from a lot of that. But once you do that schema design, you're locked in. Yeah. And then there's the hard to be agile. Yeah. It's very hard to be agile, a new field or a new column or whatever. You know, and Hadoop today is radically different than it was two years ago. So two years ago, there's a lot of skepticism, even in 2013, there's still a lot of skepticism from enterprise data warehouse buyers and mainframe buyers. You know, well, can you really do this? And you don't have all the features and you don't have all those in that. And, you know, speaking for Cloudera, we have added a ton of features that now bring it up to the point where, you know, we use the smartphone as a metaphor. A lot. I don't know if we've talked to you about that, but basically- Amar was on New York. Yeah, Amar talks about this a lot. But, you know, everyone, including me, still has a DSLR camera. I have it in my closet at home. We probably use that thing now two or three times a year. You're going to a soccer tournament. My wife will bring it. You're gonna bring it. But day in, day out, you take most of your photos, I'm guessing, with your smartphone. Now, if you compare the smartphone to your DSLR as a camera, the DSLR is a way better camera, right? In every dimension, pretty much. However, you still use the smartphone most of the time because it's convenient. You have it with you. You can- It's integrated with all the other apps on your phone, you know, Facebook and Twitter and whatever, in a way that a DSLR camera is not. And that's a very similar story to Enterprise Data Hub as compared to an EDW. If you just compare them in EDH and EDW, you know, side by side, you might conclude, and you probably would, that EDW has a richer set of features. It's more robust, it's been around a long time. It's a better data warehouse in many ways. However, if you think of what an EDH could also do, that EDW can't do, right? It's an active archive. It gives you self-service BI. It's much more flexible, right? It can store anything. You keep it forever. It's a lot cheaper. You know, a lot of companies figure, they try thinking more carefully, like you said, they're more selective, like, okay, wait a minute. I'm gonna use my data warehouse for this stuff. But, you know, there's a lot of stuff I could do, maybe not quite as snazily, but a hell of a lot cheaper and more flexibly. So that's, we see that having a whole lot of stuff. And what else can I do with that new stuff? And this did lead to an interesting discussion with Armour, we were at splunks.com, and I was using the Oracle example. I know Oracle's a big partner, you guys, and I was very careful about, you know, how you position it. But we heard Larry Ellison, John, last year at Oracle Open World talk about it, oh, Hadoop, it's a filtering system. It's batched. What you want to do is do all your filtering, and then bring it into Exadata. You know, that's tongue-in-cheek. We look at that and we talk to CIOs and say, okay, there are use cases for that, but there's many more opportunities, as we're just describing, for this new wave. And we see where all the growth is. Yeah, yeah. Yeah, so Oracle's a great partner. I think they have the most mature view of going to market with Hadoop. So as you know, the big data appliance is Clutter, a software inside of Oracle hardware. And they sell it right alongside Exadata and all of their other database products. And they view it as very complementary. And they're basically telling a very similar story to us. And they have such a diverse product line that it fits well into their sales motion and their marketing. And they're doing a great job of it. And are, you know, a very, very good partner of ours. You know, if there's a company that is, you know, only has an enterprise data warehouse, then it's a tougher thing. Because obviously, there is this overlap. I think everyone acknowledges there's an overlap. You can debate about how wide the gray area is and where the edges are. But that's where it gets a little more sensitive. Alan, talk about, you know, obviously, I mean, I can see where you're coming from saying, oh, we don't want to rip and replace. I mean, it's a nice way to align with the current environment. The reality I agree with Dave is that, and what you're saying is that it'll shift. So that's going to happen. We'd like that trend. I think that's pretty well documented. As Cloudera comes in this early market, you guys have a good lead, great positioning, nice clean pricing and product positioning. When you go in with your professional services, which you've been doing for quite some time with a lot of different accounts, some you can't name because of the confidentiality, large environments, you're moving into now the mainstream where the deployments are getting bigger and bigger. What do you go when you go into the enterprise guys? Like, that's a mid-range enterprise. Not the high-end hyper scale, but like mid-range. What do you talk to the CIOs about? And how do you talk about, hey, we're not just a little startup anymore. You know, we're having big sales organizations. You have professional services. How do you earn that trust and what's the messaging for you guys? Because they're looking at you going, hmm, we want this. We want this new direction and we want a reliable partner. Yeah, yeah. Well, we really, as of the end of last quarter, we really start with the enterprise data. That really literally now is where we start. We don't start with Hadoop and all that stuff. And we really talk about trying to help them solve their business problems. So, you know, step one, in my opinion, is listen to the customer. You know, what are you trying to do? What's your, you know, there's a many, many use cases, right? They're all over the map. I'd say a very common path is starting, a lot of companies start with an IT problem. You know, even though in the long run, the IT problem is not really the power that's possible to leverage with Hadoop, but it's often the place where you start. It sometimes is just, I just want a cheaper, more scalable place to store my data. I don't want to keep buying storage from Pick Your Favorite, San or NAS, vendor, container. That's how Hammett Barker calls it. That's right. I don't want to pay millions of dollars for the container, exactly. I want a cheaper place because I don't know, I want to keep all this data, but I'm not totally sure why yet. I just want to keep it because I want to explore it. I want to analyze it, but I don't really, I can't really quantify yet why. It's an option, kind of pricing. Yeah, exactly. I want to have, preserve the option for some insight later. So that's very common. Start with that, and that might be a storage displacement. It might just be an incremental bunch of data you never kept before, but now you want to keep. And then I'd say the next step is offloading some existing infrastructure. We have a great partnership with SyncSort, for example, and they're all about helping their customers and our joint customers offload mainframes. And there's just a direct ROI savings there. Like, figure out what's in your mainframe. It's been in there for decades, data, tables, transformations, and guess what, you could do all that stuff, not all of it, but a bunch of it, in Hadoop, just as easily, and immediately pay your mainframe vendor less money every month, every quarter. All right, so that's an immediate ROI. And then after that kind of offload angle, then the next thing they usually get to is the more advanced analytics stuff, the 360 customer view, looking across their business lines, customers who buy things from different subsidiaries or over a long period of time, or how can they market better, how can they serve the right ad up, all those kinds of things. But it's often a progression that starts with a simple, discrete IT problem. That's very common. So let's want to take your mainframe example and talk about that, because there's gold in them in our mainframes. It's been sitting there for a long time. Surprising how many of them there are. For decades, and there are a lot of them. And in fact, in certain countries and regions of the world, it's actually growing. I mean, IBM has actually good mainframe business in China and Africa. But so, and we do a number of events at IBM events and their messaging is really good. It is, it's great. It's smart to plan it. It's smart to plan it. They've got big services and we can get that data out. So it's one specific question to use. How do you compete with that large whale, that IBM messaging, the huge services capabilities? They've been around for a while too. Been around for a long time. They know what they're doing. They've sold their server division. And they've got gear and all the services. So how does Cloud Air compete? Where do you win? Where do you struggle? Yeah, so, I mean, obviously, we're not going to compete with the IBM brand anytime soon. We're trying to do our best. Eat some breakfast first before you eat lunch right now. No, but seriously, I think IBM tells a very good story. And they have a product in every category, in BI and analytics and data movement and integration and storage, obviously. And I think the story we really tell is, look, despite the marketing veneer and the great story they tell about the smarter planet and big insights and all of their products, the fact is when you really want to deploy and solve the soup to nuts problem, you're really buying a series of discrete products. It'll be at all from IBM maybe. That's what they'd like you to do. But you still have the problem of data being stored and processed in different systems. And so the story we're telling is that's really not the right approach for the modern enterprise. What you want to do is build an enterprise data hub where you put all of your data in one system and then you bring workloads to that system as needed. So if you have a bunch of data, 500 terabytes or petabyte of data, and you want to do some SQL-like queries on that data, or I mean, SQL queries, then use Impala. If you want to do some exploratory searching, just let's say you got millions of patent filings in the data hub, well, lots of attorneys really don't know SQL, they might want to just Google it and use Clutter Research. If you need to do stream processing, bring Spark to bear. So that's the thing that you can't do, that even IBM can't do. They don't have an integrated data hub that's all one system. It's actually a series of systems. So that message resonates with the CTO who sort of sees that as the vision. Yeah, we have to overcome. And it doesn't when IBM and Rungin' the board. Well, yeah, I mean, we have to overcome all of the inertia, they have a very strong brand, they have decades of relationships. You guys are picking your shots, you guys are picking your market. Yeah, we're not, I don't think we're unrealistic, but that's the story that we're telling. But you're not shotgunning it, trying to just throw it against the wall. You're pretty targeted in your position. And not everyone's gonna go for it, but there's a surprising appetite for, there's a lot of excitement about, when you're in a tech space like this that's being disrupted right now and there's a real sea change, people get very excited once they get it. Once they understand like, oh, okay. It takes them a while usually, but once they get the idea that wow, so you're saying I can put any data in here, pictures, relational data, tables, stream, click streams, logs. I can put all that stuff in here. And then I can analyze it with different tools without having to move it anywhere. Once that light bulb goes off, then there are very receptive. That don't have to move it pieces. They're not moving it, it's critical. And it takes them a while to really see that. And you can see it in their eyes all of a sudden. And then they get very interested in despite the fact we're 520 people or so. So we think that's a lot, but I know compared to IBM's, however many 100,000 people they have, it's not a lot. It's not bigger than when you started. We've been drinking the Kool-Aid from the beginning, as you know, and we agree with you. Once people taste it and they see it, it's pretty obvious everything else is just a distraction. So I want to, you mentioned something on the opening, we talked about the old Hadoop conversations, talking about the new positioning about the enterprise hub. I got to talk about the Cloudera evolution, the story, because you have to tell the narrative of Cloudera. He had Michael Olson stepped down as CEO, he's now chairman of the board and chief strategy officer, co-founder of Amarawa Dallas CTO. The Cloudera magic from the early days, and it's no longer about Hadoop, now it's a bigger picture, is growing up. And so what is the new magic? Because Cloudera had the magic early days about that unique, it's a startup, the first mover, great people, great team. And as you guys continue to evolve, you have a new CEO, talk about the new magic. What do you guys, how do you talk about the new company? Because you're growing up, you're having growth, massive growth opportunity, great traction. What's the next chapter look like? How do you tell that story about Cloudera? Well, I think we are very focused. Tom Riley is our CEO. He joined us last summer, and I think he's been on board about eight months. And Mike is still extremely actively involved as our chief strategy officer. I think it's freed him up to do what he does best, which is work on the technology, the technical direction of the company with Amar. And Tom has really helped the company focus. Still, Hadoop is obviously central to our existence. So we still have massive investment in the Hadoop open source community. I don't want to imply that we're leaving that behind at all. It's just that in our marketing and positioning and selling to business buyers. It's under the hood. Yeah, they're trying to solve a problem, a business problem. We're really committed to making them successful. So I'd say that is really the focus. We are, of course, committed to building great software and ensuring that it's governed and secure and managed and open and all of those things. But at the end of the day, a customer who's trying to figure out how their merchant system got hacked and they lost control of tens of millions of credit card numbers, doesn't really care which version of Flume we're using. Maybe they got a multi-million, maybe multi-billion dollar problem. That's the problem. So I think that's what we're really focused on is helping our customers solve business problems, using data and... Share with the folks the culture of Cloudera. I mean, I don't want to speak for you because I was there early on, sitting in the office with the early guys. But you've grown. A lot of things change when you grow, but culture doesn't change. Talk about the current culture. What is the culture now at Cloudera? Is it more the same? Is it extending? Is it growing? Is it new leadership? Obviously the founders are still around, which is always a good sign, in my opinion. Cloudera has an extremely strong technical foundation. So I think, number one, the engineers that we have I think are, we would argue unparalleled in the world of Hadoop. We still invest about half our engineering effort in the open source part of our business and half in the proprietary, rough numbers. And so I'd say technology and making sure that we stay ahead on the technical front is probably paramount. I think what we've added in the last year, really, is we've really beefed up our professional services, our technical support, and our focus on making sure that customers are happy. It's not enough as Silicon Valley is littered with tens of thousands of startups that had great technology that failed. We all know having great technology is maybe necessary but not sufficient. Guess what? You have to be nice to customers. You have to solve their problems. You have to answer the phone when they call. You have to fly out to wherever and fix issues when something goes wrong. You have to maintain the relationship. So all of those things, and we've massively increased our sales force. So our field of sales force has grown dramatically in the last 12 months. So all of those, I'd say we're really building the business culture on top of the extremely strong technical foundation. So I'd say that's kind of where we're at. Well, we're really pleased to see the success. We see, for everybody in this space, there's great valuation on everyone's companies, great growth opportunities, and obviously it wasn't for Amr and Mike and the team at Cloudera. The Cube wouldn't have existed. We started in the Cloudera office next to Fry's back on the glory days. So props to Cloudera. Great to see you success. Thanks for coming on the Cube. Really appreciate it and sharing the Cloudera mission, the new positioning, the Enterprise Hub. Great positioning, great stuff. Thank you very much. Thank you for having us. Appreciate it. Okay, we're here at the Cube. We write back live from Silicon Valley. Big day to SV, covering all the action and big day to all the innovation in Silicon Valley with Cloudera here inside the Cube. Stratoconference going on right behind us. We write back with our news break right after this short break.