 from San Jose in the heart of Silicon Valley. It's theCUBE covering Big Data SV 2016. Okay, welcome back everyone. We are here at the final wrap up of day three of wall-to-wall coverage of Big Data Week. Big Data Week is an event that happens in Silicon Valley and in San Jose every year and we are here in Big Data Week comprises of two big events, Big Data SV for Big Data Silicon Valley, which is our event with theCUBE and of course Strata had duped the Big Tent event inside the venue, inside the walls of the San Jose Convention Center. We take it outside the walls of the Convention Center. We go outside of their event, go all through Silicon Valley and we get the signal from the noise. I'm John Furrier, proud to be here. Every year I've had duped world, now it's called Strata duped. Now it's Big Data Week, including Big Data SV and of course this happens in New York City as well and soon to be Big Data London or Europe. I'm here at my co-host Peter Burris, head of research at Silicon Angle Media and general manager of Wikibon.com, our research group. And of course, Jeff Frick, general manager of theCUBE. Guys, great event and I just wanna say, super exciting this week, mainly because Peter, your first time with theCUBE just joined us, storied career in research recently with Forrester, going back to the Meta Group days, really pioneered a lot of research. It certainly, we're looking forward to doing more here but the presentation that we had was fantastic last night. We had our normal party but we had your presentation and then two panels and it really kind of flexes the muscle of the community and being the steward, it was really proud to see you up there, congratulations. Well, thanks very much, John and all we were trying to say was, this is a great event, there's a lot happening but we now have to start elevating the conversation to talk about how all this turns into business and we talked about digital business but the real emphasis is how are we going to create the digital capital that reliably and routinely gets translated into the new sources of value for customers, for owners, for employees and big data plays an absolutely essential role of that and we can see that because of the significant investment we released our first or second, actually our fourth big forecast on the evolution of the big data marketplace. So very well received, I got a lot of great feedback. And of course Wikibon was the first, actually have a big data forecast when we first published it out many, many years ago and continue the momentum. Jeff, I want to get your take because obviously theCUBE kind of goes to the next level. You can kind of see the community of theCUBE. Now we have over 8,000 videos, we've interviewed live on theCUBE in our seven season thousands, over 4,000 interviews live on theCUBE and theCUBE becomes a place where, I feel so much smarter because right here we're sitting right up on the front lines but last night you saw the community, you see the videos, people are jazzed, what's your thoughts? You know, I really enjoy this event because it's one of the two events a year that we have our own party and really invite our community to come and we're in Silicon Valley, a lot of people are local so they don't necessarily have to be like in Manhattan for that show to come and visit and it's just, you know, people change careers, people change jobs, people change companies but the people remain the same, the innovators stay the same, the tech athletes stay the same, they just sometimes change out their business cards if they even have business cards anymore. They're LinkedIn profile I guess, more appropriately but so it's always great to see them and the other thing is sitting whether here on the set or when we're not on the set in the audience, you know, you hear the themes bubble up, it becomes really simple, really clear as Peter talked about what is the value of the data and as Bill Schmarzo said, the value of the data is based on the outcome that that data can help influence so it can be big and in fact it can also do a couple of things, the democratization of data for a lot of people to use it and we hear over and over about, you know, can the Excel user use data? I loved your comment yesterday about cloud era, how funny that they were a big data company, you put cloud in their name and we've heard over and over how the impact of the cloud and putting the data and the compute together in the cloud eliminates this, which one do you move? Another great theme, so it's always a really fun event and it's great to get a bunch of alumni's in, we have some new people in and as we like to do, just get smart people, ask them hard questions and let them share the knowledge. And the other thing I like about this event too, not only the things you mentioned is that a lot of the concepts here, what we believe in in our ethos, it's still going to hang on media, and you know, you hear words like streaming, you hear words like community, everything that we do in our business and why I'm so excited to be successful as we continue to grow is we have support from our community and that resonates, we hire from within the community, we have support from our community and we're funded by our community. I wanna thank the community that has sponsored us and you know, mainly I wanna thank Hortonworks because without Hortonworks, we would not actually be doing the big data SV or NYC events, so shout out to Hortonworks who recognizes the community aspect of theCUBE, what it's done and where it's going and I think that's exciting. And IBM, IBM has transformed themselves into a forward thinking company. IBM, thank you for support. Informatica, Pivotal, EMC, Syncsort, Zoloni, DataRobot, Platform, Atunity, SnapLogic, PuduData, Cuball, Teradata, Impetus, Pixata, InfoObjects, and Inforana, a new company that we just interviewed and again, slow of others, it's just for this event, but over the year, I wanna thank you for your support. Your money allows us to increase our production values, allows us to do more, the cube gems, the cube cars, get great guests, hire great people and we wanna thank you for that, so appreciate it, shout out for that. Okay, the event. Peter, Jeff, Peter, go to you first. Really, really seminal moment in this industry because last year, at Big Data SV and NYC, we were kind of teasing it out, but it was pretty clear. The boats were kind of in between wind shifts here. You can see people kind of figure out where to shift their sails. Will the wind be at their back? Will there be a headwind? Will there be a tailwind? But we knew the storm was coming in a good way. The market's exploding. Now we're starting to see some things. The path to digital business, the maturization of tech, the trimming of Hadoop where Hadoop fits the swim lanes, whatever metaphor we're gonna use and more importantly, operational. These were top conversations that we were seeing. What's your analysis of this market right now? Well, I think what we heard over and over and over is number one, and probably more than we even thought going into the session or into the cube event this time, was how are we going to talk about the business outcomes? How are we gonna talk about the business results in a way that actually then turns into product and turns into services? A lot of folks tended to struggle a little bit as they articulated their products and what they're trying to do to get it to that very crisp and clear message. This has a business impact. But you could see them at least, John, at least you could see them trying to do it. And I think if there's, and the second thing we heard was that we need to bring simplification overall to make it easier for the tools and the work that needs to be done with big data to come together so that we get the reliability and repeatability of the business outcome. And we even heard from the folks who came in the cube from the show floor saying, a lot of people, but everybody's kind of milling around. What is, how is this all gonna come together? How are we gonna, who's gonna step up and start doing some of the thought leadership to drive some of that simplification, to drive new ways of thinking about how this generates business. I think that that was kind of a common theme. We heard a lot about it, but I still think people are searching for how it's gonna come together. Okay, and Jeff, you see that, the business impact. Again, love that. You hear in the audience at our event last night that practitioner raised their hand twice almost with pure passion. Your arm was busting out of the shoulder. Where's the actionable insights? And that is another theme is there's a lot of moving parts going on. As this thing is, as the tide's rolling in, the still, the holy grail is the actionable insights. Not only do you find them in context, to the zillion contexts that are out there, but how do you deliver them? And what's the end point? All these things are happening. So the operational, this is so early. I'm now convinced that we've kind of crossed over to a whole nother era. And it's the streaming thing, it's right. It's the real time. The best one though was when we had Bill on. Chamarzo from EMC who spends a lot of time with customers, which is why he's one of my favorite guests is he just starts from the question and he talks about the first session that they do. They don't talk about any products. They don't talk about any technology. They talk about what is the question that you want? Why does it matter? Who are the stakeholders? I mean, basic business 101 that, oh, by the way, we're going to help you solve these problems in ways you didn't do it before with data. And maybe data you didn't even know is valuable, like his airport example. So the myth of just pumping all the data into the lake and putting some magic pixie dust in the form of an acute elephant and having insights pop out or pretty pictures, it just doesn't hold water. It's still, at the end of the day, it's a tool. At the end of the day, you need to have value. At the end of the day, it's really not that different of a business process than what you've been doing in the past. So I'm reading my notes here from some of my things. I want to just throw this out here if you guys get your thoughts. One, just some notables. There's so many to talk about. Just grab a few. Jerry Hall talked about the transitions, where the data is stored, how it's processed, and then the management software. But he really did that from the history of data standpoint. And his point was that if we are going to look at this as an asset that generates value over time, we have to recognize that all the experience we've had of managing data is relevant even today. And then he highlighted also your point about digital currency, digital capital, which I love. Community is the enabler. Here's just some sound bites, fostering collaboration, data sharing economy, make it frictionless. Hadoop is losing relevance, was one comment. Structured data is winning. I love the metaphor of the body being lopped off the top, being lopped off the legs. What's left and how Hadoop is going to evolve to remain relevant? Exactly, I love that. But it's also a bigger market as you pointed out. So people are getting stuck in the definitions now. I think that the good news is it's a huge market, huge growth as you put out with the forecast for the folks out there. We keep on as new forecasts. I'll go get that signed up for that. But the other theme that's coming up, and I love when I hear this, because this to me gets me so pumped, old way, new way. You are now starting to see the polarization of two sides of the street here. Old side of the street, old way of doing things, and the new way of doing things. And that clearly has put an exclamation point around the analytics and the frustration from all the analytics vendors. We have tools saying, damn, I gotta make it easier. I gotta get to the value. I got to go faster, so making it easier. So there's all ramifications to all this. But it's also interesting, John, that again, it goes back to this notion of, what are we gonna carry forward from the old days as we do new things? The idea that Hadoop has been, and a lot of these technologies have been on the side, now becoming part of the enterprise. And some of the practices that we've learned about how to manage data are not onerous, and they're not to keep Hadoop out, but to generate additional value. And so Rishi from InfoObjects talked about, look, yeah, it's old way, some of these practices are old, but they're new to certain members of the community. And we wanna see that come together so that we can accrete value faster. And we heard from Hortonworks the word retrofit's interesting, your renovation. It's not so much a rip and replace. It used to be forklift upgrade, back on the old days. Now it's more tooling and shaving things and making things fit together on an integration basis. A quote that came in today that I wanna share, that I loved, was the fastest way to be productive is not to do the work. And I love that because it highlights the auto- That was Dan Graham at Teradata. Teradata, yeah, fantastic. And automation, really, again, a critical piece. And then last night at your panel, the theme of, and again, this is something that's on my mind years ago, I haven't thought about in a while, but what software is watching the software? So as you got ML machine learning algorithms, you have the data cleaning issue, which has been around in the data business, dirty data, clean data, cleaning the data, cleansing the data. Now you have the same kind of concept of dirty algorithms. So, okay, so dirty algorithms or bad algorithms can create bad results, so you can't just rely on algorithms anymore. So there needs to be a compiler for the algorithms and algorithm for the algorithms. So we are moving to a whole another era of complexity. And again, this is an opportunity. And fast forward lab just a couple of segments go brought up, you know, there is this thing called ethics. You know, there's people involved. There's real things, it's not just machines. And we need to keep an eye on that. But of course, but we started out our first interview with somebody who's got over six million algorithms ready to go and they're building new ones every day. So it's really exciting times. It's why it's really fun to be in this industry because it's this constant invigoration. And, you know, we've gone from Hadoop and we had Hadoop 2.0 and then some people say Spark is Hadoop 3.0 and then we just had, is it Flink? I have to learn the new word. I think Flink is the new hot streaming thing, not to mention Kafka, which is under the cover. So the innovation continues, but you know, Lauren Schwartz from Matunity, who's out there working with customers, you know, they have all these stuff. They've got all this Mongo and Cassandra and NoSQL and Oracle. So, you know, how do you bring it together? But as Peter likes to say, start from the business problem, what's the value, and then figure out how you're gonna solve the problem. One of my favorite interviews amongst the many that we've talked about is, and you mentioned Dan Graham at Teradata was, it was Stephanie McGrennalds from Alation. Yeah, Alation. You know, made a great observation. Obviously extremely bright, very capable, great ideas. It said, this is, these are tools. These are tools. Let's stop going to the marketplace and presuming or pretending or promoting the idea that all you have to do is drop in the tool and suddenly magic happens. There are disciplines that need to be put in place. Will Schmarlser talked about them. There are practices that need to be put in place to make sure that we're taking care of the data. Something that we've talked about a lot. They're just tools. And we all need to recognize that if we're gonna serve the community properly, we have to talk in terms of how the tool gets applied. How do you get value out of the tool? And also on that point of tools, I admit at Informatica talked about the fragmentation of apps or tools and then Hortonworks at the end, the CTO of Hortonworks highlighted the fact that, you know, where's all the confusion coming from? I put them on the spot like, hey, people saying that had dudes got his head chopped off and legs taken out by the cloud. What was your angle on that? And basically it was like, hey, people get confused. Now my words, he didn't say this directly but he basically said, there's a lot of tools out there. So depending on what view you have, you can't pass a tool off as a platform. So platforms are platforms and tools are tools. So they're not the same, but they're different. You need tools. So we're gonna see a variety of new tools as you had speculated and apps, tools and apps could be the same thing. And that really is where Informatica was shining in their value proposition. So again, you're starting to see people find their groove and the dogma is kind of going away, the dogma around Hadoop still a little bit there with cloud area. You see them kind of holding on to it and they just kind of acknowledge it's evolving to quite frankly a very relevant piece of the equation but it's not the whole pie. Hadoop is just a piece of it, an important piece. There's a role for other platforms and tools as well. So I mean, what's your thoughts on that? Well, I completely agree. I mean, at the end of the day, we're looking for, I think Bill Schmarzo said it, as did Stephanie, if it does the job, then let's use it. But let's focus on the job to be done. Let's not focus on the tool and then have the tool seek out something that it can do. So I think we gotta, again, we gotta keep coming back to this notion that the reason why businesses are investing in this stuff is because it generates a return. And if it doesn't, it's not gonna get invested in, whether it's an open source model or not, whether it's a platform or whether a tool. At the end of the day, everybody has to increasingly put themselves in service to the communities that are out there actually creating business value. Okay, so I'm gonna put something on the table as we end the segment here because we have a lot of great stuff coming up. This is Cube Season Start. We've got Dublin and a variety of events. It looks like SAP Sapphire is gonna be an event. We're gonna be going to zillion events coming down. Jeff, I'll probably pull up the list, but I wanna create some controversy. Give me something controversial that's happening in this world that we can put on the table and end with and continue to engagement post-event. Peter, something controversial. I don't think that'd be evil. It could be something productive. I think that the most controversial thing I heard was this notion almost of what I'll call magic data movement, where you just drop in a tool and suddenly data starts moving around on its own and it all works and you don't have to worry about it and you get auditability and you get, it shows up when it's supposed to and you get low cost. There was a tendency to just kind of say, oh no, I'm waving. Forget rid of ETL. I'll say this notion of magic data movement. There were a couple times where I came very close to looking at someone saying, are you out of your mind? Hey, you know, this hallucinogens are coming back and magic bus could always be there too with the magic data movement. Well, the magic bus is what does the magic data movement, right? Absolutely, gotta move the data, Jeff. Something controversial. Something controversial. Again, I think everybody makes it sounds like so easy. It's just, it's not, I mean, my day-to-day job is not easy. Things are not easy. There's still a lot of manual process. So I think probably, you know, Lawrence Schwartz, when he was going through kind of some of the processes they go through with their clients and the complexity of these environments and the historical systems that still need just to be supported and this magic pixie test of visualizations are gonna help you see the light. To me, that's the one that I keep coming back to and the best answer I've ever heard was, well, best visualization might just be a simple two by two, even if it is a billion points of data. I got one more and we saw it a couple times. And maybe it's out there and it just, we just didn't see as much of it in this show. Where are the partnerships? Where are the partnerships? Where are companies coming together with customers to say we've come up with a new way of solving a problem? We kind of presume it's all gonna happen, open source or, but where are those partnerships that are gonna provide the next generation of thought leadership? Because I think that, I think that- And growth. And growth, absolutely. And I think that that was probably the other thing. I thought that we'd hear more about partnerships at this event and it might have been a weakness overall in how a brick and mortar event gets run, but I expected to see, I expected to hear more about- That's interesting. We had a lot of that in New York last year. We had EMC and IBM on together. We had Cloudera and EMC on together. We had Hortonworks and IBM together, I think. I mean, we had a, that's funny you mentioned that. But you know the old expression, barny deal, which for the younger generation who don't know what barny is, barny is a show for kids. And the opening thing is we love you, I love you, you love me. It's a love fest, but there's no real deal there. A barny deal means it's nothing but a press release and it's just for optics and in market, kind of posturing and window dressing. I think there's a lot of barny deals and I guess how my controversial statement would be, I think the sign that the fact that there's barny deals aren't materializing in the real rubber hitting the road. That is an indication of some confusion amongst the main actors in the industry. And to even get more controversial, I think we have zombie leadership at some of the top companies here. And specifically, the companies have had billion dollar valuations that have all cashed out and the management's on the beach clipping coupons. You don't have leadership in a market that needs leadership. So if you have that zombie situation where you have these unicorns being cut down, Cloudera in particular is one of them. If you don't have leadership, you don't have growth and every single company that's come out of the startup generation to become a leader, a global leader in terms of revenue and sustainability, has had leadership in their sector and never once took their eye off the ball. They never once cashed out, they made some money but never went to the beach. If that's the case, then the big boys come in and fleece everything, so Oracle, IBM. So to me, this is a controversial statement. I'm putting it out there because it's a challenge to the industry. The people who take their eye off the ball don't become leaders and get too caught up in the liquidity of the startup world. And certainly we know Cloudera had a lot of eggs. We know Cloudera management, they all cashed out. We know that they're the leader and the question is, are they losing that leadership? It's an open question. We certainly know Oracle was here doing deals last night. I saw Oracle here. I saw IBM here, you're seeing the big guys. That to me is a very controversial statement. I'm gonna leave it there. It's not a diss on Cloudera or anyone else but you got to step up the leadership. Use the cash that you have to create leadership, category leadership. Well, I'll just say the interesting one is Oracle and Dell slash EMC now because you've got the old leadership and they're big boys now. They got a lot of resources and they can move that ship and as you guys talked about it at Cloudworld, Larry, Michael, they can turn the ship pretty quickly even though they're pretty big and they are and they're coming at it pretty aggressively. So the other thing I mentioned, whoops. Ship. Ship, okay. So the other thing I mentioned is the bargain boat that goes very fast. So the other thing I mentioned is the journey, I thought you said something else. No, no, no. That would have been a controversial story. Larry likes ships, we know that. Someone stepped in the ship. The other thing I was gonna mention was and I made one last night at the customer event and that is John that the idea of if this stuff works so well and uncovers the new opportunities so well for customers and drives new marketing leverage so well for businesses, why isn't this industry growing faster than any other industry that's ever existed? And that's I think a really, and it may be that zombie leadership plays a role. The lack of partnership plays a role. The fact that we're not focused on customers and what value that we can create where we're still focusing the tools may play a role but it's pretty clear that one of the first indications that all those things go away is this industry starts growing really fast. So let's take that one step further. So let's just say put the zombie leadership just a controversial state when we have a discussion around it but the other side of the coin is if you have a massively growing market which you have predicted in your forecast and have the data to show that this is gonna be a growing market then it comes down to the right products, right? So having the right products becomes paramount. So back to the leadership piece if the people can continue to have those products that's where you're gonna start to see the action. So the question is, are these products there? And then my controversial statement to answer that would be if people get caught on the dogma of what they had hoped they could become rather than evolving with the industry and Hadoop is a case in point no one would have predicted that Spark would have come in. Those are market forces. That's called market forces. Product market fit has to adjust to the market forces. So I believe that people are overreacting and the infrastructure is developing in real time and we're talking about stuff that's not even ready. We're at machine learning analytics, the end points to serve insights is not baked out. We have all kinds of stuff going on in the back office and the infrastructure from managing clusters to having databases, to having analytics. I mean, I don't think there's anything to worry about but if people try to run too hard they get over their skis, they over rotate whatever the word is, that's the problem. And if the dogma keeps them going forward they gotta step back and pause. If they over promise and they don't focus on the problem that they really solved there's nothing wrong with doing one thing really, really, really well as long as you do it really well with others. And that's what I meant by partnerships. I think that there's not enough of, I think everybody's trying to say, oh no, we're gonna be all things to all people from this little spot in the stack. And I think everybody figures that no, you're not gonna be. So that's putting, that's moderating some of the potential results. And you know, we're predicting somewhere in the 23, 24% range growth for the last year and the next couple of years. Great growth, but that's not blowing the doors off. Yeah, we gotta get some blowing doors going on. I think the other indicator that I'm gonna look for just in my pieces. I wanna look for some of the VC investment data points as a bellwether. Obviously the early stage stuff is fairly easy to do but I wanna see a lot more early stages. I'd like to see B rounds because the B rounds, series B financing, series C is growth capital. That is something that is the indicator of blowing the doors off. Or getting ready to. Or getting ready to, exactly. So the last thing I'll mention, John, for me anyway, is that we had hoped to hear more about applications. We'd hoped to hear more about how the applications are gonna evolve. And that's one of the areas of research that we're gonna focus on over the course of the next quarter or more. Think about how applications happen in this big data space. I don't think we got some of those answers. I think people don't understand. I think my vision, and I've always been saying this and I'm kinda coming back to it. We'll see if I'm right or not. But I think you're gonna see a long tail distribution of a power law. And the question is, what's gonna be the head and the neck of that distribution? And certainly in the long tail, you have specialty tools and apps that are just natively data. They're not gonna be standalone companies. They could be kind of boutiques or cash flow businesses. But it might be a very skinny neck where you only have a few power players win or take most platforms. And that has to power that. So to me, the big company apps aren't coming out. We're not seeing what we saw in the 90s where an ERP app became a fully public company. I think you have to be a platform. You have to be an enabling platform. You have to have open data. So to me, those apps are already kind of developing, but there's no monster flashpoint of, look at the app tsunami coming in. I don't think we're gonna see the tsunami of new apps. It's just apps in general are gonna be everywhere. I think that's something to watch. So, but what I would say, whatever, whether it's the long tail or whether there are gonna be some big ones, I'm not advocating one way or the other. But I am advocating for an agreed upon framework for thinking about how it's gonna unfold. That's what's still missing. All right, guys, thanks so much for a great show. Jeff Frick, Peter Burris. I wanna thank the audience for watching. We appreciate, you know, seventh season of theCUBE where we off to Dublin and you're gonna see the cadence of theCUBE pumping out content. Go to siliconangle.com as a reference point for all the technology, innovation and content. Siliconangle.tv to find out where theCUBE is. Siliconangle.tv. And of course, go to youtube.com so that's Siliconangle for all the videos. And always go to Twitter and search on the hashtag CubeGems and CubeCards to get a snackable nuggets of what's going on in theCUBE. And I wanna thank our sponsors and thank all the team here on the ground from Siliconangle Media and Extended Team and Productions. Guys, great job, fantastic event and production. Thanks so much and we'll see you next time. We'll see you in Dublin.