 Okay we're back here live in Las Vegas, this is theCUBE, SiliconANGLE, and Wikibon's flagship program. We go out to the events, extract the ceiling from the noise. This is Getting Down to the Wire, Dave. I'm with Dave Vellante, my co-host, to the second and last segment here on day two of two days of coverage of Splunk Conference. Sean Rogers, Vice President of Enterprise Management Associates. We say the best for last. Kind of put a bow on the event. Obviously Splunk successful. We were talking about it for two days. Everyone's excited about Splunk and the prospects of their business. Obviously IPO under their belt, clearing the runway, balls in the middle of the fairway, whatever analogy you want to use. It's looking good off the tee. They just launched Cloud, which could be a challenge for them. But they start encroaching into the BI, data warehousing. When you start moving out of IT, welcome to the big leagues. I think it's an exciting jump. We talked about it in their executive panel yesterday about moving with the pivot piece that they've added and all the other features that are in Splunk 6. They've kind of come right up to that line of where the business intelligence, more business analytic folks are at. And they're going to have to make an interesting decision of do they keep using the tools that they have or are they going to jump that fence and start embracing some of the tools that Splunk's bringing. I like the fact that they added a data model. So that's going to make it a lot more open and accessible to other tools. So I like the direction they've come. They've definitely expanded in a way that makes sense to them. I want to get your take on it because obviously you follow the business. You know, you're pretty close to that. I like that analogy, jumping the fence. I haven't seen any signals. I mean, my read on it is that I don't see them copying a business model. So what's nice, they're playing their cards their way. They got the search feature. I like that the data modeling brings the automation in. So I think they're going to have scale up. So I want to get your take on it. What do you see? Are you seeing any indication of what that decision might be? Is it going to go their own way? You know, I don't know if I can predict which direction they're going to go but they're certainly after a new set of users. You know, they very much have been focused on the IT management side since their inception and now they're looking to bring into the fold more business oriented decision makers. And then to do that, they've got to do some of the moves they've made. They're deploying on the cloud now. They've given you a workaround from their search language so that you don't have to use the search language. You can rely upon someone to create a model for you, use the pivot piece. So that certainly opens up the door for different and more people to utilize the platform. Who's done the best job of going beyond IT into the business uses? I mean, traditionally, go back to the decision support days, the BI days, that's been a promise of our industry for a long time. Who's done a good job of that or has nobody done a good job? You know, I can't think of any people that have really jumped that line and we could declare winners. I'd say Splunk has done a great job. I think what's more important is is that the users on the business side have finally come around to, hey, we've conquered this issue of our structured data. We know the insights that we have of our business and now we're interested in bringing new data sources in and new data like machine data from Splunk is very interesting to them to mash up and utilize in their environment. So I don't know if it's, who's done the best job from the vendor standpoint. Maybe it's more about a maturation and a sophistication of the end users on the BI side. Do you feel like those BI end users feel that they've mastered their structured data or do you feel like they're so frustrated that it takes so long to get what they need out of their structured data that they're looking for an alternative? Well, you know, I think it's a little of both. I think some companies definitely have a very good strategy in place and they're executing at a high level. A lot of other companies are bogged down in that 60, 70% of time invested around accessing the data, transforming the data, moving the data. And that's one of the things that Splunk does bring to the table that's rather interesting is its capability to federate on out and not have to muck around so much and spend so much time before you get to value. So I think that kind of touches on the point that you were making. You're explaining that, that's a good, I want to get that drill down on that. What you just said, the time to value, drill down on that, what are they doing that's unique to Splunk and that? Well, you know, traditionally, at least on my side of the world, the data warehouse has always been the well that you went to to draw your water. But in order to get what you want out of the data warehouse, it had to be highly transformed, highly governed. A lot of work and effort went into jamming it into that relational atmosphere or that database system. With Splunk, they have the capability of sort of shifting gears and moving towards data sources very easily, very transparently without doing a lot of transformation or even ETL work in certain circumstances. Splunk doesn't move all the data, it only moves what it needs, it creates indexes right at search time. So you avoid all of this upfront investment of time, energy, money, and you get the customer or the end user to the value a lot quicker. And it tends to match the speed of a lot of businesses today. When I got into the BI space 15, 20 years ago, we were all excited to get a report that told us what we did a month ago. Now people want to get access to information in a much faster, more business oriented fashion, certainly at a speed that matches whatever their business is. So you're pretty high on Splunk 6. I mean, obviously, you mentioned that. What are your thoughts on the other two announcements or maybe not announcements, the things they've been stressing here, the cloud, let's start with that and then hunk. Yeah, I'm a big proponent of having various ways to deploy your solution. I think the customers of Splunk have been asking for cloud for a while and I think they've put their foot in the water in the best possible way. They've got two solutions. They have the free version that's capped at, I think, 20 gigabytes of information which allows someone to commit and adopt and figure it out and then they've got the fully featured version of Splunk Enterprise on the cloud, which I think it was smart of them to make sure that they made it match the desktop version, to make sure that it was feature rich, to make sure it wasn't crippled and to make sure that you could utilize it as a fully functional, fully featured solution just like the one that you may have invested in previously. So I like the product mix. I like the approach. I think that they're going to have to look at hybrid deployments of the enterprise version. Just relying on Amazon as a platform will get them so many customers, but there'll be other clients and customers that are going to come along and say, look, we want our data under a little bit better control. We have governance or compliance issues around some of our information and we want maybe to host it behind our firewall or they might impose upon Splunk to offer it as well. And how about Hunk? What are your thoughts there? I think the name is funny, but the functionality is great. Any way that you can bypass the skill set issues that come with Hadoop and come as a challenge to talking to Hadoop, I think makes a lot of sense. And I like the fact that they're recognizing Hadoop as a viable data source and also a platform for their use. What do you think about their opportunity in the internet of things? Still early. It does come up on our trending dashboards kind of as a small data point outside of the whole search and Splunk data management side of it. But obviously, you don't have things thrown off data. It's just another data source. Yeah, it is an important one. But it's an important one. It's one that's going to grow and it's going to be extremely diverse. And Splunk seems rather well situated to deal with that type of information. They're not pigeonholed as a lot of the BI solutions that I've grown up using, looking for those relational sources. Splunk looks at just about every source under the sun. It's hard to find one they won't talk to. It's nice about Splunk because you can't really get your arms around them and put them in a box. You can't, like you said, pigeonhole them because they move the goalposts a little bit in terms of how they're approaching the market because they came from a unique position. They grew up from ID in the log files. So I mean, come on, that's where the action is. So they went from exhaust to now top of the food chain in terms of the data. That's a great way of playing. So I mean, you're talking business value. This is the big leagues. What's the competition going to look like? Assume that Splunk continues to go on their way and do their thing their way. They change the game a little bit so it forces a little bit of competitive strategy for their incumbents. So what do you see them reacting to? You know, they're going to get faced with an awful lot of interesting, I think, challenges. One of the things that I've seen in the sessions I've been able to attend while I'm here is everyone's talking about how they use Splunk to do stuff that Splunk's not supposed to do or at least that isn't the traditional definition of what Splunk's marketing department might suggest that you do with it. People are out there doing some really interesting things. I was in a session today where someone was using Splunk to identify recommendation engine data and feeding it to MongoDB. That's not what we talked about with Splunk two years ago. So they are going to bump into some of the traditional analytic players, some of the traditional process players, and they've got a good fight ahead of them, but I frankly think they're positionable. The beautiful thing is they're not the one pulling the trigger. The customer's themselves doing it. Yeah, well that's the best part, right? That's the best part, smoking gun. We're just smoking gun. It's not Splunk. It's the customers doing it. I haven't seen any material that said go out and do these types of things. You have all these customers here going, oh yeah, we've bent it this direction. That's a good definition of a platform. I mean, I think that is true enabling technology. Yeah, yeah. So what are your thoughts on the whole Hadoop space? We've been tracking that now for some time. You're starting to see some alignments occur, the partnerships occur. We had Amar Awadallah on yesterday. It's talking about their Oracle partnership, but also at the same time talking about how they want to be the platform for everything. How do you see that, ShapeMap? I ask this question a lot. If you got the Hadoop tail right now wagging the dog, do you see that flipping around? Well, you know, I think it can flip and I think there's two things going on in the space that are kind of interesting. One is, is we're seeing big data workloads happening in an ecosystem of platforms, not just Hadoop. And I think some members of the press have taken us down that road of big data always seems to equal Hadoop. Hadoop's a great platform. It could be critical for that type of work, but in the end, a lot of different purpose-built platforms are playing a role there. The other side of it is we just finished some research at EMA, and by that, I mean just a couple of days ago, and we found that the leading Hadoop distributions weren't who we expected. So we were fully anticipating to see some of the more innovative companies that we might see here at a Splunk event or maybe at a Strata-type show. And the two big names that came out at the top of our research were IBM and Intel. And we were especially surprised by Intel, because as both of you guys know, they just announced their Hadoop distribution. We've seen a lot of Intel, too, it was being very aggressive, but of course they're packaging it with a lot of their OEM parts. You saw the Intel, they got the distribution change. You got Hortonworks out there with a Hadoop data platform. You got Intel, and SAP just did a deal recently. I don't know if you saw that deal. What do you think of that? I don't know the details of that one, so I can't really comment on it. The Intel thing's interesting. We look at them as kind of not making their bet yet, because I don't think they have to. They don't have to make a move at this point. I think it's a safe bet for Intel to get their hands on a distribution, because they don't know where they could use that. We did a little further analysis on where the adoption was coming from. We also saw that they have much greater traction in the APAC region, where IBM's getting most of their traction out of North America. Okay, that's interesting. Yeah, it was, very interesting. And the other players, the innovative guys, the Hortonworks and Cloudera's and even Pivotal, much farther down on the list. What do you think about the balance of, this is more a big data question. Dave and I were talking earlier, haven't gotten our arms around it yet, but you've got the open source software movement, and obviously that's happening. And the business explosion of business value, it's always kind of like a balancing act, right? So the pressure to code and contribute code has always been, I joined in my conversation, but now the business value, the pressure, the demand on big data technologies. So let's take in the Apache Software Foundation and the business world. So are you talking about the need for those larger companies to contribute to the open source world or that split that we're seeing from an adoption where some are going open source and some are going to names that they're more used to dealing with? Because we think that that speaks to the maturity of the market as well. Well, I want to get your perspective on how to frame it because like we're talking to Cloudera and it seems like obviously they're donating through open source, but like the greed factor, when money's on the table, right? I mean, hey, I love religion. I love to go talk about open source, and you got the money on the table, companies like Splunk, the way they're printing money right now. It's like, you know, a lot of these guys, pure open source. I got to see a lot of that in the BI and analytics space with some of the open source data integration, like Taland is a good player in that space. You look at Jaspersoft and Pentaho, they kind of came up the ranks of the open source world and they've all kind of found their balance, their offering and kind of that standard array of here's the open source offering, but here's our offering. And of course, there's this more enterprise, I think, focused, and that's the trouble with the open source stuff is it's an easy entry, but there's an awful lot of work that has to be done. My research partner, John Myers, likes to say that Hadoop is free like a puppy. And I've heard a few people say that, but that's the trouble with some of the open source solutions that are in the market is you get into the initial piece of software in a very low capital outlay, but then there's skill sets and then there's maturity of the platform to deal with. And I think that that's the pain that some are seeing around the Hadoop. Yeah, we heard from Amar Al-Adal saying, you know, they're doubling down on CDH and basically what he was, I'm paraphrasing enough, Amar, we got to get the foundation set. They got to actually do the things that are boring or important table stakes. I mean, there's some table stakes I need to get done. That's not the sexy, putting in the new features into this open source. So is that a conflict, I think it, you know, I don't know if conflicts are a business model and one's donation, one's marketing, right? So like, or, you know, I just don't, I just can't, I'm having a hard time resolving that. I think the software companies are having a hard time resolving that. Trying to figure out how much to put into the community version or the community itself is a difficult thing for them. Dave, what's your take on them? Because the more they give, the tougher it gets to reap the reward. Well, I got to ask you, Sean. So John and I asked our power guests who have an opinion on Hadoop and big data, the following question. Will there be a red hat of Hadoop? Oh yeah, that's a good question, right? We got to see it in the Linux world and, yeah. Yeah, and we'll be ready. We can't be ready. You know, I think we might. I think that there's enough big name effort around different Hadoop distros to do that. And I think we saw the same thing in the Linux world with Red Hat. And I think we may very well see the same thing with Hadoop, wouldn't surprise me a bit. Yeah, so, and then the other question I have for you is so you've got this interesting juxtaposition and I alluded to it earlier. You have these alignments, these relationships. Hortonworks and Microsoft, Cloudera and Oracle. You got, actually, you got Pivotal and GE, which is a whole nother vector that maybe we can get down later. But you've got sort of the traditional scale up, you know, a million dollar box crowd pairing up with the scale out, no sequel open source crowd. What happens there? Does Oracle just buy everybody and then act like they invented it? Or will these guys actually disrupt? We're probably talking about disruption and crossing the chasm and how the world's going to end. And it seems like the rich keep getting richer. What's your take on all that? You know, from the adoption, I think the adoption side is going to probably push a lot of this forward. It's going to help us pace how quickly that change is going to come. The research that we just did, we looked at 600 active projects. 16% of those projects or companies doing those projects had five or more projects underway. So we've definitely, to your word, crossed that chasm of adoption where a year or two ago it was hard for us to find people who were doing big data research or big data projects. Now they're pretty simple to find and they're doing really mature work. So I think the winner of the race is either going to be through acquisition and the roll up that we often see in innovative markets or it's going to be who can get the mundane things to John's point of the infrastructure, the mechanical side of it, the easy to manage side of it so that it can slip into the enterprise in a seamless way. Now, I'll use Kristen Chabot, CEO of Tableau, right? He comes on theCUBE and he gives us keynotes and he talks about the old line BI companies and he accentuates the pace. Christian does like to do that. Very good, right? And then the other vector, you got Excel. Yep. And you feel like, I feel like Hadoop sort of drove a truck between that and sort of allowed this new growth in the marketplace. So what happens to the traditional BI guys in your view? What do they have to do to thrive? Well, I think they can't ignore this new change around the information and the data. They certainly can't ignore big data. Our number one use case or at least how people are treating data with Hadoop is they're archiving it but they're doing it in a smart manner so they're not just dumping on this platform, they're using it to sort of power up or tee up data and information to help their enterprises move faster. I think the traditional BI players who aren't paying a lot of attention to this are going to be in a tough spot because there is sort of a paradigm shift going on with this idea of good enough analytics, meaning I don't have to put everything through this tightly squeezed and constrained data quality process. I don't have to transport form every drop of information. We can take a look at the data on a faster platform like at Hadoop, get a generally good answer to steer the ship by. And that is a paradigm change away from tapping into the sanctified world of an enterprise data world. There's a spectrum of acceptability to sort of use your term. And ultimately, based on this, we've come a full circle now, that Hadoop tail, a big data tail, could ultimately become the dog. Very much can be. We've seen some architectures that are literally tipping on their side and using Hadoop as this transformation base to steal from that great article, I think that was in the times about, you know, data's the new oil. Well, as we refine information as it comes into our ecosystem, we're refining it for jet fuel to this app, we're refining it to unleaded for this app, but we're continuing to leave the atomic data in a structure like Hadoop so that we can always get back to the details, which frankly is one of the drums that Splunk was beating this week. Their capability of being able to jump all the way backwards to, no matter where you're at in their environment, to always get to the source information. Sean Rogers with Enterprise Management Associates. Thanks for coming on. I'll give you the last word about the show here. I want you to share with the folks out there who aren't here, who can't see and feel what's happening. How would you describe this event past two days, the vibe, the content, the people? What's it like here? You know, a couple adjectives jumped to mine crowded. I think they grew a little faster than they expected to this year, and there's a level of that almost cult-like passion around the Splunk solutions that I used to see with the SaaS solution. I used to see with a couple of other vendors in the space. There is this real kind of club community feel here, and it is a blend of sort of hackathon and open source and enterprise, and I found it interesting that they gave us all hoodies. I was going to wear mine to the interview because I like the idea of being a hoody data guy right now. Certainly a lot of testimonials and happy customers. I mean, people are thrilled to product. Sean, you're a thought leader. We got to put a star next to your name because we want to get you on the crowd chat, our new product, this new social media thought leadership. We're going to get you on board with that. Great content as always. You cover big data, the space, great commentary. This is theCUBE. We'll be right back with our wrap-up of day two of our two days of live coverage here with John Furrier and Dave Vellante. We'll be right back.