 Live from Boston, Massachusetts, it's the Cube at the HP Vertica Big Data Conference 2014, brought to you by HP with your hosts, John Furrier and Dave Vellante. We're on big data analytics and one of the key topics of course is the ecosystem. We talked throughout the last two days about the importance to not just HP Vertica but to the entire kind of big data ecosystem to really integrate the different technologies and approaches that make up big data to make it more consumable for practitioners. And in this segment we're going to talk a little bit about that. We've got two guests, Ashley Sturrup who's the CMO of Talent and Steve Murphitt, Director of Technology Alliance at HP Vertica. Guys, welcome to the Cube. Thank you. Thank you. So yeah, thanks for coming and you know as I mentioned and we talked about on the show, you know there's a lot of different pieces that make up quote-unquote big data and of course you've got to integrate those together and I know from HP Vertica's perspective it's really important to kind of build that Alliance network. Why don't you tell us a little bit about kind of your approach Steve in terms of building that network of partnerships? Sure, so basically we have, as you say, the important thing is the customers can have the different products work together in integrated fashion. They don't have to be concerned about the different pieces working together. And so what my team does is we work with the various partners. We get the software in-house, we give them access to Vertica databases and we test as much as we can those integrations. We look for points where the sequel or the interactions between the products can be improved, some of it we feed back to our product management and some we feed back to the product management at the partners so that over time integrations get better and the customers get a better result. So this is much more than kind of a marketing partnership. This is you're actually getting guys in the lab working together to kind of build those connection points? Exactly, we have a full-time team that's focused on integration and testing with the various products. Obviously we go out and we try to understand which ones are important to our customers and to our prospects and to the markets and try and focus on those. But we also have to be aware of the upcoming ones as well because you need to watch for the next big company that's coming along and make sure that you don't just focus on what's said now but what's coming in the future as well. So Ashley, tell us a little bit about talent. We've had some folks from talent on theCUBE over the years but I think it would be good to kind of talk to our audience a little bit about the role you guys play. Obviously data integration is an important part of the ecosystem. There's some major giant companies out there in this market. Where does talent fit in the overall ecosystem? Yes, the talent was founded in 2006. We're an open-source data integration company. We help our customers integrate data in batch, in real-time application integration and through master data management. And really where we stand out in the marketplace is the fact that we're open-source and we have a very open platform and that we've unified all these different pieces together so that a customer can go from doing data integration in a bulk fashion to then providing real-time capabilities integrated in with their different applications and then over time getting to a single golden record around a customer master or a unified product catalog. So that's kind of our overall value proposition in the marketplace. And we've been working with Vertica for a long time and we're really proud of the partnership we've got with them. We invest a lot in making sure that we're taking advantage of the latest capabilities that come out in Vertica. One of our real strategies is that you're working with a very simple drag-and-drop user interface that talent provides and that it's generating code that runs natively in an HP Vertica and so that it's taking advantage of all the capabilities that they've built in. So obviously, Vertica is one important player. There's others in the market. How do you go about making those investment decisions in terms of who you're gonna invest in in terms of a partnership level? Resources are limited. How do you make the decisions around, hey, these are the players, the database players or maybe the Hadoop players, wherever it might be. These are the ones we need to go after and really integrate tightly with. Yeah, that's a great question. I mean, it's such a fast-moving market these days. And we have over 1,800 customers including some of the biggest brands in the US, very large companies in Europe as well. And so we spend a lot of time listening to our customers. We also spend a lot of time working with partners like HP Vertica looking at the overall evolution of the landscape. We partner very closely with the Hadoop distributors to name a couple others. And across the board, we're looking at what the different elements of innovation are that are out there in the marketplace and evaluating which ones are ready for prime time. And we've got kind of open-source projects going on for the newer stuff. And then as it matures, we put that into our enterprise products. So Steve, we've been talking a lot about it on the show over the last couple of days about really the business value of the big data analytics. So it's a lot more than just the data. It's about bringing that value to the fore. So again, how does the, speaking about the partnership and the alliances, how do you go about making similar decisions about where we need to partner? Where are the most important areas to partner or with so that we're delivering the most value to our end users? Sure, so basically it's trying to understand which are the use cases that people are trying to use Vertica with. What are they trying to do with it? So, and then there are various components to that. So at the moment, the predominant things that people are trying to do with Vertica seem to be, how do we get data into Vertica efficiently? And so again, that's where companies like Talent come in. We also then have to look at what are they trying to do with that data once it's there. So the visualization products, the BI type products, and then now the other area that's becoming more and more important is the predictive. So which are the predictive products that we can work with as well and how can we help them to leverage more Vertica? And then what you're doing is you're looking at the market trying to see who are the ones who you must work with and then which ones are friendly to you because at the end of the day it has to be a partnership. If they're not committed to working with you as much as you want to work with them, that obviously makes it much more difficult. Yeah, so Steve just mentioned one of the requirements or use cases around more real time, whether that's either interactive or actually more streaming capabilities. So actually, can you talk a little bit about how you approach that? You mentioned obviously, and we think people think data integration, they often think ETL and kind of batch loading, but you mentioned real time is an area you are involved with as well. What are you seeing in terms of trends around real time uses of data as this market starts to mature a little bit more? Yeah, well, I mean, first I'd say is that not every product meets every need, right? And so one of the things I think that HP Vertica's done a great job with is looking at how they can partner with the Hadoop to make sure that the right kinds of analytics are being done using the Hadoop database and that they're using their capabilities to support more of the real time use cases. And then in terms of a talent's perspective on that, what we're seeing is customers go through this evolution, right? The first thing is okay, there's this whole new data source that I want to start to analyze. How do I do it? What are the best tools to put in place? How can I get that data? And then once you start to get that kind of access to insight, okay, now how do I deliver it at the point of use, right? Where, say, a salesperson's on the phone with a customer knowing exactly what to cross sell and upsell. So I really see customers going through that journey. And same question you, what are you seeing in terms of as these real time workloads start to become more important? Again, from a partnership perspective, obviously you're working with talent. Are there other technologies or other areas that are important in terms of supporting some of the more real time use cases, which of course Vertica is, that's all about real time and interactive capabilities. Sure, obviously real time means different things to different people. And so maybe just in time is probably more of a phrase that we look to do more often rather than real time. It is a confusing term as our CEO, Dave Vellante, says just in time for him means fast enough so that you save the customer, you don't lose the customer. So it all depends on your point of view. But nevertheless, Vertica has come to be known as that really performant, high performant, for lack of a better term real time or near real time database. So is that, from a partnership perspective, is that, how does that impact as you start to see real time become more important, who you align with and who you, again, invest some of your time with? Sure, and again, what we're looking at is the products and understanding where they're moving towards that real time capability as well. So are they looking to be able to stream data into us rather than trying to batch it and put it into us? Obviously again, but having a platform like ours, we're also looking at the companies that are embracing the more ELT rather than trying to do too much with the data on the way in because that's, we believe, it's going to be slower than getting the data there and then processing and making it available quickly. Yeah, I mean, you know, actually, this whole idea around big data about bringing the compute to the data rather than bringing the data to the compute, I think it's having a pretty big impact on the data integration market and field. How does talent view that and have you had to adjust kind of your approach as that concept of, you know, data is heavy when you're talking about big data. You don't want to move it around too much. How does that impact data integration vendor? Well, that actually plays very well with our overall architecture. You know, we are a code generator, so we're generating pig and map reduce and SQL that that's being run locally. And so it completely aligns with this new computing paradigm and allows you to take full advantage of the both the performance and the cost benefits of that approach. So the idea is abstracting ways and the complexity is where you can value to this equation. Yeah, that's a great point. Yeah, so what we're doing is we're making it easier for customers to generate that code, whether it's SQL or MapReduce or Pig. Through a drag and drop user interface, it simplifies a lot of the connectivity and the actual coding part of it and managing that code, but still allows you to run it locally where it's going to get the best performance. So let's talk a little bit more about kind of talent. You can't get a business update. I know you guys were kind of founded as a French company. You've got, I think, dual headquarters in the U.S. I think it was correct. What's your business look like in terms of, you know, Europe versus U.S. Are you still expanding here in the U.S.? What's the state of operations? Yeah, it's an exciting time here at Tallinn. So the company is over 400 employees now. Our global headquarters is now officially in Redwood City. So recently, just last week, moved into a new offices. We, like many of the players in the space, have raised, we raised $40 million last year. So we're making big investments in sales and marketing. And, you know, that's being driven by the overall explosion in data, particularly in the big data space, internet of things, cloud computing, mobile devices are all generating huge new sources of data. And so our big data integration products are selling particularly well. But we're also seeing a lot of momentum around master data management. So how do you get this single view of customer? And how do you get, you know, a more aligned supply chain, which makes a lot of sense. You've got all this new data, but you need to still make it customer-centric or product-centric while you're using it. Right. Well, that's interesting, because the whole idea of kind of that 360 degree view of your customer, I mean, that's not new. That's been around prior to the big data movement. But I think a lot of people in the pre-big data world were struggling even then. I would imagine this makes it, the potential value of getting that view is even more valuable now in the big data world. But it's also probably more complex because we've got all these new data sources. How are we going to do this in this big data era, get that single view where maybe in, you know, pre-big data, it was still difficult even then? Right. Yeah. Sorry. No worries. Yeah, so that's a great question. And in general, what we're seeing as a trend in the marketplace, you know, the rise of cloud computing is leading to more and more digitization of processes across companies. And more and more of our customers are realizing that where they're going to get competitive advantage is how they use all these different applications, but they can't use them in silos. They need to bring them together. So whether you're trying to bring in sentiment data or clickstream data or something like that, you need to be looking across all the different aspects of your business to really optimize it. And so that plays really nicely, again, into our approach because we have a unified platform that allows you to do both do data integration as well as application integration, master data management with one set of tools, you're much more likely to be successful in how you pull all that together. The other key thing that we think is really important is giving our customers the flexibility to start small and think big so that they can grow over time where they're identifying a particular business problem. The cross-sell-up sell is a great example, again. And optimize around that and then continue to add on additional use cases, business problems they're trying to solve. Because what we see all too often with these master data management projects is they get too focused on bringing the data together and trying to cleanse it. And then they don't think about the second half of the problem, which is, okay, how are we gonna use it? Where are we gonna deliver that insight? How do we keep it clean now that we've got it clean? And so we've got tools to allow people to do that end-to-end approach, but in a much smaller incremental way that's lower risk. So rather than trying to do this one big project where you're gonna get this pristine copy of your data, take a more incremental approach. Yeah, yeah, because all too often people say, 360-degree view of the customer is what we're trying to get to, but they don't have a clear thought out, how is this gonna change the business? How are we actually gonna drive better business? So it's one thing you are, you get that 360-degree view. All right, well, let's go now what? Right, right. You gotta think about that now what? Before you start the project. That's right, who needs it? When do they need it? How are they gonna get access to it? Because most of these cloud applications, they're focused on sales or customer service or something else. So they're not built to provide that whole 360-degree view, interesting. So Steve, in terms of looking forward, what's on the horizon for you? Do you see any kind of new, either new technologies or new companies coming up from an alliance and partnership perspective? What are you keeping an eye on as you start to, as you plan the next six, 12, 18 months? But we're always using companies like yourself to help us be aware of what we should be looking at. They're looking at the startups and what's happening there and just seeing which ones are getting traction. Obviously, what we try and do is split our team up so that we can have somebody whose job it is to be aware of that and to keep an eye on that to make contact with them and understand how they're going to work with us. And then, obviously, keep an eye on trends and seeing if there are gaps in our coverage where there are certain products where we don't have quite the coverage that we need and filling those gaps as well. And then working with our customers to understand their pain points and where integrations need to be improved together as well. Yeah, it's always good to keep you on the pulse of your customer base. They will often tell you precisely where you need to be focusing. So guys, I wish we had more time, but we unfortunately are out of time. So thanks for joining us, Ashley and Steve, really appreciate it. You're watching theCUBE. We are live here at the HB Vertica Big Data Conference in Boston. We'll be right back with our next guest after this. Stay tuned.