(upbeat electronic music) >> Live from San Jose, in the heart of Silicon Valley, it's theCUBE. Covering Dataworks Summit 2018, brought to you by Hortonworks. (electronic whooshing) >> Welcome back to theCUBE's live coverage of Dataworks, here in San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We have two guests in this segment, we have Steve Wooledge, he is the VP of Product Marketing at Arcadia Data, and Satya Ramachandran, who is the VP of Engineering at Neustar. Thanks so much for coming on theCUBE. >> Our pleasure and thank you. >> So let's start out by setting the scene for our viewers. Tell us a little bit about what Arcadia Data does. >> Arcadia Data is focused on getting business value from these modern scale-out architectures, like Hadoop, and the Cloud. We started in 2012 to solve the problem of how do we get value into the hands of the business analysts that understand a little bit more about the business, in addition to empowering the data scientists to deploy their models and value to a much broader audience. So I think that's been, in some ways, the last mile of value that people need to get out of Hadoop and data lakes, is to get it into the hands of the business. So that's what we're focused on. >> And start seeing the value, as you said. >> Yeah, seeing is believing, a picture is a thousand words, all those good things. And what's really emerging, I think, is companies are realizing that traditional BI technology won't solve the scale and user concurrency issues, because architecturally, big data's different, right? We're on the scale-out, MPP architectures now, like Hadoop, the data complexity and variety has changed, but the BI tools are still the same, and you pull the data out of the system to put it into some little micro cube to do some analysis. Companies want to go after all the data, and view the analysis across a much broader set, and that's really what we enable. >> I want to hear about the relationship between your two companies, but Satya, tell us a little about Neustar, what you do. >> Neustar is an information services company, we are built around identity. We are the premiere identity provider, the most authoritative identity provider for the US. And we built a whole bunch of services around that identity platform. I am part of the marketing solutions group, and I head the analytics engineering for marketing solutions. The product that I work on helps marketers do their annual planning, as well as their campaign or tactical planning, so that they can fine tune their campaigns on an ongoing basis. >> So how do you use Arcadia Data's primary product? >> So we are a predictive analytics platform, the reporting solution, we use Arcadia for the reporting part of it. So we have multi terabytes of advertising data in our values, and so we use Arcadia to provide fast taxes to our customers, and also very granular and explorative analysis of this data. High (mumbles) and explorative analysis of this data. >> So you say you help your customers with their marketing campaigns, so are you doing predictive analytics? And are you during churn analysis and so forth? And how does Arcadia fit into all of that? >> So we get data and then they build an activation model, which tells how the marketing spent corresponds to the revenue. We not only do historical analysis, we also do predictive, in the sense that the marketers frequently done what-if analysis, saying that, what if I moved my budget from page search to TV? And how does it affect the revenue? So all of this modeling is built by Neustar, the modeling platform is built by the Neustar, but the last mile of taking these reports and providing this explorative analysis of the results, that is provided by the reporting solution, which is Arcadia. >> Well, I mean, the thing about data analytics, is that it really is going to revolutionize marketing. That famous marketing adage of, I know my advertising works, I just don't know which half, and now we're really going to be able to figure out which half. Can you talk a little bit about return on investment and what your clients see? >> Sure, we've got some major Fortune 500 companies that have said publicly that they've realized over a billion dollars of incremental value. And that could be across both marketing analytics, and how we better treat our messaging, our brand, to reach our intended audience. There's things like supply chain and being able to more realtime analyze what-if analysis for different routes, it's things like cyber security and stopping fraud and waste and things like that at a much grander scale than what was really possible in the past. >> So we're here at Dataworks and it's the Hortonworks show. Give us a sense of the degree of your engagement or partnership with Hortonworks and participation in their partner ecosystem. >> Yeah, absolutely. Hortonworks is one of our key partners, and what we did that's different architecturally, is we built our BI server directly into the data platforms. So what I mean by that is, we take the concept of a BI server, we install it and run it on the data nodes of Hortonworks Data Platform. We inherit the security directly out of systems like Apache Ranger, so that all that administration and scale is done at Hadoop economics, if you will, and it leverages the things that are already in place. So that has huge advantages both in terms of scale, but also simplicity, and then you get the performance, the concurrency that companies need to deploy out to like, 5,000 users directly on that Hadoop cluster. So, Hortonworks is a fantastic partner for us and a large number of our customers run on Hortonworks, as well as other platforms, such as Amazon Web Services, where Satya's got his system deployed. >> At the show they announced Hortonworks Data Platform 3.0. There's containerization there, there's updates to Hive to enable it to be more of a realtime analytics, and also a data warehousing engine. In Arcadia Data, do you follow their product enhancements, in terms of your own product roadmap with any specific, fixed cycle? Are you going to be leveraging the new features in HDP 3.0 going forward to add value to your customers' ability to do interactive analysis of this data in close to realtime? >> Sure, yeah, no, because we're a native-- >> 'Cause marketing campaigns are often in realtime increasingly, especially when you're using, you know, you got a completely digital business. >> Yeah, absolutely. So we benefit from the innovations happening within the Hortonworks Data Platform. So, because we're a native BI tool that runs directly within that system, you know, with changes in Hive, or different things within HDFS, in terms of performance or compression and things like that, our customers generally benefit from that directly, so yeah. >> Satya, going forward, what are some of the problems that you want to solve for your clients? What is their biggest pain points and where do you see Neustar? >> So, data is the new island, right? So, marketers, also for them now, data is the biggest, is what they're going after. They want faster analysis, they want to be able to get to insights as fast as they can, and they want to obviously get, work on as large amount of data as possible. The variety of sources is becoming higher and higher and higher, in terms of marketing. There used to be a few channels in '70s and '80s, and '90s kind of increased, now you have like, hundreds of channels, if not thousands of channels. And they want visibility across all of that. It's the ability to work across this variety of data, increasing volume at a very high speed. Those are high level challenges that we have at Neustar. >> Great. >> So the difference, marketing attribution analysis you say is one of the core applications of your solution portfolio. How is that more challenging now than it had been in the past? We have far more marketing channels, digital and so forth, then how does the state-of-the-art of marketing attribution analysis, how is it changing to address this multiplicity of channels and media for advertising and for influencing the customer on social media and so forth? And then, you know, can you give us a sense for then, what are the necessary analytical tools needed for that? We often hear about a social graph analysis or semantic analysis, or for behavioral analytics and so forth, all of this makes it very challenging. How can you determine exactly what influences a customer now in this day and age, where, you think, you know, Twitter is an influencer over the conversation. How can you nail that down to specific, you know, KPIs or specific things to track? >> So I think, from our, like you pointed out, the variety is increasing, right? And I think the marketers now have a lot more options than what they have, and that that's a blessing, and it's also a curse. Because then I don't know where I'm going to move my marketing spending to. So, attribution right now, is still sitting at the headquarters, it's kind of sitting at a very high level and it is answering questions. Like we said, with the Fortune 100 companies, it's still answering questions to the CMOs, right? Where attribution will take us, next step is to then lower down, where it's able to answer the regional headquarters on what needs to happen, and more importantly, on every store, I'm able to then answer and tailor my attribution model to a particular store. Let's take Ford for an example, right? Now, instead of the CMO suite, but, if I'm able to go to every dealer, and I'm able to personal my attribution to that particular dealer, then it becomes a lot more useful. The challenge there is it all needs to be connected. Whatever model we are working for the dealer, needs to be connected up to the headquarters. >> Yes, and that personalization, it very much leverages the kind of things that Steve was talking about at Arcadia. Being able to analyze all the data to find those micro, micro, micro segments that can be influenced to varying degrees, so yeah. I like where you're going with this, 'cause it very much relates to the power of distributing federated big data fabrics like Hortonworks' offers. >> And so it's streaming analytics is coming to forward, and it's been talked about for the past longest period of time, but we have real use cases for streaming analytics right now. Similarly, the large volumes of the data volumes is, indeed, becoming a lot more. So both of them are doing a lot more right now. >> Yes. >> Great. >> Well, Satya and Steve, thank you so much for coming on theCUBE, this was really, really fun talking to you. >> Excellent. >> Thanks, it was great to meet you. Thanks for having us. >> I love marketing talk. >> (laughs) It's fun. I'm Rebecca Knight, for James Kobielus, stay tuned to theCUBE, we will have more coming up from our live coverage of Dataworks, just after this. (upbeat electronic music)

>>Live from Las Vegas, Nevada. It's a queue at HP. Discover 2014 brought to you by HP. >>Welcome back, everyone live here in Las Vegas for HP. Discover 2014. This is the cube we're out. We go where the action is. We're on the ground here at HP. Discover getting all the signals, sharing them with you, extracting the signal from the noise. I'm John furrier, founder of SiliconANGLE. I joined Steve Woolwich VP of product marketing at map art technologies. Great to see you welcome to the cube. Thank you. I know you got a plane to catch up, but I really wanted to squeeze you in because you guys are a leader in the big data space. You guys are in the top three, the three big whales map are Hortonworks, Cloudera. Um, you know, part of the original big data industry, which, you know, when we did the cube, when we first started the industry, you had like 30, 34 employees, total combined with three, one company Cloudera, and then Matt are announced and then Hortonworks, you guys have been part of that. Holy Trinity of, of early pioneers. Give us the update you guys are doing very, very well. Uh, we talked to you guys at the dupe summit last week. So Jack Norris for the party, give us the update what's going on with the momentum and the traction. And then I want to talk about some of the things with the product. >>Yeah. So we've seen a tremendous uptick in sales at map. Are we tripled revenue? We announced that publicly about a month ago. So we went up 300% in sales, over Q3, I'm sorry, Q1 of 2013. And I think it's really, you know, the maturity of the market. As people move more towards production, they appreciate the enterprise features. We built into the map, our distribution for Hadoop. So, um, you know, the stats I would share is that 80% of our customers triple the size of their cluster within the first 12 months and 50% of them doubled the size of the cluster because there's the, you know, they had that first production success use case and they find other applications and start rolling out more and more. So it's been great for us. >>You know, I always joke with Jack Norris, who's the VP of marketing over there. And John Frodo is the CEO about Matt bars, humbleness. You don't have the fanfare of all the height, depressed love cloud era. Now see they had done some pretty amazing things. They've had a liquidity event, so essentially kind of an IPO, if you will, that huge ex uh, financing from Intel and they're doing great big Salesforce. Hortonworks has got their open source play. You guys got, you got your heads down as well. So talk about that. How many employees you guys have and what's going on with the product? How many, how many new, what, how many products do you guys actually, >>We have, well, we have one product. So we have the map, our distribution for Hadoop, and it's got all the open source packages directly within it, but where we really innovate is in the course. So that's where we, we spent our time early on was really innovating that data platform to give everything within the Hadoop ecosystem, more reliability, better availability, performance, security scale, >>It's open source contributions to the court. And you guys put stuff on top of that, uh, >>And how it works. Yeah. And even some projects we lead the projects like with Apache Mahal and Apache drill, which is coming into beta shortly other projects, we commit and contribute back. But, um, so we take in the distribution, we're distributing all those projects, but where we really innovate is at that data platform level. So >>HP is a big data leader officer. They bought, uh, autonomy. They have HP Vertica. You guys are here. Hey, what are you doing here? Obviously we covered the cube, uh, the announcement with, uh, with, with HP Vertica, you here for that reason, is there other biz dev other activity going on other integration opportunities? >>Yeah, a few things. So, um, obviously the HP Vertica news was big. We went into general availability that solution the first week of may. So, um, what we have is the HP Vertica database integrated directly on top of our data platform. So it's this hybrid solution where you have full SQL database directly within your Hadoop distribution. Um, so it had a couple sessions on that. We had, uh, a nice panel discussion with our friends from Cloudera and Hortonworks. So really good discussion with HP about just the ecosystem and how it's evolving. The other things we're doing with HP now is, you know, we've got reference architectures on their hardware lines. So, um, you know, people can deploy Mapbox on the hardware of HP, but then also we're talking with the, um, the autonomy group about enterprise search and looking at a similar type of integration where you could have the search integrated directly into your Hadoop distro. And we've got some joint accounts we're piloting that she goes, now, >>You guys are integrating with HP pretty significantly that deals is working well. Absolutely. What's the coolest thing that you've seen with an HP that you can share. How so I asked you in the big data landscape, everyone's Bucher, you know, hunkering down, working on their feature, but outside in the real world, big data, it's not on the top of mind of the CIO, 24 7. It's probably an item that they're dressing. What have you seen and what have you been most impressed with at HP here? >>Yeah. Say, you know, this is my first HP event like this. I think the strategy they have is really good. I think in certain areas like the cloud in particular with the helium, I think they made a lot of early investments there and place some bets. And I think that's going to pay off well for them. And that marries pretty nicely with our strategy as well in terms of, you know, we have on-premise deployments, but we're also an OEM if you will, within Amazon web services. So we have a lot of agility in the cloud if you will. And I think as those products and the partnerships with HP, evolvable, we'll be playing a lot more with them in the cloud as well. >>I see that asks you a question. I want you to share with the folks out there in your own words, what is it about map bar that they may or may not understand or might not know about? Um, a little humble brag out there and share some, share some, uh, insight of, into, into map bar for folks that don't know you guys as a company and for the folks that may have a misperception of what you guys do shit share with them, with what, what map map is all about. >>Yeah. I mean, for me, I was in this space with Aster data and kind of the whole Hadoop and MapReduce area since 2008 and pretty familiar with everybody in the space. I really looked at Matt bars, the best technology hands down, you look at the Forrester wave and they rank us as having the best technology today, as well as product roadmap. I think the misperception is people think, oh, it's proprietary and close. It's actually the opposite of that. We have an unbiased open-source approach where we'll ship in support in our distribution, in the entire Apache spark stack. We're not selective over which projects within Apache spark. We support. Um, I feel like SQL on Hadoop. We support Impala as well as hive and other SQL on to do technologies, including the ability to integrate HP Vertica directly in the system. And it's because of the openness of our platform. I'd say it's actually more open because of the standards we've integrated into the data platform to support a lot of third-party tools directly within it. So there is no locked in the storage formats are all the same. The code that runs on top of the distribution from the projects is exactly the same. So you can build a project in hive or some other system, and you can port it between any of the distributions. So there isn't a, lock-in >>The end of the day, what the customers want is they want ease of integration. They want reliability. That's right. And so what are you guys working on next? What's the big, uh, product marketing roadmap that you can share with us? >>Yeah, I think for us, because of the innovations we did in the data platform allows us to support not only more applications, but more types of operational systems. So integrating things like fraud detection and recommendation engines directly with the analytical systems to really speed up that, um, accuracy and, and, uh, in targeting and detecting risk and things like that. So I think now over time, you know, Hadoop has sort of been this batch analytic type of platform, but the ability to converge operations and analytics in one system is really going to be enabled by technology like Matt BARR. >>How many employees do you guys have now? Uh, >>I'm not sure what our CFO would. Let me say that before. You can say we're over 200 at this point >>As well. And over five, the customers which got the data, you guys do summit graduations, we covered your relationship with HP during our big data SV. That was exciting. Good to see John Schroeder, big, very impressive team. I'm impressed with map. I will always have been. You guys have Stephanie kept your knitting saved. Are you going to do, and again, leading the big data space, um, and again, not proprietary is a very key word and that's really cool. So thanks for coming on. Like you really appreciate Steve. We'll be right back. This is the cube live in Las Vegas, extracting the city from the noise with map bar here at the HP discover 2014. We'll be right back here for the short break.

>>Winston Edmundson here at Hadoop summit. We've got Steve woolens from Teradata. He's going to talk to me a little bit about a exciting new announcement that you had with Hortonworks today. Tell me a little bit about that. >>Yeah. So Teradata has been in the data management analytics space for over 30 years. And with the announcement today, we announced data portfolio for Hadoop, which is a collection of products, services, and customer support for an entire portfolio for the products. So we've got turnkey appliances, we've got commodity offerings and with Hortonworks, we've got a shared customer support model, so we can give our customers everything they need around >>Ultimate support. Pretty exciting. Now this seems like it must've been a long process to put all this together. >>Well, we've had a partnership with Hortonworks for about a year. We've had Hadoop product offerings in the market for about six months. We've seen a lot of uptake from our customers, and it's really about broadening that to make sure that customers can buy a dupe standalone integrated in with the rest of their data architecture and make it a trusted component within that next generation data architecture. >>Tell me what excites you right now with the customers that you're helping, you're meeting their needs. Where do you see things going? What trends are you following right now? >>The big thing we're seeing is customers. Our customers want to better serve their customers. And there's so many new interaction points that they have with those customers through social networks, email, and being able to take things like the call center voice records, but that's been data that hasn't really been explored in the past to figure out how to better serve those customers. So now with Hadoop and other MapReduce technologies, we can incorporate that analysis into how we better serve our customers, customers at the end of the day. If that makes sense, that's ultimately, it's about getting deeper insights into how to better service the customers. And I think with all the new data that's out there and the hype around big data, that's really what it's about. >>Do you find the customers are coming to you with their own ideas or are they looking to you for suggestions on just how they can bring these different data sets together and how they can maximize and leverage some of this data? >>Well, the problem is there's so much hysteria in this market. I mean, it's an exciting place to be, but there's a lot of technologies, right? So I think the thing with Teradata is we do provide that trusted advisor status. I mean, we've been implementing data analytics solutions for a long, long time and a lot of the problems aren't new, they're just incorporating new analytics techniques. So they have ideas in terms of things they've heard about. They're not really sure how to implement it sometimes. So part of our offering is we have services, so we can look across their entire data architecture and figure out where does the dupe really fit? What are the best use cases for it? How do we integrate that across the enterprise? So the end users and the applications that can benefit from that data can really get the value from it. >>How important do you think it is or how much is an advantage that you are tried and true. You've been here. I mean, some of these solution providers, you can call them fly by night. I mean, they just, they're just here on, you know, they've just formed. They don't have a track record. It's your track record of success? One of the main things that customers are attracted to? >>I think so. I mean, the reality is we have, we're like in the trenches with our customers, it's not just the technology, but when we have business consulting, people that come in with domain expertise from a given industry, so you can call it a track record or whatever it is, but it's really understanding, not just technology, but the business and how these things come together to really get the most value from all the cool technology that's out there. So yeah, a lot of the fly by nighters, I mean, there's a lot of innovative things that are happening. And at duke five years ago, it was one of those very new things. And so we've been looking at it for a while and now we figured out the best way to incorporate it into our solution portfolio and to roll it out to customers >>When you're helping a customer. And you're, you're looking at the here and now, this is what they, they need to be addressing. I would imagine a lot of customers want to know what's around the corner, what's around the bend that we should be aware of, that we should try to be, be prepared for. What do you, what do you tell them? >>Well, I think, you know, everybody will say there's just more and more data coming at you. I think other analytic techniques like graph analysis is something that people particularly with social networks are trying to figure out how are people interrelated to each other. So it's a lot of different use cases and there's different analytic techniques that can be combined in unique ways. So a lot of our R and D investment is going into how do we bring more of those analytic techniques and unify them for people in one system. So that regardless of your data scientists or business analysts, you can ask really interesting, tough questions that you couldn't answer ask before. So it's about giving answers to sometimes the unknown questions and helping them explore that data through unique ways. >>What would you say are some of the industries that are maybe there's probably more urgency for them to adopt some of these strategies or perhaps just, they're more likely to have a big return on investment? What industries would you point to? >>I mean, for us, it's a lot of the traditional industries where you have a lot of consumers, right? Telecommunications, retail, retail, financial services, anybody who's working with. A lot of customers that have a lot of products, just have a lot of complexity, a lot of customer interaction touchpoints. So I think those are the people that typically we see adopting new technology and really thinking about how to better serve their customers >>For folks that are watching tuning in. And they're pretty excited about what you might be able to help them with. What's the best way for them to get in touch with you or, or >>You just go to teradata.com and check us out there. That's probably the best way to reach us. >>Right. Fantastic. Thanks for your time. Winston Edmondson here with studio B signing out.