 The Cube at Big Data SV 2014 is brought to you by headline sponsors, WAN Disco. We make Hadoop invincible and Actian, accelerating Big Data 2.0. Okay, welcome back everyone. This is Big Data SV. This is SiliconANGLE and Wikibon's The Cube, our flagship program where we go out to the events, extract the signal from the noise. I'm John Furrier, the founder of SiliconANGLE. Join my co-host, Dave Vellante, co-founder of Wikibon.org. And our next guest is Prakash Nanduri, the CEO and co-founder of Paxata, who launched live on The Cube at Big Data NYC just a few months ago. Welcome back to The Cube. Great to have you back. And we love when they launch on The Cube because we just amplify the hell out of it. We love it. It's like a newsroom. We call it the mobile newsroom. We like to cover all the action. We go where the action is, that's The Cube. So tell us, since New York, since Big Data NYC, what's happened? What's the news? Thanks, John. Thanks, Dave. You know, in the last 90 days since we met, it's been a phenomenal ride for us at Paxata. What I'm very excited about is the fantastic market adoption we have seen. We have seen adoption of the Pax, the Pax personal subscription licenses, the Pax shares, and our Pax Enterprise editions. We've had traction on all three. Two customers that are highlighted are the Dannon Company, the wonderful purveyors of great dairy products. And we started working with them early last year and in a work group type of license. And we're really thrilled that they have adopted Paxata on a much greater level to solve very critical data preparation challenges that they have for their enterprise analytics needs. In addition, we've also seen wonderful companies such as ZEP come in and purchase the Pax personal license. And you will see that in the case of ZEP, they're doing really interesting things such as spend analysis, and instead of spending hours in munging data and getting data prepared to do that analysis with Paxata, they're able to do it in minutes and not months. And that's what we're really thrilled about. So talk a little bit more about Paxata, what it is, how it works. When we first heard it on theCUBE, we said it sounds like magic. And now you're bringing real customer examples in. So I want to go there in a minute, but just refresh our memory and sort of what it is, how it works, that secret sauce behind Paxata. Absolutely. So Paxata is the industry's first adaptive data preparation solution that targets a business analyst. What does that mean? Any time you're doing an analytical exercise, the fact of the matter is anywhere between 40 to 60%, and in some cases, 80% of the exercise is centered around bringing data from multiple data sources, being able to clean that data, merge that data, shape that data so that it is ready for analysis. So before you can do any real analysis and get insight or make decisions, you have to prepare the data. Today, that is a very, very cumbersome task. It's generally, it takes, you know, in some cases months, in some cases weeks, and really destroys the weekends and the lives of our champions or PaxPros who are business analysts. What Paxata has done for these people is to take away all the hard tasks, the manual tasks of merging, cleaning, and shaping data, and using the power of our IntelliFusion platform, which allows a business analyst to really focus most of their time on analytics and uses the power of algorithms and distributed computing and the power of Hadoop to be able to bring all those data preparation capabilities in an automated fashion for the business analysts. That's what we're changing their lives by doing all the heavy lifting for them so that they can focus on analytics. So let's go into the Dan and example. Take us back to sort of when you first started, you had said it was a little work group license that was probably a POC in there early on. So take us back to the beginning. What was the problem that they were trying to solve and take us through where we are today? Yeah, I think it starts first with the great vision of Tim Weaver, the CIO of North America for Dan and I love when he says he has an organization where he calls it the business traditionally has number of analytical requirements and therefore uses a number of tools. In his words, he calls it BYOBI. Bring your own BI. Because marketing may need a specific analytical tool and sales may use a different analytical tool. And what they all have though as a business is a challenge of preparing data as I mentioned earlier. In the case of Dan and they are very much focused on making sure that their customers are able to have healthy lives by eating the right kind of dairy products, the great products that Dan and makes. They need to be very much on top of what products are being built, what products are being manufactured, how they're being distributed and which retail customer gets the product at the right time at the right place. So they do analysis and keep looking at data, looking at all the different pinch points in their value system. And they use a number of analytical tools. One of the primary tools they use actually is ClickView, which is their dashboarding and analytical tool. Well, different business groups need to be able to source data from different sources. Frankly, the data comes not only from internal systems and spreadsheets, but a lot of the data they're getting is from external sources. From their retail trading partners, from companies like Nielsen and other sources. They need to be able to merge, clean and match all of this data before they can analyze it in a tool like ClickView. That's what they started doing with Paxata, the data preparation piece, and what they have now done is to go and expand their usage across multiple groups and multiple use cases. So the data is relatively structured or not necessarily? The data that Paxata can handle, Paxata handles structured, semi-structured and unstructured data. That's the power of the IntelliFusion platform that we have. Okay, and in the case of Dan and it's pretty diverse. They use a lot of structured and semi-structured data. Okay, so talk about the unstructured piece, because that's the hard part. Well, I guess both hard parts is blending the different varieties of data, texture, if you will. What do you see people do with the unstructured piece? Talk about what your capabilities are there. Are you talking about text analytics, interpretation? What are they doing with it after they cleanse it or prepare it? So, what is interesting is, unlike in traditional world where all the analytics you had to do was based on the data you had in your proprietary systems which was mostly structured, is now in order to do an exercise like a customer targeting exercise, or to do a spend analysis exercise, you want to bring data from different sources. A lot of times you bring data from both structured and semi-structured, but also potentially from unstructured data sources, if you're doing demographics or if you're doing some kind of a social indicator of your product. You want to be able to merge data from an unstructured source with the proprietary and personal data sets which are structured or semi-structured. The difficult challenge is merging these to then make sense of it and make a decision out of it. That's the power that Paxata brings to the table. It allows you to take data such as unstructured data from social and combine it with structured data, whether that's your spreadsheets or whether that's your databases that you have internally, and then make a more complete decision in time and in an accurate manner. That's the real power of Paxata. I want to ask you if some of the trends you're seeing in the marketplace, what do you like in terms of the trends? What are some signals that you're seeing that make you excited about the current market, a big data? I think one of the most interesting things is there's a few, but one that I want to really stress about is that we're moving now from a time where a lot of the business analysts are very comfortable with using data visualization and analytical tools and data discovery tools such as FlickView and Tableau, et cetera. This is now the time where what it becomes is as these solutions permeate through the enterprise, it's really important to start focusing on important things like data preparation, governance, enrichment, quality. One of the trends is now going from data discovery to governed data discovery, which is really important. That's why I'm so thrilled about the advances we have made. Paxata, by being the industry's first adaptive data preparation platform, is solving real data preparation problems for real customers, whether they be large enterprises such as Dan and are wonderful companies like ZEP and whether they are at an enterprise grade or whether they are at a personal or a share grade. The other thing that is really important that's advanced, it's very important to see is the trend is for business analysts and the IT organization to be able to leverage solutions such as Paxata very easily. That's where being able to deliver this solution both in a multi-tenant public cloud environment and on private cloud deployments becomes very exciting. Well, I got to say, the adaptive data is something that Dave and I talk about and governed data discovery, that is really relevant because data discovery has kind of been loose, see the pan, that's good unstructured, it's natural, it's organic, it's an illusion. Now you're starting to see some discipline, some processes to it. At the same time, more data. So it's a nice flywheel. Absolutely, that's why when we came out with our vision of adaptive data preparation, we said from the beginning that this is about having a comprehensive end-to-end platform and that involve five major capabilities. It's around being able to enable the business analyst to integrate multiple data sources, to enrich that data on the fly and in the context of the analysis she or he is conducting, to clean both semantically and syntactically to be able to share the data sets in real time amongst their peers and with IT. And last but not least is to be able to have a governance setup for data which doesn't prevent usage but also enables and empowers the users. So Prakash, I got to ask you my last question. I know you've tried on time and you got a hard stop. So we just had Andre on and he said, look there's this new role emerging because of this whole big data meme, the chief data officer and it's a parallel role to the CIO, I mean given that you guys are all about the data and preparing the data, you're just center of the data universe, are you seeing that sort of same role emerge and do you see that role reporting to the CIO or do you see it separate? It will vary depending on the organization and depending on the structure and the expertise of the people involved frankly. But I think what is really important is now is the time when data preparation is real and that's why we're so excited that in addition to the fantastic customer traction we've received, we're also announcing advances to the IntelliFusion platform and we're throwing open a challenge. We're throwing open a challenge for the PAX formation challenge as we call it and we're inviting any business analyst anywhere to go up to our website, sign up and if you give us three raw data sources we will give you an answer set in a very short amount of time, in hours. And because we are saying that now data preparation is real and it's ready for usage and it's ready for mass consumption. We're ready to go. That's what is the transformation we're pushing. Parkash, thank you so much for coming on. Great to hear from you. We're excited by your success. Obviously, launching on theCUBE was, we love it. And we're going to be watching you all the way, rooting for you. You're a tech athlete and you're in a hot space and we love your thesis and everything about your company. Thank you so much. It's delightful to come back here. Thank you so much. This is theCUBE. We'll be right back with our next guest. Talking about big data, munching on the big data, analyzing commentary, rumors, opinion, facts, all here on theCUBE. Extracting this here from the noise live in Silicon Valley, I'm John Furrier. We'll be right back.