 Okay, we're back here live inside the Cube at IBM's Information on Demand in Las Vegas. This is SiliconANGLE, the Cube, our flagship program. We're out to the events. Check to see if they're from the noise. Let's get right back into the action. I'm John Furrier with my co-host. I'm Dave Vellante at wikibond.org and we're here with Stacey Leidwinger who is a senior director of product management at Vivissimo, which is a company that IBM bought recently. A lot of people are excited about this acquisition, Stacey. So welcome to the Cube. Yeah, thank you. It's great to be here. Yeah, so when was the acquisition? When did it go down? So it was closed beginning of June this year. So have you been blue-washed? So actually we're getting ready to launch our first blue-washed product. We'll be announcing tomorrow. Oh, Jonas says the antibodies. Yeah. He's the guy who ran a Skunkworks project called G2 for like four years. So, you know, he's a little bit shy from the, you know, the machinery. Doesn't play with the heavy machinery at IBM. So what's been like there? It's been really positive and good. So I think we're excited because we've come under the big data portfolio. And so, really, yeah, right? And so it's been great working with the teams, getting the product ready to go ahead and launch, working with all the different sales mechanisms. As a product manager, the wealth of technology, we can now integrate with our product. It's like Christmas. So it's all about prioritization and focus. And the market's growing like crazy. There's a lot of demand for solutions. Yeah. Man, it's exciting. So give us a quick, yeah, I know you got a deadline, so we'll try your writers. Give us a quick overview of what's going on with the product with you guys inside IBM. Yep. So our product is going to be announced as Data Explorer. And it's really one of the entry points for clients who are looking to understand and navigate and explore all of their big data assets. Whether it is stored in a system like Big Insights where you're going ahead in a Hadoop infrastructure, or you want to go ahead and bring in more enterprise content coming from content management, ERP, CRM, external information like social media, web, Wikis, et cetera. And so we really allow organizations to explore and navigate all that information to use at point of impact. So talking about applications, it's really big data applications that customer service agents can use. Marketing executives can use. Sales executives within R&D. So I was always talking to my friends in the big data world. We need a search engine for data. Data sets, not so much data per se. Is that something that you guys are looking at? Yeah, so fundamentally we've come from a search background. So what we're doing is we're able to go ahead and index all of these rich assets to allow users to navigate through it. We also have a user interface that pushes content out, providing a 360 degree view of information. So customers, products, again, all of your information sits where it resides. We're not asking you to move or change your data. We build that rich index and then we allow for exploration. Does that include real time information, anything that's streaming in? You indexing that too? Yeah, so that's where we're integrating with InfoSphere Stream. So we can actually show how real live data is being streamed in within our interface. And then you can push that information so you can index it later on. So you're not sucking it into a God box? Is that right? No, it's all in our index. Okay, so it lives where it lives. Stays, yep. It's distributed by its very nature. You talked to it off camera about federated discovery of data, right? So talk about why that's important. So I think one of the biggest challenges organizations face is how do I get started with big data? I don't even know what I have. I don't know what I don't know. I don't even know necessarily what information's valuable for my users. And so we're that initial step to start allowing users to navigate and just find what information do they have about a topic? What information is used heavily by their users? Once you start to identify those characteristics sets, now you can start to decide, all right, this information is valuable. I should probably put it in a system like Hadoop or Big Insights to run analytics. This information actually would be better off in a different archival system. It's not heavily used. I need to keep it for governance reasons, but I could find cheaper systems to store it in. And so we're really that entry point to start exploring and understanding what information you have. So is there a classification capability as well, or is that sort of a different technology? No, so we actually, we can leverage anything that exists, any type of metadata or structured information. But we also have what we call our clustering engine which dynamically categorizes themes without any pre-processing with your unstructured information. So that's where some of this exploration comes. So people can actually find things they otherwise would have missed. So obviously unstructured data is a big theme here. How do you guys deal with all the unstructured data? That's really our sweet spot. Because there as we start to build these indexes, we can start to find related terms and themes as I've pointed out. We can also allow users to hunt for that information. We can combine structured and unstructured so we can go into your CRM system and understand here's our list of customers. Now in all of your unstructured information, your file shares, your content management, your email, find everything that relates to that customer name. And so that's where we see this merge of structured, semi-structured and unstructured content. So share with the folks out there. I mean, I don't want to get too, you know, you give away too much of each side of it, but explain to them how hard that really is to do. So I think that's what everyone says. That's not, you know, it doesn't sound hard, but when you think about enterprise applications, it's very complex. You've got to think about security. So how can I ensure that only the right information is being delivered to the user, that they're not seeing anything that's unsecure? You've also got to consider about updates. So as content changes, how can I ensure that it's updated almost instantaneous? We live in a world of instant gratification. People want to know that if they change a document and SharePoint file in that, they're going to immediately see that change when they hunt for it. And people test that all the time. Also the nuances, when you think about all the fields and metadata that might be associated with a piece of content, you need to ensure you're accessing all of that. So when I talk about connectivity, I always talk about ensuring you get all the content in a secure fashion, and you support real-time updates. And that becomes quite complex when you think about systems that have been out there for a number of years. You're a competitor, Oracle. Yep. They bought in Deca. It was in Deca, they bought, it was in Deca. Yeah, and they're inventing big data, as we heard from Larry Ellison. They're just a note on the grid we heard earlier. And they say they do a lot of things, really weren't built for what's going on in the workload side of things. How do you look at Oracle relative to what IBM's doing? So I mean, I think I'll look at it first, kind of where you pointed out, like in Deca and in Search. I think where Oracle invested was more around product cataloging, e-commerce. That's really where in Deca's strength has been over the year. They have a number of retailer sites that they would allow to go ahead and search against the product catalogs. Probably less of the sweet spot was the unstructured wealth of information that's coming in, the content management, the ERP, PLM, all that I mentioned before. And so I think the way that we're attacking big data is really how do you bring big data to the masses? How do you ensure that the business user is getting real tangible benefits? And I think that's how we start to differentiate. Also having this UI, which I could show our screen now, because I think really that 360 degree view of how the information's being pushed together, we're not seeing that from a product perspective with any of the competition to date. We're seeing organizations try to build it, but we all know what happens when you try to build something. How do you sustain it? How do you maintain it? And that integration point becomes the challenge over time. So talk about what you mean by that 360 degree view, because a lot of firms in the BI business used to say that. And I want to probe a little bit and tell us what you mean by that. So I'll use a scenario. If I'm a marketing executive and I'm looking to do a marketing campaign on one of our new product lines, how do I go ahead and today, without using Data Explorer, how do I find my information? Well, I probably go into my content management. What's the latest marketing data sheets that I've had on this? What has been the recent case studies that we've done? What's the recent stats around it? Then I probably go into our CRM system. Who's actually bought the product? Who can we use as customer references? I might go in our PLM system. I might check our data warehouses around inventory. I might go out and look at the social media. So I'm going to all these different silos to understand just how my product operates, the health of my product, the business of my product. Now, in a single interface, we can bring all of that data together. So you're seeing information from CRM, PLM, our marketing automation tools. And that's what we're talking about 360. Where I think 360 has gone in different areas, like MDM, for example, is they find that 360-degree view of an identity. So they know that Stacey Lydwinger in the CRM is S. Lydwinger in email, is S. Lydwinger on the intranet. So we can actually leverage all of that work and now pull in all the unstructured in the context of all of that information. Similar to BI, I think BI has done a lot of work around quantitative analysis. So looking at a lot of transactional information. We can pull that information in. We work together. But we then go after the qualitative and the unstructured. And that's really where the magic of our solution is, is being able to find that golden nugget maybe in an email or a sales briefing notes that otherwise is overlooked. You got to know what a gold nugget looks for before you can actually find a gold nugget, as we always say. That's great stuff. My question, I know you got your tight on time, but I want to dig into the go-to market for you guys, obviously. So talk about how you're getting the word out. What are you guys doing as you go take us to market with market development? Is it selling through IBM channels? What kind of marketing do you do? What's some of the playbook there? So, I mean, we're really all just ramping up, I'd say, leveraging the IBM machine to get our name out there. But I'd say where we look at kind of the playbook, really in three areas, all around big data. The first is really how do you navigate and explore your big data assets? I'd say that looks a little more traditional like a federated discovery or search solution where you see a list of results that you can drill into. The second area then is this 360 degree view. So much more of a dashboard like view, pushing information out to the user. And then the third area is taking that 360 and extending it with analytics. So really starting to merge the quantitative analysis that might come out of a big insights, a Cognos and SPSS with the qualitative of the unstructured. So based on those three areas, we're going ahead in training a lot of the IBM sales team. We're going with our channel partners. We're getting people ramped up to go ahead and deploy in the field. I think every week I'm doing probably five to 10 different enablements in training sessions. That's the plus word for IBM. Is there any marketing behind it? Like yeah, so you can, you know, I mean print advertising, web advertising. So what you're going to see come out is all around data explorer. And I think we're spending a lot of time talking about the big data platform because we really want customers to understand how all these products come together. They're not really just piece mail. There's a plan and how they can get started. We have our big product announcement that's going to be coming out this quarter. So you're going to see a lot of marketing. Yep, this year you're going to see a lot of marketing information come out around that announcement. And we're coinciding that announcement with Streams 3.0, Big Insights 2.0. Now a big data group. We're interviewing Rob Thomas. He's coming to see you. Is he your group? He really leads our group. He's, you know, our champion. He's the head top dog. Yep. So we brought Vavisimo in during the acquisition phases. Yep, he's in the NMA. Grilled me with lots and lots of questions. Who does the marketing for the group? Tracy Moustachio? So she runs Big Data Marketing. So she does Big Insights, Streams, and Data Explorer. Yeah, we like your Big Data. You know, I used to be friends with Anad Jhingran until he turned and left the company. I had not, he's been at IBM for years. He went to a startup, but yeah, we've talked about structured data for a long time. You guys have done a lot of work in the area. Final question before you go is what's really exciting you the most about two things. One, the IBM acquisition. And I know you can say, oh, it's great all the effort. But two, product wise in the marketplace, what's really getting you excited? Well, I think those two go hand in hand. So I had been at Vavisimo for eight and a half years. So the fact that IBM saw the business value that we were bringing to our clients and said, I think we can do a lot more. We can take this product that's been your baby and show it to a broader audience. So to me, that's the most exciting. The fact that tomorrow I'll be talking at the IM keynote showing the demo of our product to maybe two, 3,000 people. It might have taken me a whole year to demo to 3,000 people. And I did a lot of talking, but there wasn't that many. Well, you're just talking about 2,000 people. Yeah, there you go. Right? You can reach that right here. Several help. We should have got the demo going. So from the product perspective, I think that's it. And I think that what we bring is we've really focused on what are the business problems that our customers are looking to solve. And I think I'm seeing this evolution where probably the last year or two years there's been a lot of lack of a better term of science projects around big data. We're hearing at the conference where there are now a handful of 50 different organizations or more that have really taken these products and started to expand and use. And so I think that's going to evolve over the next year. And the fact that we get to be a piece of that, I think is exciting. Okay, Stacey Ledwinger. Thank you for coming on. I know you're busy. Senior Director of Product Management at Vivismo. Now an IBM company and M&A into the big data group. You've got a good car you pulled off the deck there. Getting in the right group. Big data's big, it's hot, we love it. This is theCUBE. We'll be right back with our next interview after this short break.