 It's theCUBE, here is your host, Jeff Crick. Hi, Jeff Frick here on the ground at the Clifft Hotel in downtown San Francisco. We're at the Dell 1510 discussion series. This is the second in a series that they're doing all over the country. They started with the first one back in Boston, talking about security. This one was about big data, and they brought together about 15 press and analysts, about 10 Dell executives, one customer from the healthcare industry to really have a discussion about what is big data, what does it really mean, hype cycle, et cetera, et cetera. So it was a good discussion, and we're excited to have a few of the folks here to get their deeper perspective here on theCUBE. So joined here by John Thompson, not the basketball coach from Georgetown, but thanks for stopping by, VP Research or GM Advanced Analytics. Yes. Welcome. Thank you, Jeff. Glad to be here. You started the conversation with a very provocative statement. We'll just jump right in. I think you said you wanted to know 100% of the information at 100% of the data, 100% of the time. That's what I said. That's the goal. That's really what I'd like to drive towards. I mean, we have companies all over the world, big and small, piling up data all over in their systems and in the cloud, and they're using it at a very, very low rate or a very small amount of data is being used, and I'd like to increase that. No, that's interesting. You actually have had a broad background. You've worked at companies that use data, like Nielsen Company. You've worked at kind of specialty big data companies like Kinesio. Now you're working at Dell, which obviously provides an entire platform of services and hardware and software, but you've got this interesting perspective because you've been really out on the front lines. What's taking so long? What's happening with big data that is still more hyped than reality? Well, the technology is an issue. It's difficult for the people who have the questions to get to the data and build analytics and then get the answers out of the system, so technology is one aspect. Another aspect is the integration of it. Data is proliferating everywhere. We mentioned the cloud a little bit and a lot of people stack things up on-premise and then their third party partners have it, so it's hard to integrate the data. I think the biggest challenge, though, is in empowering the analysts themselves to have all the tools they need to build either simple reports or visualizations or advanced analytics. We talked a little bit about the promise of BI, the 30-year promise of BI versus now we've got contemporary big data, if you will. It's replaced big BI as certainly the hot button topic and things like Hadoop. So again, with your perspective, what happened with BI? Is this really going to be that much different? Well, BI was very successful. If you were looking at backwards looking, descriptive analytics on structured data, it was a huge success. Now what we're looking at is opening up to the other 95% of the data that's out there. Will it be successful? Yeah, I think so. I think it's a matter of time. We're here at the conference talking about one, five, 10. I think we're probably looking at three and a half to five years before we see real leverage on this data. We're going to have to make some progress. Right, right. And of course the other thing is to get it out of the hands of the really smart scientist, of the data scientist and get it into the hands of the line business decision makers so they can actually get the data, analyze the data, get some insight and then do something about it. Absolutely. You couldn't have said it better. You know, it's really that the data is kind of locked up with the PhD modelers, data scientists, programmers. And we're really working hard and there's a lot of companies working hard on this problem to give the people, not just the PhD modelers, but like you said, the subject matter experts, the people who know about healthcare, people who know about logistics and different kinds of business areas, give them the right tools so they can build the analytics. Yeah. So what's next? What are you working on in the short term that's going to help move this train forward a little bit? Well, one of the things we're working on right now is actually giving analysts the ability to themselves go to any data source, any place in the world that they have access to, understand that data, do data discovery on it and then go out and either decide do I want to sample and use this as a part of my analytic or do I want to look at all of it. So, you know, we have some tools coming out pretty soon that are going to enable people to do that. So, it's exciting. You bite big chunks of the apple. I've never talked to somebody that uses all as many times as you all in every, I love it. Yeah. You know, it's a good ambition. That's the approach. That's the approach. Well, you know, you shoot for the stars, you end up at the moon, it's not always a bad thing or in your case, probably Mars or Jupiter. You should be way past the moon for sure. We'll give it a go. Well, John, thanks for stopping by. Thank you. Great event, thanks for having us. It's really insightful to get a group of people in the room and really just have a discussion outside the context of kind of our normal day-to-day life and I really appreciate it. It was fun. I enjoyed it. So, Jeff Frick here with John Thompson. We're on the ground at the Clifft Hotel at the Dell One 510 discussion series here on Big Data. I'm Jeff Frick and you're watching theCUBE.