Dave Bottom: Yeah, Jim, I lump it into two large categories. Actually, this is a hard question to answer because there are a number of challenges. The first challenge, I think that technology can help us with is what I call the large data to big data problem. From an NGA standpoint working with air born imagery and satellite imagery, we've been in the large data business for a long time, so large files that have specific properties. If you correlate that against big data, which is smaller files that Hedupe and Mercedes touched on that. How do we transition that? We're all carrying legacy... JIm Flyzik: Right. Dave Bottom: ... Architectures. How do we transition those capabilities into an open source world? How do we work the code re-write and make sure that we can minimize cost there to get that integration? That's the first set of challenges in that category. The second is really all about tradecraft. We're changing the way that we're analyzing information. Chris touched on it with a discussion about process was king, now data is king. How do we change our tradecraft around that, particularly in two categories? One is analysis, so how do we change our analytic processes and capabilities to accommodate big data? The second challenge is what I call conveying those data understanding to decision-makers. We've been in a static product. I mean, our favorite way is Power Point to convey information in the written word. JIm Flyzik: Absolutely. Dave Bottom: But how do you convey understanding in terms of big data that's really more activities and motion to convey an understanding more quickly?
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