Live from the Hilton at Bonnet Creek, Orlando, Florida, extracting the signal from the noise, it's theCUBE, covering Vision 2015. Brought to you by IBM. And now your hosts, Dave Vellante and Jeff Frick. Welcome back to IBM Vision, everybody. I'm Dave Vellante with Jeff Frick. So this has been two good days, day and a half for us, and don't forget, go check out ibmvisiongo.com and that's our digital experience site. You can check out all the videos from the keynotes and the main tent presentations, all the general sessions. You got to register to get those and then there's the CUBE interviews that we've been doing for a day and a half. That's all open. There's tons of content in the all access section. Go check out the social page. These digital experiences have been just a fantastic second screening experience for people that are at the event and people that are remote. It's really been fun working with those sites and participating with theCUBE and with other media types and particularly social media. So really this crowd, Jeff, hardcore CFO crowd, we heard a lot about predictive analytics, governance risk and compliance. IBM announced the deal with Deloitte yesterday. We had the execs on. My take is essentially what IBM has done is it's taken its collection of businesses like Cognos and Open Pages and Algorithmica and all those acquisitions that it made over the years starting really with Cognos and SPSS in 2007, 2008, 2009 respectively and it's now layering Watson analytics on top of that. To fulfill the promises of this business that vendors have been putting forth for decades a 360 degree view of the business, predictive capability, anticipatory business moves, aligning resources in your organization. All these things that the vendor community has talked about that as we talked with Doug Barton, got somewhat sidetracked after the Enron Debacle and Sarbanes-Oxley. People sort of had to go chase that transparency issue and deal with reporting and it was a boon for the business on the one hand but it sidetracked them on the other and I think frankly a lot of vendors are struggling with that. IBM has Watson analytics, it's bringing in Watson services from the Watson Group and building new products to overlay on top of this very established, very lucrative business. You often talk Dave about did first gen BI deliver the promise and a lot of people feel it felt short and then you have kind of the Hadoop movement jumped in and now we've gotten past as you said, having to make sure we're Sarbanes-Oxley compliant and we can now kind of shift the gears back towards the business and then you have the citizen developer, you now you have the citizen data scientist. So it does feel like it's a different world, it's BI gen two, I don't have been around long enough to know if this was gen three or two and a half but it does feel different and I also think that the way that they describe the interaction with Watson analytics is very kind of Google-esque and we often talk in the show about kind of before Google and after Google and the expectations of people's interaction with applications and how they should be able to act with them and this is really trying to be more of a Google-esque way. I ask questions of my data, I get questions back, I can explore, I can dig down. I don't have to be a hardcore data scientist and exposing that to a much broader group of people in the organization which allows you to go faster, innovate quicker and move faster so it feels like this is potentially something kind of very new and different. Yeah, you talked about AG after Google, people have an expectation of simplicity. We've been talking for a decade almost now about the consumerization of IT, Google, Amazon, Facebook, LinkedIn and that clearly has started to mainstream in the enterprise, IBM calls it CAMS, I call it SMAC, Social, Mobile, Analytics Cloud because Watson's like heroin. IBM's giving you a little taste, let you try it, they got a really interesting free-mean model of developing out APIs, I was talking to some of the folks in the exhibitor area, it's still immature but that's where they're headed. Give developers the power to tunnel into the Watson analytics platform, connect into other parts and IBM's sort of leading that charge with the analytics group. The more I think about what Ginny's done with the new organization, the more I like it. It's sort of taken the traditional hardware business and pulled in some flavors of middleware and Tivoli which have always been needed. It's always been a criticism of mine at IBM, they really stovepipe along hardware, software and services and now what they're doing is they're really, I think better mapping into what we call that digital fabric, that notion of you've got cloud, you've got a social layer, you've got an analytics data layer and companies like Uber and Airbnb are building digital businesses on top of that, well maybe you're not going to sell to Uber and Airbnb, maybe you are but the more important thing is there's a big global 2000 out there that wants to compete with those guys, respond to the threat, find new opportunities building on top of that ever more capable digital fabric and I think IBM is aligning themselves to that digital fabric so I think it's, I think the organization starts to make a lot of sense and particular the analytics group that is sort of under Pitchiana who we've had on theCUBE before, big business. I think it's approaching 20 billion, 17, 18 billion this year, it's pretty substantial. The other big news and some of the hallway chatter at lunch was talking about crowd sourcing and the intelligence of the crowd and really IBM in their relationship with Twitter and enabling unstructured outside the firewall data into the decision making process is a very significant change and it's a really different kind of attitude in the way that you make your decisions and the way that you place value on getting that crowdsource data and that seems to also be a move in the right direction Dave, that has to be part of it increasingly more and more the data exists outside your walls and it's really the combination and the unique way of using that publicly available data with your proprietary internal data to come up with a competitive advantage in sites that are going to help you move your business along. Well, we talk about the wisdom of the crowd all the time and John Furrier is very big on crowd sourcing. I mean, Wikibon was essentially founded on a Wikonomics like model. That was one of the books that inspired us and so when you think about it the crowd has always been pretty good at making picks.  One is my favorite horse racing example. In horse racing of even money shot will come in more than a two to one will come more than the three to one statistically. So the public tend to be very efficient handicappers. Now, unfortunately, favorites only come in about one third of the time. So maybe they're not that accurate but overall relative to an individual expert the crowd is going to be a better handicapper on balance. The other example I'll give you is one of the things we learned at 2MA in London talking to the guys at MIT. In the second machine age there's a story about a professor at Stanford, big data, teaching big data course and he decided to open that course up online and I think about 10,000 people took that course and he required that everybody who was in his class who had taken the course passed the test with flying colors, some very bright students obviously that they take the course as well. I think there were maybe, I don't know, several hundred students that he had take the course. Well, the interesting data point is that the number one kid from Stanford who took the course under this professor scored like 400th, you know the exact number, 343rd in that test. So 300 plus people ahead of him in the crowd. Okay, so the knowledge in the crowd is vast. The long tail is substantial. Combining that power of what IBM's calling, I guess the citizen data scientist, although they didn't really pound that term heavily, they really more talked about analytics for everyone. I like the citizen data scientist term, I think it's a powerful concept. That's a new era that we're entering now. The big question is can it live up to the promises of this industry that this industry has been making since the 1980s? It feels like we're finally there from a technology standpoint. The big question is are the organizations ready to adopt this new way? Right, and that's what we talked about a little bit about the trust. It's one thing if you're a data scientist and you have the knowledge and the education and the experience to have the trust and the algorithms that you built to deliver a predictive model, it's very different if you are not and you're trying this out and you dumped some data into Watson Analytics and it tells you what to do. Are you ready to take action on it? Do you understand it enough? But it sounds like that's where they're trying to go and at the end of the day, we talked to so many people, Dave, and the way to innovate is to enable more people to try to innovate, fail fast, have cheaper experiments and move the organization faster and spread that opportunity to innovate. So I think there's a real opportunity for folks to get huge value with just a couple of these things paying off. So we really didn't talk much about the horses on the track here, but let's maybe delve into that a bit.  Now granted, people may be critical of IBM, saying they're throwing the kitchen sink into the cloud, into analytics, and okay, that's fine, but they're counting it and they're counting it in a consistent way. IBM has built a powerhouse through acquisition and now bringing in the organic piece, which is Watson. That is a tremendous combination. IBM's one of these companies who can do very well with acquisitions and fund R&D and get R&D out into production, productivity. I put IBM right up there, Oracle's another good acquirer of companies, EMC is a very good acquirer of companies, Cisco's a very good acquirer, I think under Nadella, Microsoft has great potential as well, and SAP. So IBM, definitely a leader here, Oracle with the acquisition of Hyperion and others is obviously plays in the space, SAP, HANA, people driving that hard or SAP is driving that hard, those are kind of the big guys in this business, you got SaaS who remains a private company, obviously very competitive, you got companies like MicroStrategy, somewhat significantly smaller, but focused on their niche with a legacy and a long history and customer base, but IBM, the big difference that I see is three things. One is I was sort of asking, hooking Doug Barton a little bit about services, do I need to bring in a big army of consultants? Well, the flip side of that is IBM does have a big army of consultants and they know how to solve problems, they have deep industry expertise, interesting to know that IBM did a deal with Deloitte for the financial piece of it, and Deloitte's one of the gold standards there, but IBM's got that for the capability, that doesn't go away with the reorg, obviously. The second is Watson Analytics and Watson, generally, is I've become not only a shiny new toy, but a secret weapon, nobody really has that cognitive capability that we talk about as the future of in the second machine age, the second half of the chessboard, and I think the third is the pretty rich and vast portfolio, embarrassment of riches. The embarrassment of riches, we've heard that a number of times. We heard that a number of times, so very, very vast and deep portfolio, and the big question is, does it all tie together at the back end? I suspect not so much, you talk to customers and there's clearly certain frustrations around that, but that's what Bluemix is supposed to be all about, that's what bringing things to the cloud is all about, so these integrations are always challenging, rather have them in your portfolio than not. So Jeff, I'll give you the last word, your thoughts on IBM vision and what's next for theCUBE? Yeah, again, I thought it was interesting that we had a lot of people that joined IBM via acquisition and were so excited to have the vast richness now to play with, that I think that's a really good sign as opposed to people that they get acquired and they stay and they time out on their besting and then they're gone, so the fact that people are staying is a good sign. I had a great time, Dave, the first time I was here I thought it felt a lot broader than just the sales and finance and GRC crowd, and that's kind of the core and the foundation of the show, but it feels like what they're doing around the Watson analytics is a lot broader than that and that's exciting. So theCUBE, we've been busy, we've been on the road and we've gotten more to do, so we actually get a break, we got a team at OpenStack Vancouver right now, they're going for another couple of days and then we take a week off and then we're back to Vegas, Dave, we go to HP Discover, which is a big show, Nutanix Next back in Florida in a couple of weeks, Hadoop Summit's coming up, so we'll get a little bit of a lull in late July, I think, and then we'll be right into the fall season. Red Hat in the month.  Spark Summit. We also have an event in JockerCon. That's right, we're doing JockerCon, we have an event in July with MIT, the Chief Data Officer Conference, big emphasis on security this year and it'll take us through August, we've got a couple of shows in August as well, so the Vertica show and then back to VMworld and start the fall schedule. Oracle Open World, so we're busy. It's whirling, all right, Jeff. Keep watching everybody. Thanks very much, it was great to co-host with you. Thanks for coming to the East Coast. Thank you, yeah, change. We'll see you. Thanks to the crew, they're working hard over there. Yes, excellent job, Matthew. Matthew, Sam. Sam, way to go, Leonard, appreciate John, all your help back at the office, getting all these videos up. Chris and Nicole and our team. Brendan, switching back in Boston, thank you so much. Way to go, Dave Butler, opening the office this morning. And check out ibmvisiongo.com. Mark Hopkins and his team put that awesome site together, really phenomenal job of bringing together social data, video, blog posts, IBM content, other independent content that we brought to the table, content from the crowd, the power of crowd sourcing, so that's a wrap from here. I'm Dave Vellante, he's Jeff Frick. This is theCUBE. We're live from IBM Vision in Florida. We're out.