 Live from Seattle, Washington, it's theCUBE at Tableau Conference 2014, brought to you by headline sponsor, Tableau. Here are your hosts, John Furrier and Jeff Kelly. Okay, welcome back here, live in Seattle, this is the Tableau Conference, data 14. You want to join the conversation, go to crowdchat.net slash data 14, we're answering tweets there, LinkedIn users, Facebook users all sharing one thread, it's our new social innovation. Here, I'm John Furrier, the founder of Silicon Angel on my coast, Jeff Kelly, big data analyst and surprise guest, Lee Feinberg, president of DecisionViz, welcome to theCUBE. Thanks very much. So we bumped into each other last night and said, hey, we've got to get you on theCUBE. I really enjoyed our conversation last night around kind of our throwback to our glory days in the web. We were kind of reminiscing about what it was like in the web, 1.0 days, but really talking about how data is changing digital. I think we had a great customer, so I want to extend it out here. I'm a huge digital believer. When the web came out, I saw that, it was like obvious, people were nacing the web, I'm like, oh, the web is just a kid's toy, you know, no one's going to do anything on the web. The web, web 2.0. That kind of didn't pay enough for social networks, but now digital with mobile is a real deal, things are changing significantly, the iWatch yesterday, the iPhone 6, some really, really interesting new digital things happening. What's your take on that? Share with the group and the audience out there what you're working on. Yeah, I mean, it's really interesting, you mentioned the iWatch, and if you read what Apple is doing with that, it's really all about collecting information, all that personal information from individuals. And then the question becomes, how do they access it in a way that it becomes useful to them? And that'll be the biggest challenge of all of that, because now the technology is there to capture the information. And that's really never a big problem anymore. The data is available, and it's the communication of the data to ways that people can consume it and understand what it actually means to them and what they should do because of it. So having the data itself is good, but if you can't have some action driven from that, it's not really that helpful. And that's one of the big things that we work on with our clients, because today in all this data collection, and here, obviously, it's all about data, data, data. If you just have the information and you just make it into some charts and you put them together and hope that there's an insight, it's kind of backwards from how we view it. We focus on what it will you do with that? How will you drive decisions in your company? You know, the holy grail and advertising and web and commerce has always been actionable things, call to action, click on something, get into a landing page, get into act, get the data, buy something. And I think what you're talking about really is interesting because real time is a huge deal right now. And so that's a big trend. And the other trend I want to get your perspective on besides real time is Omni-Channel. It's a buzzword, basically means it's unlimited bi-directional channels of customers. So if we are living in an era of you can measure everything, which is really what we're living in, the first time in the history of the world, you can actually measure everything, right? So 50% of the ad spend shouldn't be wasted. Y'all saying half your ad is half your spend is wasted. You just don't know which half. But that shouldn't be the case anymore. What's your take on all this? I think if you from there's a couple of angles when you talk about marketing and advertising, right? There's a lot of automation that's going on. So people are building these exchanges and kind of using similar models that people do for buying stocks, right? So they're using that to figure out where my advertising should go. And that's very real time for some aspects of it. A lot of the other aspects are not real time. And it's really companies looking at the data, trying to actually understand what it means. Not from just placing ads and optimizing the pricing, but what does this mean in terms of people who are viewing the ads? Who are they? How do we understand their behavior better? And that's where people need to take the data that's coming in from all these different places and assimilate it into something that they can use to figure out maybe different types of marketing either into those channels and feed that back in even to these kinds of systems. Roy, you just almost, you started to answer my next question, which was how do you create that feedback loop so that you're connecting both the real time operational activities that you want to be optimized through analytics. But then you've kind of got to step back, big picture view, we're going to use something like Tableau and try to find some brand new insights. But how do you close that loop so that your big picture insights are impacting your operational everyday real time operations? Yeah, well there's a couple things. One, most companies aren't operating for those things in real time. There's some industries that are. Most of them are either daily or weekly type actions now. Hopefully that will improve over time, but the organizations just aren't set up to do that. So what you're asking is how do we get there? And I think something like a Tableau starts to instigate that kind of a question. Wait, now it's easier to get the data. It's easier for more people to have the data. And so now more people can make decisions. And what does that mean for us? Who should be making the decisions? Where do those decisions go? And the trick there is to track the decisions also. Not just to say, oh I see the data and I make a decision, but you want that information to come back to you and say, here's what we decided to do, here's what we did, here are the results. But a lot of people just make the decision and they haven't even created the ability to close the loop yet either. So there's a lot of redesigning of how organizations think about data that has to go on to enable that to happen. It's not just, it's not about technology really, it's probably more about the people and the culture and the process that they go through. You've got to change workflows in order to adapt to this new reality. And the cultural part is really interesting because if you're empowering people to find actionable insights, you've also got to empower them to take the action. So you're democratizing the way decisions are made across your organization. It's not just, okay, I have an idea, pass it up through the chain and then somebody higher up from you makes the decision. You've got to empower your frontline workers in some cases to make important decisions. And that's a big cultural change. It is one of the big areas we talk about with our clients and we have these workshops where we start helping them through these cultural ideas and recognizing that they have to address them is one that the idea of data democratization that's used a lot, we actually say that it's really more about decision democratization. It's like having data into the more people is going to let them make the decisions. And, but the trick with that is the organization's still kind of- They might not be ready for it. They're not ready for it. And they also still have this notion of we have to control the data. And then people say, well, it's our data. It's like, no, it's really the company's data. Which is another big thing. And that you have to get the data out. I mean, that's the, and the challenge is that the tools are cracking that open before it was really hard for regular people to access the data. And that's where Tableau really changes the game in enabling that where I don't have to be an SQL programmer or have any sophistication in that area. I can just be a regular business person or even someone in IT who might not have all that programming experience and get into these huge volumes or small volumes of data and start doing these kinds of things we're talking about. Let me talk about the challenge that you mentioned obviously the people and some of the processes that companies have. And we just had that young kid, young gun on who's basically like, hey, hoard your own data. Get your own data and manage it yourself. That's the mindset. So, what you're pointing out is how some companies just don't have that mindset. How early is it truly in this transformation? Because I think it's pretty clear that you got to shift your mind and have an open data modeling kind of culture. But where is it in the life cycle? How early is it? How would you peg that inning if you want to do an inning thing? And then, what are some of the challenges? I agree with you. I think it is really early on because it's the companies that, and remember, there's not even, if you could imagine, the volume of companies that are out there who don't have tools like this. So even those don't have a long way to go. But for the companies that are starting to make investments in being able to do the kinds of things we're talking about, they're just getting through the stage of putting the technology in, training people, how to use the technology. What they haven't gotten to is educating them on how to apply it to the company, which is very different. And so that's why I think it's still only, maybe inning one and two is the decision to make the change, to start buying this kind of software. Maybe inning two is where they put it in, they start to make the investment. And maybe they're kind of starting to get to innings three and four. So what would you talk to your friend if you were at a cocktail party or advising a potential customer of yours on this, hey Lee, I'm done. I got to just go this new direction. What do I do? What do you tell them? Yeah, the beginning is if you're going to go this direction, a lot of them ask what are the features and they have these long checklists. And I go through this with clients and I say the checklists are great because I know you have to go through that because that's your process. But in the end, it's a little bit of an arms race sometimes in terms of features and functions. You have a particular thing that you're really trying to do. Maybe the first step is to find the software that does that. But what you really need to look at is which fits the culture of your organization the best. Because if you're going to think that this software is going to help you, part of the transformation, a key part of the transformation, and it doesn't fit with how the company operates today, you can't change the entire company to fit the software. But you can try to pick the software that best fits the way the company does work and how you've set the company up that way. That's really the most important part that we talk to them about from a starting perspective. And then we have actually structured what we call the Blue Ocean for Visualization Framework, which is 11 competencies that you have to understand for your organization to succeed in the transformation. And so we kind of do an audit with that on their business to say, here's where you're strong, here's where you're weak, and then you can build a plan. I love the ocean term, much better than the lake. I'm not a big data lake person, I hate that term. All I do is rant about that, because it's more of an ocean, it's currents, it's different data, it's a huge data tsunami every company's having. So I got to ask you about the thing that we were, Jeff and I were kind of riffing on yesterday, which is, and kind of rolling our eyes a little bit, but the whole storytelling, you know, concepts. I love the concept, but it's very hype-ish right now. But we're saying, hey, storytelling's good, why not, storytelling's great. But most people don't even know what the story is yet. So what's your take on the evolution of, okay, the goal is to be a good storyteller, got visualization that plays right into that. But if you don't know what your story is, how can you tell the story you don't know? So the data prep, the mangling of the data, the wrangling of the data, all that stuff really is critical. Can you take us through your perspective of the storytelling outcome, but all the steps required to do that? Sure, obviously you need to go through the pieces of having data available. And what we try to help people understand is, and I think they've made comments about this during the week, is the idea that your data will ever be perfect is really not possible. So you want to start working with the data that you have. And that helps you start to understand what kind of stories you might be able to tell with it. The challenge with this notion that you said it's kind of hype, well, first of all, storytelling isn't a new idea, it's been around forever, right? But with respect to what we're doing, they say be a storyteller. But nobody explains to you, what does it really mean to tell a story? How do you structure that? Having a tool, so something like story points in Tableau starts to help you structure it, but the question is what do I put in there to actually tell it like a story? And so there's real skill in storytelling, right? I mean, authoring, writing, it's hard. It's a real skill you have to develop. So that has to be part of the transformation for the people. As we say, Tableau is we help people see and understand their data, and what DecisionViz is about is helping people become great communicators of data. So we want to help them move from just working with the data to really being able to communicate in the storytelling part is a key piece of that. We want to transition a little bit to the view of Tableau software, the company. We heard yesterday in the keynote from CEO Christian Chabot about the massive investment that aren't either going to do. The company's growing like crazy. We've talked about over the last couple of days on theCUBE, one of their challenges is going to be to maintain that customer focus as they scale. What's your take on the state of Tableau and where they sit in the larger enterprise software landscape and the enterprise business intelligence landscape? Sure, and I can give you some ideas from what I hear when I'm out talking with clients, and clients have huge investments in a lot of them in these other systems that have been around for a long time, but they start to see the transition that they need to make. And so where they, their challenge is to figure out where does Tableau fit and how do we, what do we keep in our current environment in the enterprise because we're not tearing down one of those systems, it would take a long time to take everything that's done in there, and if we were to port everything to Tableau, that would be a huge effort, so they're not doing that. So then the question becomes educating the organization on, we have this new application Tableau, we believe it's important to the company, but also helping people understand where it fits with what they're doing today. And that's a big challenge. There's no right or wrong answer. It really depends on the company and what they're trying to fix and what they're trying to solve as business problems, where that's going to work. I think that's the big thing, and Tableau needs, and people like us in Tableau need to help customers try to figure that out. Well, that's interesting because there's a similar conversation going on kind of a little bit further down the stack around new approaches like Hadoop and how that's impacting the enterprise data warehouse and where do we shift, and people aren't ripping out their charity installations, but they're saying, well, maybe we can shift some of these workloads to Hadoop, and maybe we want to do some of the new analytics and new applications that we're going to build on these newer systems, and it's a similar conversation. Sounds like it's kind of mirroring the conversation further up the stack when it comes to business intelligence. Yeah, I think they all start all being tied together because then they might say, well, if we have a new technology as our platform for data, that's a good time to transition, trying to access it in a different way as well. So sometimes companies are able to use that as a joint approach going forward. And how would you grade Tableau on a couple of really key areas that I was interested in coming into this week on their cloud strategy and their mobile strategy? We heard a little bit about both yesterday and the keynotes. How do you grade them? Do you think they're doing what they need to do in those areas? Yeah, as John was saying, kind of the 3.0, as things move more towards the cloud, I think what they're doing is you saw some good progressions and it's been happening over the last couple of years with Tableau, especially things like the web authoring. They've really increased the capabilities there and you're almost at the point where what you can do on the web mirrors what you can do on the desktop and that's really powerful to be able to do that. So that's, I think, and they've continued to make those investments there. In terms of the mobile, I really like what they did yesterday in terms of some of the things they're gonna enable on the iPad, some of the, made some of the user interface improvements which are great. The idea of snapshotting is huge for people. I have a lot of clients who have people out in the field so you can't rely on an internet connection so being able to take that with you and know it's gonna be there is huge. I think that has held a lot of people back from really pushing those kinds of mobile applications forward and I think the notion of the new app that they developed, the Elastic app, is interesting and really intriguing. Trying to figure out exactly where that fits now in the model of if I'm already using Tableau, when do I use something like that in my organization so it actually adds another question like what we're talking about now where does that piece fit in as well so that's something that we figured out over time. Lee, let's wrap it up and I'll give you the final word. Share with the folks what you're working on. Great to meet you last night. Great to get your insight. Industry Vet been around the block seeing these up and down cycles. What's your current thing going on now? What's getting you excited right now? What are you working on? Yeah, what I love about my company and the clients that we're working with is we're really helping with that transition so our goal is to really accelerate the adoption of Tableau in the company and we're seeing it transform how people start to talk to each other and how they work. I'll just give you the quick story so we did kind of an initial project with a big retailer for the executive suite and when we finished the work and presented it to them they were talking about it and they were amazed and they were starting to ask questions about what's going on here. As we all know, it was the same exact data they'd already been working with but because they didn't have it in a way that they could actually see it and just absorb it really rapidly it completely changed how they were talking to each other really in a matter of minutes and that's really what gets us excited about making those kinds of changes a company. And it's really, it's a positive change. I mean, it's a small little tweak and this little bit mindset shift but at the end of the day, it's huge changes, positive changes, health of the company, growth, easy to work with, pleasant to have a funner, more fun in your job. Lee, thanks for coming with you. Thank you for having me. This is so exciting. The stories are always the same, right? Someone's innovating, a lot of action going on and it's just the beginning of a transformation to this big data presentation layer where we want to call it the Tableau visualization. We're calling it an operating system. We see the dots connecting. This could be the next Microsoft. If they don't screw it up, that's what I was saying last night to the Tableau guys. They're in a good position right now. They're in a really good spot and they're enabling people to do great stuff and that's a good business model when you have people that you're helping grow their business and making things good. So, Lee Feinberg who's with DecisionViz here live in Seattle, theCUBE. We'll be right back after this short break.