 Live from Seattle, Washington, it's The Cube at Tableau Conference 2014. Brought to you by headline sponsor, Tableau. Here are your hosts, John Furrier and Jeff Kelly. Okay, welcome back everyone. We are live in Seattle for Tableau's data 14 conference. This is The Cube, our flagship program. We go out to the advanced, extract the signal of noise. I'm John Furrier, joining my cohost, Jeff Kelly, big data analyst at wikibon.org. And our next guest is Francois, agent stat. Welcome to The Cube, director of product, senior director of product management at Tableau Software. Welcome to The Cube. Thank you, it's great to be here. So I'm excited to talk to you because product is an exciting part of Tableau. One, you're under a lot of pressure. It's fun pressure, because the culture is pretty solid as we find out every time we talk to someone. But the product has been successful. So there's a lot of pressure to have more gusto. Especially some of these more automated products like Elastic. And just in general, visualization is on top of mind. You guys have achieved amazing success with the product. Product market fit, as they say, in Silicon Valley. Your customers are voting with their wallet. You got traction, growing like crazy, changing the landscape. How do you do it? What's the secret? Come on, tell us. Well, if I could share the secret, then everybody would build great products like that. I mean, the first thing is that we are a product company, and we're a mission driven company. You know, our mission is to help people see and understand their data. I mean, that's what really drives us. And when we think about the features that we put in the product, we really think about how does it help that mission move forward? And looking at that mission, we build the features to enable everyone to work with data, to help them see that data. And that's really the visualizations that you see in Tableau. But it's also the deep analytics. It's about understanding that data and answering your own questions. But the software is for everyone. I think part of our success is that we're designing software for people. People that have questions of data that can actually use it. So talk about the product group now. So obviously, that's great messaging from Tableau. Love it. Check the box on that one. Let's move to the product. How are you guys organized? And obviously I can imagine the meetings, just like the passion and the energy, wrestling over feature war, PRDs, MRDs all happening. But how do you guys organize it out? Obviously analytic, and a lot of moving parts in terms of tech. You mentioned analytics. Is there a platform group? How do you guys structurally organize your product teams? Well, so, I mean, aside from the typical product development efforts where you have developers and testers, program management, documentation, really what we're investing in is around six core areas and really the teams are building features around those six. So it starts with seamless access to data, being able to connect to any data that you have. Second, it's about statistics and analytics for everyone. Anybody that has a question should be able to ask it. Third, it's about visual analytics everywhere, answering questions on mobile, in the cloud, anywhere you have. Fourth, it's about storytelling so that you can communicate your stories with data. Fifth, it's about the enterprise and how do you scale analytics across the entire enterprise. And the last thing, which is actually really, really important is that we have to design software that's fast, easy, and beautiful, that people love to use. And so the whole team's really rallying around these six big areas. So are they functionally separate or are they all kind of like intermingled and more of a... It's all intermingled together. Every team is working together. Okay, got it. And so if we're working on a really exciting feature like Project Elastic, there's client people and mobile people and server people and data people that are all coming together to enable Elastic to come together. So which products do you work on? So I run product management, so I own all the products. Okay, so we had analysts on earlier from TBR's name, just Stuart Williams, okay? Who said, I said, would you like this? What did you like the most about the show? He said, I love Elastic. I mean, I said, what's awkward about the show? What are they missing? I want to see Elastic talk to everything and then grow with gusto. Okay, so that's the pressure. What's the status of Elastic? And it was a very negative article in GigaOm about Elastic being not ready, not sure. Give us an update. Where were you at? The product was shipping, I talked to Dave earlier. I questioned him directly, was that a demo version on the stage? No, that's code that was running on the system, no problem. So it's legit. Where is it in the roadmap? How are we doing? So I mean, right now what we show today is a full running code of Elastic, but it's not ready yet to be delivered. We still have a lot of work to do but we want to give people a sense of what the capabilities are going to be there. We have to work on connecting to data, making the experience great, enabling you to save and share more easily. So you understand the feedback, pretty much. Absolutely. It's all documented, already built out. And again, when we're going to deliver this out there, there is no app at all on an iPad or on an Android device that does this. And so we're going to deliver something out there, we're going to listen to feedback, we're going to improve, but it's so exciting to be able to just touch your data. It's a whole new possibility to work on data model. So what's the GA of that going to look like? Is there a date even thrown at the dartboard yet? Or is it still, let's keep it iterative, it's on direct availability. How are you guys going to deal with this? Is it? No dates yet, it's going to be next year, 2015. And we'll ship it when it's ready. We'll have a beta program. We're inviting our customers are ready to be part of the beta program and give us feedback. So you have a process for all that? Absolutely. And we do that for all of our products. Any product before we release it, we go through these extensive alpha and beta cycles to let our customers tell us, is the product ready? Does it work? Does it answer the questions that you have? And once it is at a high level of quality, then we get it out there. So you mentioned a moment ago how you're designing software for everybody. So that obviously, that's a big challenge because different users have different levels of expertise. You know, when we go to shows in the new world, you see the data science community. They love Tableau, all the kind of data visualization competitions most of them are done in Tableau. But you're talking about things like Elastic, we're talking about the common user who doesn't have any of those skills, doesn't know what data science is, and everything in between. From a product management standpoint, how do you build a product that can meet the requirements of such a wide user base? It's hard. I mean, it is hard to deliver software for everyone while still appeasing the high end, the people that want to go really deep in the data and the people that are maybe more casual. That's always that big struggle that we have. And part of the design approach that we want is that we actually want to keep people in the flow of analysis. We want to keep them thinking with their data rather than struggling with the software. So a good example in one of our previous releases, we added forecasting capabilities. Now forecasting is really hard for our statistical knowledge, lots of algorithms, tons of different algorithms. And rather than just giving the users an algorithm picker and say, choose what you want, most people don't even know what they mean. We said, well, why don't we just automatically inspect the data and then based on what we find, choose the right model that fits the data. Now, is it the perfect one? Could an expert change it? Absolutely. But we wanted the defaults to be as good as possible so you can stay in that flow. And that's really that approach is try to make all the defaults the right ones or as good as you can make them and then give people the options to go and go further so that they can really answer their own questions in their own ways. So, and another kind of related question, I mean, Tableau is very well known for being very customer focused. You listen to feedback from the customers, you add new features based on customer feedback. But of course you're growing extremely fast. I think 2,200 new customers last quarter, I think was the number. When you're growing at that kind of pace from a product management point of view, how do you, you must be getting lots of requests for different types of features. How do you make those decisions about, hey, this is something we need to focus on because our users are interested in it and how does that become more of a challenge as you scale so quickly? I mean, it's definitely, it's hard. That growth is unprecedented in the marketplace. You know, some companies have this tendency as they get bigger and they chase bigger deals to only focus on maybe the big customers. And then that becomes not a necessary tool that everybody wants. And I think it's important to have a balance of all those. In product management, there's this great story that's been shared that when you think about a release, what we put in a release, there's big, think of it as a bucket. You got this bucket and you're gonna put some tennis balls in that bucket, right? Those are the big features you add in. Now, is the bucket full once you fill it up with tennis balls? No, I can go and fill it up with pebbles. Those are the smaller features. And so now, once we've filled up the bucket with pebbles. And then there's the QA features, which is the same. It's a lot of concrete, which locks it in. You can put water or sand in, and that's like even the smaller features. So it's, every release has a balance of all those. Addressing the needs of the enterprise, addressing the needs of the user, thinking about new markets that we can go and address and new capabilities. Storytelling is a perfect example of something that no customer really said, I need storytelling. But we saw this pattern emerge that we can innovate here. And it's this combination of these three things. It's very Steve Jobs-like, actually. Absolutely. You know, see the future before the customers, build it before they see them. No one said, I wanted an iPhone. Yeah, and you look at the iPhone. There were smartphones before the iPhone. And what they came up with is a value proposition that was so much greater, that was delightful. And we want to do the same thing, but with data. It was said that if Steve Jobs listened to analysts, he would have built a better blackberry. And, but that's kind of to what you guys are doing. You're doing something completely new and vicious with the pressures on. So there's a lot of pressure for you to manage the product teams to one, think differently like an Apple mindset. But you're changing the game on the user experience. So you have to actually do that, do that product thinking. Does that, how do you guys do that in a tough market to get talent? Are you bringing in diverse resources? How do you as a manager manage that? Is it a new hiring algorithm? Can you share any insight? Or you do a take a Steve Jobs approach, you know. Is there a John Ivy in Tableau? Or is that you? There are. It's clearly not me. They're better looking people too. Can I have your autograph? But the part I think is actually interesting is the people that we hire, they're not necessarily BI people. We're hiring video game designers. We're hiring graphic artists. We have psychologists on staff that understand how people interpret colors and maps and what's the right way of bringing that talent together. And it's about bringing people together and understanding what's going on. But the thing that we always say is when somebody wants a feature, we don't just say, okay, let's give you that feature. We ask, well, what are you trying to cheat? Because there might be better ways of solving that problem in a way that they haven't articulated. But we can see that pattern and, you know, part of my job is to pattern match across the customer's feedback. So I got to ask you on that point. In some successful companies, in successful companies, you have products dominate the discussion and feature creep becomes a huge issue. How do you guys deal with trying not to get caught of that feature creep, which essentially means you start working on those little pebbles and you forget about the tennis balls? So how do you manage that? And is there a process for, is it more of just kind of like instincts? I mean, we have an agile development methodology. So we have different teams working in parallel on different features. But the way that we've organized our philosophy is around something that we internally call QSF. It's quality first, schedule second, and features third. So the most important thing is that we deliver a high quality software, a piece of software, with great features. And then the schedule comes last. So instead of trying to jam everything into release, we just try to figure out when do we have the best possible features? So quality first, schedule second, or features? So QSF? QSF. SF, so schedule second. Schedule second. So you work on the quality, that paces the schedule. Correct. And then eventually you have features. And if it doesn't fit at the level of quality that we want, then it doesn't ship. Usually it's features, schedule, quality. That's right. And it's really interesting because product people like me always want the most number of features at the fastest schedule with some quality. And if you talk to customers, they want the opposite. They want high quality software, right? On a predictable schedule. And then they'll live with the features that they have. All right, so how do you handle the following situation? I'm a customer. I'm a big top tier one customers. I want this feature. I mean, obviously you don't say no. Oh yeah, we'll look at that in the road. We'll put that on the roadmap. That's kind of the standard answer. But I mean, how does a feature get adopted into the life cycle of the roadmap? Is it a, does Christian have the veto power? Is it used or the consensus? I mean, just share the internal dialogue on how that works. I mean, I think it ends up being a conversation. But we get requests from our ideas forum. We get requests from the industry. We get requests directly from customers. We get requests in the community. It comes from everywhere. And ultimately it's a balance. Now for a customer like yourself, let's say you had some features that you wanted. You know, the important thing is that I understand what you want and that we have a dialogue. I can tell you, we're never going to do this feature. And this is why. But if it hits your pattern match the broad market, then you say, okay, it's on my radar. Correct. And I can say, yes, it's in or it's not. And actually that transparency, something our customers love and they appreciate because then they can plan accordingly. It's not just, oh yeah, it's going to be there and it never shows up. I'll clearly say, yes, we're doing this maybe not immediately in the near term, but maybe it's long term. And these ones, no, those aren't the things that we want to do. We're not planning to build video games at Tableau, right? Here's our focus. Yeah, but video game environment is a first person. It's a lot of collaboration virtual space that that's a user base that will be growing up. It's very user friendly. I mean, gaming is the, I tell my son, that's the future work environment. Headsets, multiplayer, first person shooter, shooting down those projects. No, but I mean, seriously, that's a user and experience issue, right? Thinking about those different situations. Yeah, absolutely. It's about thinking of what's the right thing to do that aligns to our mission, makes our customers successful, and really adds value to the overall experience. So earlier today, we had George Matthew from AlterExxon. He was talking about- Love George. Really smart guy, and he was, I think he had on somebody talking about leveraging the community of users to help innovate the product. Specifically, I was asking about some of the vertically focused capabilities of AlterExxon. He says, well, a lot of that comes from users who will customize AlterExxon with Tableau to fit you, certain use cases. But just kind of riff on that question a little bit from a product management perspective, how do things like maybe Tableau Public, or actually not just user requests we want this feature or that feature, but actually seeing what your customers are doing with the product, how does that influence product management and where you take the product? It influences a lot. I mean, first off, when you look at Tableau Public, 300 million people have consumed visualizations for public. That's probably like the most, the biggest BI system in the world. So we get to understand how people use it, what kinds of features are being used, what the performance characteristics of the software are. When we release a feature, we actually do BI on our own systems, and we can see, wow, this feature is getting some adoption, or this one's flat. What's going on? Which browsers are being used? All that just comes right straight into the product. Another good example is Tableau Online, which is the cloud-hosted version of Tableau Server. Again, we get some phenomenal analytics of using a BI system at scale. What data sources are important? Are they refreshing? When are their errors? What kinds of things are people doing? How hard is it for them to accomplish their task? And then we use that to improve the software. That's a great point. I mean, the idea of using analytics in product development, is one of the initial big data use cases. We saw a lot with the gaming companies, John, watching what are our players doing in the game? Where are they getting stuck? Where are there areas where we need to improve? And it sounds like that's something that new innovations, and I think you mentioned the online version of Tableau gives you that capability. Now they're phoning home. You've got all that data. You can actually start using that to build the product. And we actually use Tableau to build Tableau. So when our developers are building the software, we're actually using Tableau to visualize what's going on, code quality, performance. Anytime a developer checks in a fix that causes a problem, we know instantly, we have visualizations. We can see how many bugs are assigned to people. So we love to pontificate about trends, but also we like to analyze and try to connect the dots and get inside your head. So I got to get inside your head for a minute and ask you, is there an operating system group within Tableau? I mean, is there a secret department working on the operating system for the cloud? Because you guys are essentially overlaying on existing systems for born in the cloud, and it's a direct threat to Microsoft and these other companies who have these big fat bloated models of software where visualization is an abstraction layer. It's like a game engine, but you accept the game engines don't exist yet. You are the game engine. So to the gaming point, there was no market for game engines. Someone built a game engine because they had to build a game. In the old days of writing code, you wrote your own stuff. And then they sold that game engine. So if that plays out for you guys, your engine is gonna, Ken proliferate, you are the standard. So that's an operating system. So I don't think of it in those terms. I think of them in the terms. So is there a special group though yet? So we have a core engine group. That's the group that works on VizQL. Core engine, okay, good. But I look at VizQL as the heart of Tableau, right? It's what connects the data and the visualizations together. All that freedom that you have is VizQL. It's really, really that, that heart of the product. And so for me, I think about it as how do you connect the data, the visualization and the analytics together to help people answer more kinds of questions in more mediums in more ways. So it's not an operating system. I'm not gonna manage files that way, but if it's data related, then I should be able to fluidly work with any of that data regardless of where it is and the cloud on premise and Hadoop and a flat file, whatever. And I should be able to visualize it any way that I want and answer any question that I want. That's my operating system. That's VizQL. It's actually a new, it's a new take on a modern approach which is essentially by decoupling the data which still makes the core. You now have other subsystems. Now call it an operating environment where you want to call it, but if you're sitting on existing systems, you're in an abstraction layer. I mean, a perfect story that I love is think of the business world in the 60s and 70s. If you wanted a memo written, what did you have to do? Well, you would call up these ladies on the fourth floor. You're a dictator. Memo. Two. And the ladies on the fourth floor would type up your letters and they'd bring it up and then you'd red ink and mark up what you have. Okay, and then you'd go bring it down and bring it back up and look at what happened after Wordstar and WordPerfect and Word came about. Imagine if we didn't have these tools today. We'd be frustrated. Well, in the BI world, it's the same thing. People don't have ways to answer their questions and explore the data. And so I think of it more in that context of Word or Perfect than I think of the operating system. Well, I mean, it's a whole new ball game. I see how you guys are looking at it. I like how you're taking them very apple-esque. That's my kind of interpretation of it. I like how you're thinking differently. You're getting out in front and reinventing the future while having a lot of happy customers. We're getting the hook here. I love talking product to you guys. I love it too. Very successful product. And again, that's the challenge. Keep on being successful. So Francois, agents stat here. I want to give you the final word. Share with the folks out there. You've been with Tableau for four years. Your stock's still vesting. You're still here. You're having a good time. What is so special about Tableau having this company? Why are people, I mean, is there special Kool-Aid being injected into the veins? Why are everyone so happy? I mean, they pump special oxygen in the room. It's just fantastic. I think it's the combination of an amazing product, incredibly amazing customers and partners that we can interact with, and this big mission that can really take us and you can see the impact that the mission can have. And your product focused for the next 12 months hardcore. What's the straight and narrow for your product team? What's the, where are you guys going to gas it? What's the key thing you're going to build out? Elastic? Well, as you saw in the keynote, there's a lot of things from drag and drop analytics, mapping visualizations, performance, performance, performance, that's really important. Data preparation tools, storytelling, enterprise, massive enterprise capabilities. We're investing in the cloud and we're missing on mobile. We're not just looking at one thing, we're trying to really think about this broad spectrum of how people see it and understand their data. And I gotta tell you, I'm so excited. I think that everything we've done so far, that's just been the prototype. It's amazing what's coming next. Congratulations on your success. Thank you. A lot more challenges ahead. You got a globalization plan, you got channels, you got new products, new requirements. Again, 55 million customers potentially out there for you guys. Good luck with it. We're live here in Seattle. This is theCUBE talking to the product czar at Tableau. We'll be right back with more analysis after the short break. I'm John Furrier with Jeff Kelly. This is theCUBE.