 joins the CUBE alumni. Welcome, John. You got any phone calls you need to answer? Hold on, let me check. Live from New York, it's the CUBE, covering big data NYC 2015. Brought to you by Hortonworks, IBM, EMC, and Pivotal. Now for your hosts, John Furrier and Dave Vellante. Welcome back, everyone. We are here live in New York City. This is SiliconANGLES, the CUBE. This is our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the founder of SiliconANGLES. This is my co-host Dave Vellante, founder of wikibon.com. And our next guest is Jeff Bang, VP. I'm sorry, product manager. VP will promote you, product manager at Tableau. CUBE alumni, great to see you again. We had a great chat last time. Tableau, obviously public company, big company now, even though you're still acting like a startup, great to see you. So obviously visualization continues to lap the field in terms of the number one use case, storytelling, whatever you want to call it, big data, really is all about what the data is telling us, what's going on in the data, the human interface. But now you've got machine learning, a lot of stuff going on under the covers. But still, the analytics is the killer app for data and how you present that data is the key. So give us the update. What's going on at Tableau and what are you seeing here at the show? Yeah. Well, the latest at Tableau is we just had our latest product release, which is Tableau 9.1. And what Tableau 9.1 does is it makes data even more accessible than before. So one of the highlights of 9.1 is we just released what's called the Web Data Connector. And it's essentially a lightweight developer-based tool that allows you to be able to connect to any RESTful API service. So when you think about trying to connect to Facebook data or Twitter data or even Google Sheets or something, we anticipate that the community is going to write connectors to be able to connect to all these different data sources. And that really makes data much more accessible. In addition, we've also added some additional new named connectors, such as several new Azure data services, Amazon Aurora, as well as Google Cloud SQL. And on the mobile front, we've also have a refreshed mobile app that includes offline snapshots, which means you can take your data with you wherever you go. So what's the big news? I mean, obviously, there's been open source tools out there we've seen. And then on the high end, you've got automation with visualization. You guys got connectors. Obviously, people want to take the data and make sure it's connecting to the visualization. But there seems to be more competition, but yet I don't really see competition. So it explains the landscape of the business because you guys always have been the leader. But yet it feels like there's more competition, but I really can't name one company that's competing with you. So I mean, what is that all about? Share with us because it feels that there's a lot of visualization tooling, but you guys are still winning. Yeah, well, I think it comes down to our core value proposition, which is being fast, easy, and beautiful. So when you think about the amount of friction it takes to be able to get to the answer for a question or how many questions you can answer along the way of your analysis, that's what Tableau really excels at. Now, there are plenty of other BI companies that have specialized features in certain areas or may excel in other areas. But when it comes down to the vast majority of business users, they just want to be able to find answers quickly and be able to come to a solution easily. So you guys have always had, Kristen Shabbo talks about the land and expand strategy, and it's just amazing, the uptake. And of course, you talk about the old, he talks about the old, slow BI tools. He does it in a way that's quite tongue-in-cheek and funny, but of course excel is obviously the big one. But Tableau is gaining a lot of traction. Can you sort of lay out the sort of relative momentum there? When you think about these other, the old, slow BI tools and whatever visualizations they have, excel can still ubiquitous with all of its limitations and then Tableau, just sort of rocketing. What's your take on all that? Yeah, I mean, my take on that is, it all comes down to the end user experience. Like how delightful is it to be able to create your visualizations? Do you get positive feedback as you do certain drag and drop motions? And so as a user, when you get that immediate feedback, and you're able to be successful, then that really adds fuel to the fire for our land and expand strategies so that they're much more happy to share with their friends, their colleagues, and all of a sudden, before you know it, you have full departments and companies adopting our software. And so when you think about the BI tools of old or even excel to some extent, Tableau is just so much easier and more delightful to use. And you've also done a good job with the college kids. Kids coming out of college today, they talk about, oh, yeah, Tableau, are they throwing are? I mean, those are the two biggies, but was that deliberate or is it sort of just pull? You know, I think it's, I wouldn't say it's deliberate, but I would say that we're trying to make our software available to everyone. We do have an educational program which makes Tableau free for, I believe, a year for college students. So we're hoping that by making it available for them to adopt and to try it out, that we'll have a new generation of people who are familiar with using Tableau. What about how I get Tableau? Is that changing? What's going on with it to keep announcing some stuff in cloud and mobile and the like? Maybe talk about that a little bit. Some of my options there. Yeah, definitely. So I mean, we do see a slight trend in terms of where data is being landed and where data is being leveraged from. And so I think increasingly data is being stored from the cloud and therefore like online business as well as our cloud business is becoming increasingly more important because people are going to want to use their BI tools based on where their data resides. Well, in IoT. Talk about the competition. You guys got, I mean, I mentioned that earlier, but specifically we had ClickOn earlier. They're also a public company. They're valued, I think, $2 billion less than you guys. You've got micro-strategies out there. I guess they're kind of in there. And again, that's the old BI play, right? I mean, you put them in that game. Performance is certainly Excel. But I'm looking at the stock price now for a second. I'm not going to ask you a stock question in your public company. I'm not going to answer it anyway, but in your product, we want to talk product. But the stock price reflects a couple conditions out to the market. It kind of is weird, but product-market fit is a big thing. So you're the PM, right? As the PM, product manager, what are you guys looking at for the product? Are you guys happy with the trajectory? Are you going to be bolting on new things to kind of bring added functionality, land and expand from a customer base makes sense, but now you've got to grow your product base. You've got to drive more revenue, right? So that's the goal from the CEO. Okay, hey, let's keep happy customers happy and keep shipping new functionality, hopefully that they want. So what's the key differentiator for you guys, vis-a-vis, say, click, for instance? Yeah, I mean, so in terms of where we're investing, I think it's all across the product, you know, an area such as performance, making it easier to work with your data from when you first get the data, as well as, you know, from our Tableau online business, as well as Tableau server. So we're really innovating on all fronts, but I think when it comes down to, you know, how we compare to, you know, our competitors, it really does come back down to, you know, how easy and how elegant it is to use our tool. To use your interface, combine with some of the automation, tooling, et cetera. Right, exactly. Like you don't have to go through, you know, a, you know, some sort of like, chart creation menu to get to your, to create your visualizations. It's really, you know, how many clicks does it take to get there? So versatility, flexibility, and then ease of use, pretty much what you're saying, right? Exactly. Okay, so let me ask you a question. I'm not going to push it on the spot too hard, but it's kind of a generic question. I think you can answer this one. So we were at Splunk Conference last week.com, which is their big annual conference. And one of the things I mentioned to them was, I mean, there's still a product company like you guys, and not so much solution because they've got good stuff going on as well. And they have their nice beachhead in the marketplace. And again, kind of like to have a good culture, start-up culture, but different use case. The question I had for the Splunk was, and I'll ask you is, at some point, you got to make a move and bolt onto the core platform, new enabling opportunities. At the same time, you don't want to be too shotgun from a focus standpoint, right? So focus is an issue because the customers are probably pulling you in 10 different directions. That's one of the problems with big data is a zillion use cases that may look great. So it's like the danger is looking at every potential opportunity as a product. And you know how hard it is to run a product roadmap. It's like, you follow up on my question, and does that make sense? Yeah, I think so. Yeah, focus versus balancing a multitude of use cases. What do you guys, how do you guys view that? How do you manage it? How do you keep your focus? And what is that focus? Yeah, so I think a couple of things to that. I think number one is we focus on quality above anything else. So when you think about all the choices you can make in terms of as a product management team, you can add new features. You can improve the overall quality of the product. We try to put an extreme emphasis on quality over everything else so that users have a great experience with whatever features that they do use. Now in terms of adopting new features, we take it from a combination of what our users are asking for. So we have a community forum where users actually vote up and down, well vote up their individual ideas that they're really interested in that they'd like to see if this feature is in the product. And so we heavily look upon that list and draw from that to understand where the greatest pain points are for our customers. But we also balance that with features that we know would really improve the product because oftentimes a customer doesn't know that they want to, a customer doesn't know they can fly an airplane if they're driving a car. That's a good analogy. So let me ask you the next question, because this is more industry question. This event Strata Hadoop, that's in conjunction with Big Data NYC that we're throwing on here, seems to be the pace car for your business. At some point, the underlying infrastructure and the ability to wrangle, present, ingest, all the stuff they talk about is going to be limited by what they're doing. So how do you see this market that's going on at the Javits Center in terms of Hadoop, Big Data, because there are a lot of underlying enablers that are accelerating the movement, but some customers are saying it's not fast enough. Certainly visualization is kind of like waiting for the relay race almost, like waiting for the hand up, the more data you get, the more powerful visualization is, and then the more important in machine learning. And so it's a nice flywheel of innovation. So what's your take on that innovation flywheel? Where are we and what are some of the things that need to go faster in your mind? Yeah, so in my mind right now, that the overall Hadoop ecosystem right now is moving from a period of focus on just the technology to real business end use cases. And that's something that Mike Olson alluded to during his keynote, I believe, yesterday. And I believe that that focus is really going to increase the adoption of Hadoop, as well as the whole ecosystem of data prep, data integration players, advanced analytics. And so I continue to see a steady uptrend in terms of that overall business. And that, of course, is going to help Tableau as well. And, but then you have to look at, for Tableau and our overall business, we look beyond just big data, but we look, we address like all data. And so that means relational databases. It means CSV files and Excel spreadsheets. We had Bruno Aziza on before. He's with AtScale. Is that this company? AtScale, yeah. And I don't know if you're familiar with the survey that all you guys did. So it was AtScale, Cloudera, Hortonworks, MapR, and Tableau. Did you see that? Yeah, I'll stop briefly. Yeah, okay. So you were intimately familiar with it. But it was interesting. I mean, sort of basically talking about BI on Hadoop and kind of the trends that are going on there. And it was pretty significant, the uptake on Hadoop. But you guys are obviously more than Hadoop. But how much is that driving your business, that move to Hadoop, the whole Hadoop movement? Yeah, I think it's a significant enabler, especially when you think about the Fortune 500 and Fortune 1,000 companies that are significantly investing in Hadoop as part of the core data platform. And generally speaking, when you see large deployments like to Hadoop, you're also going to see large deployment of BI tools such as Tableau. And so I think that definitely is a driver for our world business. And what's your take of the big data separation on Hadoop? Obviously, a lot of the big whales are coming in. IBM, EMC, Oracle. I mean, you have a lot of big incumbents coming in. Do you think that they're going to mop up some of that or break some of their proprietary technology? What's your take on the big players moving in? Yeah, I mean, I think the big players are obviously going to have a large footprint with their existing customer base. But I think that this is still a very nascent space and very early on. And so I think there's a lot of room for expansion for all players. So what are you getting excited about these days? I mean, you're actually getting Tableau. You're proud of it. You've seen a lot of stuff. As you kind of look outside the Tableau realm in the market, what's getting you excited as you're going, man, this is going to be a 20-year run for this business. What do you see out there? What anecdotal data you could share, comments, color? Yeah, I mean, I think when I think about the future of this overall analytics space, I think about just the overall adoption amongst companies and becoming having more data-driven businesses. And so I think that we're just on the very tip of starting to become more data-driven. As you see, companies that tend to be more in the leading edge technology have adopted data much more readily than, say, maybe companies that have been around much longer. And so I really think that we're just getting started in terms of the data revolution and then people becoming data-driven in their decision-making. And what are people expecting to hear at your conference coming up in a few weeks? Yeah, I think what people are going to expect to hear are people are going to be expecting to see some really cool product announcements, which again, I don't want to share yet. I don't want to spoil the surprise. Come on, spill the beans. Look, you. The cube will not be there. If you remember last year, folks, we were not going to be there this year. So look for the coverage coming out of Tableau.com and all the news wires. But to share a little bit of taste, high-level themes. Can you share a little bit? Yeah, so I think high-level themes, we're going to continue to talk about our improvements around performance. We've made our first forays into data preparation if our 9.0 release. So you'll probably see more there. And then we have our continuing investments in Tableau online and our mobile product. So I think all of us across the board, we're going to see a lot of exciting news. You guys write your own database. I mean, you guys dealing with data all the time. You've got Spark is killing it. How about database and in-memory? What's your guys, you guys doing your own homegrown there? Do you work with another vendor? So we have a really unique data connectivity story in that we support both live as well as in-memory extracts, which we call our Tableau data engine. And so that adds a whole another dimension of flexibility for all of our users because... Speed. Right. You can augment your speed if you have a slow database by using our Tableau data engine. Or if you have a fast database, you can just go hit it directly live. And so... But you guys don't ship your own database, do you? It's not like a really own database, but our own like data formatic, as you could say. Well, you have your own data suspended to your application. So I mean, that's normal, but like not like a database, not going to be selling a database. No. All right, well, Jeff, thanks so much for coming on the team. Really appreciate it. It's always great to get Tableau. The leader in visualization, again, one of those successful startups, and I stand corrected, I just checked, you were $3 billion more than the next competitor. So congratulations. Continue to see success. Visualization is the storytelling behind data. Tableau is the leader. We'll be right back with more data after this short break.