 I'm John Furrier, the founder of SiliconANGLE.com. This is theCUBE, our flagship telecast. We go out to the events, extract a signal from the noise, and I want to be joined by my co-host. I'm Dave Blonte, with the BAN, share information, collaborate and develop open source research, so check out the BAN.org website. And it's my pleasure to introduce to you, Dan Jewett, Vice President of Product Management, at Tableau Software. Tableau is becoming the gold standard for visualization and big data. Dan, welcome to theCUBE. Excellent, thank you for having me. So, we first heard about Tableau several years ago at this conference when one of our friends and colleagues, Abhi Mehta, who was at the time, at the B of A, building the data factory, talked about Tableau and sort of introduced us to him. Now, you guys started the company before this whole big data trend even occurred. Maybe take us back and give us a little bit of history. Sure, absolutely. So, it was great that Abhi did that introduction. He's been a big champion of Tableau for a long time. Tableau started way back in 2003, technology spin-out of Stanford University. Co-founders were doing their PhD research at Stanford, and it was kind of, even that was an interesting background. It was a Department of Defense grant given to Stanford to try and understand big data at that time that they had tucked away in their databases, but it wasn't even called big data then. So, they gave a grant to Professor Pat Hanrahan, who was one of his many claims to FAMES was being the architect of the RenderMan software, which Pixar uses to create all those great movies. So, the Defense Department came and said, you're a visualization expert. You've got a team of PhD students working on visualization. We've got a data problem. Help us understand how to make sense of what's in those databases. And now it's the beginnings. So, if there's some event, I mean, notice the number of partnerships you guys are announcing, because everybody's lining up to do deals with Tableau. Talk about Tableau. Yeah, absolutely. For us, our mission is to help people see and understand their data. So, having access to all the different data sources that people have becomes really critical for us. So, this week we've announced a number of new connectors and expanded out our footprint into the Hadoop world. So, we've supported Cloudera and MapR for about a year, but this week we've announced, along with Cloudera, as they've done their Impala announcement this week, we've announced that we've got support for that. We've been working with Impala and the team to test that and get our systems hooked up into that. We've also are announcing support for Hedapt and Hortonworks as two new Hadoop distributions that we support. We're working with both those companies to bring visualization to their distributions of Hadoop. Kind of in the big data space, but not necessarily Hadoop, there's a company called DataStacks who makes a product called Cassandra. And we've, that's more of a no-SQL type database. We've now hooked up and wired into that. Yeah, the Cube was at the Cassandra Summit earlier this year. All those companies you mentioned, all friends of the Cube all have been generous supporters of underwriting our great program of independent coverage. So I want to put a plug out to all those names you just mentioned. It's great to be part of this ecosystem for three years now, this is our Cube. So it's fun to watch it grow up from pioneers emerging from Grants to Stanford to really creating an industry. And we look at this marketplace as a whole new industry, like the computer industry was birthed by the computer, a personal computer and then a client server. But one of the observations we said information on demand IBM's conference earlier in the week was the big data revolution is as powerful as the PC revolution and the client server revolution combined and happening faster. So obviously that's happening, right? So one of the big things that everyone's talking about this year is insights. And insights is about visualization. You guys are in this. So I want to ask you about insights. One of the keynote presenters from ClearStory said it's not about visualization, it's about making sense of the data. Tell us where you guys are at. Obviously you're partnering with all the platforms to simplify the experience, which is another factor. Talk about your vision of, okay, visualization step one, insight and what's next. Right, well that's a great segue there, right? So insights are the key part of what you're about. So we don't think of ourselves strictly as a visualization company. Visualization is the output of what we do. We're really an analytics company. The twist is we're an analytics company to help the individual understand this data. So it's not about necessarily a data scientist, although data scientists love Tableau, it's about more of the regular person and how they can have a discussion with their data. Those are the folks who have the hunches and the guesses and the hypotheses about what's going on with their data. And the visual paradigms that we expose to them are what really start making those stories come to life. And then it's that iterative, discussion centered dialogue that turns into the insights. So Tim asked these from Digital Reason who we're a big fan of. He's also been on theCUBE and great guys. He's doing all his work in this area for a decade or more. He talks about this understanding gap. And he showed a chart in the keynote that showed massive growth of data we all know, unstructured being 60 something percent of it, but the attention has been flat, meaning people aren't getting enough out of the data. Can you comment on that and what's your perspective on that? And what needs to change? I'm glad you mentioned Tim. He had another slide in his keynote that was people are greater than data, right? And having the data is one thing, but if you don't have access to it, if you can't understand it, if you can't put that human touch on it, the human understanding of it, you've got a gap there. So I think even though the data explosion is there in capturing the data, what folks like Tableau are bringing to the market is the way for people to take advantage of that data. So take us through now. We've got that all the high end stuff covered in positioning and kind of the analysis. Let's go into some of the real world conversations. People are using data. So take us through some of your experiences in terms of how you design products and how they're rendered themselves in the market. What are the use cases? What are some of the things that people are really enjoying with Tableau and with Insights? Okay, so scenarios with Tableau are all over the map. We've got the biggest retailer in the world is standardized on Tableau and uses that. We've got the number one electronic marketplace on the internet uses Tableau is standardized on that. And they do all the standard things you would think of of product management and brand management and category sales management and things like that. We've also got three researchers from John Hopkins University in the field in Africa doing research on malaria. And they have a satellite modem that they're transmitting data back and forth. They're out there in the field using Tableau. We've got a gentleman last Christmas bought a single copy of Tableau for his son to analyze data that he was working on in a science fair project. Now all of those folks, maybe they're not touching Cloudera per se, but in their world, a high school kid doing a science fair project, big data is big data to him in his world. If I'm a large retailer, I've got a petabyte sized database. And I still need those same tools and those same discoveries out of it. I mean, I wrote a blog post in 2007 or eight. I can't remember which year it was, but it was early. And I said it was one of those provocative blog posts. I said, data is the new development kit. But back then, no one was really talking about data as a way to develop or play with data or develop, use it as a development ingredient. That's your business. You just mentioned the high school kid. So you range from the high school kid, the kid in the dorm room to data scientists up and down from big financial companies. So this new development of data is key. So how do people play with data? What's the developer look like, developer being anyone playing with data? For us, it's anybody, if you have either a mouse or a finger if you're on a tablet, we want to really have people reach out and touch their data and kind of dive in and explore with it. So it's a canvas, you drag and drop, you undo, you back up, you look for trends and patterns and things start popping out at the page for you. And then you can start drilling down and knifeing in on those unusual things that you see. So it is really an interactive experience with your data. Can you talk about from your product guy, can you talk about how you're adapting to this new world? Because Tableau predates Hadoop. Absolutely. So this notion of distributed systems that wasn't as much prominent when you guys were founded. So how are you adapting to this whole big data movement? Well, so there's two key things I think we have on that front. So when we started, we built the premise around, we need to connect to your data and run a series of live queries to the database. And we want to interact with your database that way, pushing a lot of the requests and the work back to the database. So that's a key tenet for us is we want to leverage what the database gives you. Now when you move into some of the big data solutions, sometimes latency's been a problem or running queries at that scale maybe isn't an interactive type experience you want to do. So then a few years ago, we've introduced our own in-memory analytics engine. So now the balance point is, how do I appropriately and I can appropriately run queries to the live data source, but I can also snapshot and bring things into our in-memory engine to accelerate the analytics along it. So it's a very seamless transition between the analytic experience of pulling data out of the raw source or choose to put it in memory to supercharge the performance. So where do you see this going? I mean, historically, the whole decision support business has been a very small number of analysts have a big impact. They put the beer next to the diapers and watch what happens, but your mission is really to set anybody with a screen and a mouse. So where do you see it going long term? It's really got to reach out and become pervasive, right? So we've done some things with another product we have called Tableau Public where we're basically giving visualization back to citizens of the world, right? It's a free place. If you have some data, you can publish your data to the Tableau Public server and make it available for everybody on the planet who has access to the internet to start interacting with it. It's not just look at a picture. So we really think that it's going to reach out and touch everyone, you know, your mom, your dad, your kid, your neighbor who's maybe a rocket scientist, but the kid next door who's still, you know, in high school, they want to interact and touch and collaborate around that data. And that's where I think it's going to go, the Joe Everyman. So my final question for you is, what's the big question that's unanswered yet? No pun intended or pun intended. Big question, big insight, big answer. For individualization in your world, what's next? What's the big question that needs to be addressed? So one of the things we continually focus back on is that you don't know what that big question is from your data. You need an iterative discovery process. So the big question is, well, what's the next question I need to ask? And your data is going to tell you that story. You have to have a way to tease that story out of your data. Okay, Dan Jewett with the Tableau. Thanks for coming on theCUBE. You guys are a leader in visualizations where one knows you for, but you're really an analytical platform, analytics as we said in our opening segment is the hottest area. Second hottest area is business value. That's where the focus is and data is that road to business value. So we'll be right back with our next guest after this short break.