Speaker 1: I think up next, we have Jock McInlay, who is a Tableau employee. He is the vice president of research and design. Welcome, Jock. Thanks for taking time out. I'm sure there's 18 people vying for your time. Appreciate you being here. So maybe you could start off telling us a little bit about what you do at Tableau and why you're with the company.

Speaker 2: So I run the Tableau research team and also the UX design team I'm in development.

Speaker 1: So pretty much everything that was in the keynote today, you guys have been like busting your bottoms to knock out.

Speaker 2: The research scientists had absolutely, you know. So I started Tableau research three years ago, 2012. And some of the results are starting to show up in the keynote. So it's very cool.

Speaker 1: That's really cool. Yeah, so it's about, you're saying it's about a two or three year investment time. That's our goal.

Speaker 2: Yeah, when you're doing that kind of research, it takes a couple of years for it to actually materialize in the product.

Speaker 1: Totally. And I'd imagine that's something really difficult right now with all the innovations and new products come in all the time hardware changing, you've got to support different devices.

Speaker 2: Well, hardware change is an opportunity, right? Things go faster, and so it's really, really a benefit. But yeah, I mean, on our mission to help people see and understand data, innovation is really critical. I mean, we're only getting started here. And so it's very important for us to continue innovating. Our user community is the knowledge worker, a very broad community of users. And we need to make it very useful for them. We want to both have a lot of analytical depth as well as really make it easy to use. Those two sort of go the opposite direction, and so it requires innovation to do them together.

Speaker 1: Absolutely, and what does your whole process look like when something ends up as a feature? Can you backtrack for us everything that went through to get it there?

Speaker 2: Sure, well, so for a research scientist, they have a great job, which is that they manage their own research portfolio, and so they get to explore ideas. They'll test ideas out by writing academic papers or building prototypes, and then at some point, the research matures, and then we start to realize that this is something serious, and we start to invest a development team to do the work on that, and then it goes through a development process, and then it starts coming out as features, and then extended features over time.

Speaker 1: Very, very cool. So what are the hot things in Tableau right now? What are you personally really excited about?

Speaker 2: Well, so one of them was the lead off at the keynote this morning, which is the ability for people to work with data from multiple sources. So that started a couple years ago as a research project in Tableau Research, and it's a multi-year journey. We're in the middle of it, but being able to connect the data from different sources, it turns out when people are asking questions, it's like almost never one data source that can give them the answer. They need to be able to bring data in from lots of different places.

Speaker 1: Got it, and you guys, I'd imagine you have quite a bit of collaboration across. Can you say how big your team is?

Speaker 2: So the research team has just grown. When I started it three years ago, it was five, and it's now 12. But the thing is, is even before we had research, we did research in the company. Sure. So there's a bunch of PhDs in the database team, so they're the core team that's doing that work that I just talked about, and it's going on.

Speaker 1: And do you find folks generally, so you mentioned the database team. Do you have other specialization teams, like, I don't know, front-end teams, or?

Speaker 2: We have a whole bunch of different teams. Like, for example, one of the big features that landed in nine was level detail calculations. So we have a team that actually is on the topic of writing calculations, because the truth is, to answer questions, you often need to write a calculation at some time. And the team both worries about things like the performance of calculations, but also the user experience, to make it really easy to write them. So the level detail calcs were designed to make regular business people can write these calculations at different levels of detail. Got it.

Speaker 1: And do you find a lot of cross-pollination between those teams, or is that something that you?

Speaker 2: We have a hackathon culture at Tableau, so there's a lot of hacking going on, and people are presenting their ideas. It's quite an innovative and collaborative effort.

Speaker 1: That is really cool. And you guys have a really unique team that you need hardcore, hard competencies in there as well. But they've got to have, like you said, they can't just be off in a, give them a Linux terminal and they come back to you in a week.

Speaker 2: And there are guys on the development team who are serious introverts. So, yeah, they're sitting back in the corner,

Speaker 1: but we are very collaborative anyway. That is really cool. How do you strike that balance? Sometimes that's not a Venn diagram that matches up.

Speaker 2: Well, you hire people from a broad range of disciplines, and then have a culture in which they work together in a collaborative way. So that's what you do.

Speaker 1: Cool. And what are some of the cultural things that you guys do at Tableau? You're one of the, I think it might be only the second person I've interviewed directly from Tableau. Oh, really? What does the culture look like inside the company for you guys?

Speaker 2: Well, it's a great culture. I mean, it started, so the part we were just talking about, which is the innovation part, goes from all the way from the beginning. It was, Tableau spun out of Stanford, and we've always been, we knew that our mission required a lot of innovation, and so we worked on it that way. So, and the, you know, there's a set of core cultural values, honesty, collaboration. We use our product everywhere in the company. So that's a really interesting part, which is that the sales team's looking at their sales pipeline in Tableau every day, the marketing team's looking at their survey data, or whatever, the finance is looking at, obviously, financial data, and the development team's looking at, you know, performance data, bug data, things like that. And so that gives sort of a cross-discipline interest in what we're working on. And so as we come out with new features, there are people inside the company that can give feedback on and make it better.

Speaker 1: Very cool, and a common thread I've heard from everybody who's used you, or people that work there, just really, really genuine care for the customers, and meeting with them, and talking them through their issues. The research team is involved in that as well, I'm sure.

Speaker 2: Yeah, well, so I run both the research team and also the UX design team. So I started both in 2012, and they work really collaboratively with each other. So you have these PhDs worrying about things like high-performance computing, or, you know, visualization, or whatever it is, but there's also the UX team who's worrying about people every single day. I mean, that's what a UX designer does. And then they can give critique back and forth to each other about the work that they're doing.

Speaker 1: Sure, and if you were to assign, I mean, like you said, the UX is becoming so more important. Like, a lot of folks say that's why Uber, Airbnb, it's just ridiculously easy to use, right? And your guys' product as well. If you were, and I know this is a complete, you could refuse to answer the question if you like, but if you were to place, you know, technology, back-end technology, savviness, and speed, and all that, and you were to look at it against the UI, what is the mix there, the sweet spot that you want to?

Speaker 2: Performance really matters, particularly when you're working with data. So, and particularly with technology like Tableau, since we can connect to a huge range of data sources, including really massive ones, then, you know, data computation takes time, and people have trouble dealing with lag. So it's really important that we have high performance. So the folks at Tableau Development who are working on speed, actually, it's part of it. It's like, one of our internal credos is, fast, easy, beautiful. We want to do all three of those together at the same time. And so it starts with fast, as you notice I said at first. And if the UI is running too slow, it doesn't matter how good the user experience is, it's just not going to work. And so you have to have that performance there as much as possible. You have to, you know, obviously, working with data can take a lot of time. I mean, you know, computation can be slow, in which case you still need to have a good user experience to help you get your work done. But we start with fast. Absolutely. And beautiful matters too, actually. I said easy and then beautiful. All three at the same time is our goal.

Speaker 1: Right, and visible, I think, matches all of those, at least what we saw today at the keynote.

Speaker 2: Well, I mean, the Visible 1.0, what we just launched today, is running on an iPad. So the size of data there isn't really massive yet. Sure. But at least in our future, we want to take it to massive as well. But it's definitely, I mean, it's definitely doing a significant amount of computation on the iPad. So for the size of data that's there. So it is fast, easy, beautiful in that context. But people, when they're working with data, the data's just growing. So there's more data all the time.

Speaker 1: Absolutely, but luckily Moore's Law has not broken down yet. Luckily, yes. Do you guys have a good big brain, and kidding on top of this, do you see a point in the future, we seem to always stay ahead of it by a couple years, but is it, are we doomed? Is Moore's Law coming to get us at some point?

Speaker 2: I'm no expert on Moore's Law,

Speaker 1: but I hear that, yes, that someday we're doomed, so. Well, I'll have to figure out a solution for other things before that. Cool, so something that stuck with me from the keynote, the guy, I forget his first name, I think it was Ryan maybe, the guy that said he was Sausage Fingers. Oh, Ronnie. Ronnie, that's right. Yeah. It sounds like you guys came up with a little bit of secret sauce around that, because that's something that annoys the heck out of me on the mobile platform, is I'll smudge my wrist a little bit in the corner, but somehow it picks it up and types a letter. Seems like you guys developed a lot of.

Speaker 2: Well, we're continuing to work on that. I mean, we're very motivated to work on the mobile environment. That's part of the reason we did Visible, is because it gives us really authentic people working with data in the mobile context, something you can't do right now on an iPad, and it allows us to continue to explore. I believe that we will continue to innovate there across the entire UX as we go forward.

Speaker 1: Cool, and what platform are you really interested in right now? What is the one that you like the most, that you like personally working with the most?

Speaker 2: I like my MacBook Pro the most. Sorry, Mac, that gave you things, but what I'm really excited about is part of what we showed today, the ability to bring your data onto your phone, because you're always carrying it around with you all the time. Absolutely. So that'll be really good. So I really like with our new enterprise thing, I can actually have views there offline so that it will refresh, and then I can take the data away with me, which is really useful. But probably the thing I like the most, interestingly, is the thing I've noticed, is as we've been adding more analytical capability into the browser, I started using the browser to answer my ad hoc questions. So as I said, we use Tableau inside, everywhere, and so people are publishing these views up to our server, internal server, and I'll have an ad hoc question, like I'll be looking at some data about hiring or something like that, and the person didn't anticipate my question, but I can just open up the view, add my filters, filter it down, and answer my question and go about my business without having to download the data onto my MacBook and use it there. I can just do it in the browser, which is really awesome. I mean, these ad hoc questions come up all the time, and being able to just do it in the flow is really, really valuable.

Speaker 1: I'll bet. That is very cool. Good. And so you mentioned that you guys use Tableau internally, and you just gave a really good example of that. Have you seen other companies just, and I'm sure this is a common pattern, it gets in through the marketing department or whoever, and then before you know it, everybody in the company is using it. Do you have, no company names, but do you have examples of?

Speaker 2: I'll tell you stuff that isn't a secret at all. Core of Tableau's sales is what's called land and expand, so we're easy enough to use that we sell to anyone who's got questions that they need to answer. Just kind of everybody. Yeah, and our price point's really easy, our user use is there, so people can just evaluate Tableau on a full trial, and then start using it themselves, and then from there it expands out into the organization. We've done this over and over and over again with companies, you know, you've been talking to some people here, lots of companies as well, and that's the standard adoption pattern for Tableau.

Speaker 1: That's excellent, and it is so drop-dead easy to use. I think that's the other nice thing, is it doesn't require a big IT staff to set up, it doesn't require a lot of maintenance, everybody can just grab it and start playing with it. You've got great tutorials.

Speaker 2: If you're in a company that has a great IT staff, that's great. We do work with data warehouses and all that sort of thing. Our server works well with IT, but even if you're in a company that doesn't, like a couple years back I would say we were seeing a lot of web game companies that were collecting massive data just in CSV files, and Tableau, you could just aim them at them and start to answer questions. Now, when they got really massive, of course, you needed to put that data into a real database. That's what databases are for, right? Computation, or into Hadoop or something like that.

Speaker 1: Totally, and do you see a big, speaking of Hadoop and NoSQL engines, a big problem with them has always been, you get all this great scale and elasticity and all that, but then you've got to go and learn that engine, and it's really limited, it's typically aggregate roll-up data. I mean, you can make MySQL a key value store if you wanted to, right? It's not hugely difficult to build something like this. Do you see it, like the Nickel product from the Couchbase folks, and Hive and so forth in Hadoop, do you see kind of the death of proprietary engines? Are we all moving back towards a more SQL-based model, in your opinion, or?

Speaker 2: I have no idea. I think that we're still in a very heterogeneous place here. One of the things about the large data lakes, of course, is the computation takes a long time to run, and as I just told you a moment ago, humans have trouble with lag, and so the people that have a lot of data need to stage it so that you can get fast as well as that fast data lake that you're going to do computation over it. So I think that there's a richness here of different technologies, which is good for Tableau because we connect to all of them, and so we allow you to work in all the different ways that people need to work.

Speaker 1: But, and I might be totally wrong on this, I'm not super, you know, vested in the product and don't know a lot about it, but I believe it needs to have a SQL interface, correct? So what if somebody did have a MongoDB cluster they wanted to interface with? How would they go about plugging that together? So I'm no expert at this either,

Speaker 2: but Mongo's a good partner of ours, and so we do have a lot of customers working with Mongo and connecting with it, but I don't know the details of that. I see, okay, cool. Yeah, no worries. So what were some of the? Can't know everything. Absolutely, I'm sorry.

Speaker 1: When you say PhD, I'm starting to, I'm gonna throw all kinds of.

Speaker 2: PhDs are deep, they're not broad, so.

Speaker 1: That's true, that's true, my mistake. That's okay. So what were, being the guy who saw all this, you know, get developed and come to fruition, what were some of the biggest just moments of pride in today's keynote that you just thought, ah, I'm so glad to see that, and happy to see the response?

Speaker 2: Actually, the whole keynote's awesome, so. It was pretty spectacular. Yeah, I really liked all of it, and I'm really glad we brought back devs on stage. I don't know if anyone's told you about that, but when this conference was smaller, we would always have the developers up there presenting the work that they were doing, and we brought it back this year, and it was great. You get to really hear from the developers that are working on it. I love that. And they find a way to really explain the features they're working on, because they know them really well.

Speaker 1: Totally, and they connected so well, the baseball example and all that stuff. Yeah, yeah. They were great, great examples.

Speaker 2: That was my favorite part, actually, so.

Speaker 1: That's one thing that I hear a lot about. You guys are about disseminating information. So many of these conferences are about, you know, the expo hall, and the vendors, and you know, selling things, and you guys really, it seems like, want to educate folks. You've got significant investment. Do you know how many folks you have in the data doctors up there? It looks like at least 40 or 50.

Speaker 2: I have no idea. It's crazy. I was amazed to see that. We have about 2,000 employees here, so it's significant. And we've done that. That's a really great way for the development team, in particular, to have one-on-one contact with customers working on real problems, which means that they then can go back to work on their features with an understanding of who they're going to be helping with those features, and why, which makes the features better.

Speaker 1: Absolutely, it's beautiful. It's significant investment, but it's so smart to have your developers sitting there with your clients. And that means you've got to hire very dynamic developers, right? They're not just folks you're going to lock in a room with a Linux terminal.

Speaker 2: On my team, I tell them, you know, I actually make sure that people understand that you're going to be sitting across the table from a customer, so don't do Tableau Doctor if you're not comfortable with that. There are other ways from Tableau people to help at the conference besides that. But for the ones that are able to handle it, it's actually a really good experience.

Speaker 1: Very, very cool.

Speaker 2: So, good.

Speaker 1: That's fantastic. Do you have any sessions coming up that you'd like to tell us about?

Speaker 2: Sure, so for a beginner session tomorrow, Ginger Goystein, who's a UX designer, and I are talking about travel tips on your visual analysis journey. And so, whenever you start asking a question, you're going on a journey. And if you use your visual system, it's a visual analysis journey. And there are all these different types of views, and so we're going to talk about why you should visit any particular view type, like why would you visit maps and use them as part of trying to answer your question. Very, very cool. So that's the talk tomorrow. Excellent, do you have a, excuse me,

Speaker 1: a room and a time for that?

Speaker 2: Do you have any idea? I forget the time. Okay, very good. But the other one, so my favorite thing I'm doing at the conference is the IronViz competition. The what competition? The IronViz competition, have you not heard about this?

Speaker 1: I have not, I'm an analyst, you know how we are.

Speaker 2: Okay, so. I know what I know. So over the year, we run these contests for people who build visualizations to explain various things. We take the three winners of the three major contests we have, and on stage in front of the audience, they duke it out like an Iron Chef. Iron Chef things, with monitors behind them. I get to be a judge for the contest. Oh wow. And I love it. It's like, they do stuff that is amazing, and they're way more skilled than I am. No pressure there, huh? Yeah, so. So what did last year's competition look like? Like who was the winner, and what did they do that was so unique? I'm actually a complete blur on last year at this point, and I don't want to say anything, because all three of the contestants were tremendous, and I don't want to get into trouble with any of them.

Speaker 1: No problem, and teams of how many?

Speaker 2: No, it's one person. Oh, it's one individual, wow. And then we team them up with a Tableau person as their sous-chef, because they're so busy that they can't really even talk to anyone about it, and so the Tableau person who's helped them can explain what they're doing and why as they're going along.

Speaker 1: Oh wow, and how long is this top to bottom, the entire competition of two hours?

Speaker 2: It's one session, so it's an hour long. It's one hour. Total from the start to the end. Oh my gosh. So it's pretty fun. Anyway, the Iron Viz is the best session at the conference, in my opinion.

Speaker 1: I'm going to have to check that out, highly recommended. Cool, Jock, thank you so much for spending time with us, and we look forward to seeing you in future endeavors. Thanks so much for building all these cool things. Really appreciate it. Absolutely.