Speaker 1: My name is Lindsay Lang. I am the account manager for Stanford University. I've worked with folks on campus for a few years now and I'm based at our headquarter office up in Seattle but we do have a Tableau office on El Camino Real in Menlo Park and Encore is based in Arizona but we help clients here in the Bay Area so we're here pretty frequently. And basically today what we're going to go through is a quick introduction of our technology and our company and Tableau at Stanford and then we're going to, I'll walk you through a couple examples that are out there and to give you some context of different ways that Tableau are using, people are using Tableau with their data. Then Encore is going to do an introductory product demonstration, show you from the start to finish how to connect to data, perform some analysis, create a visualization, create a report, a dashboard and then publish that for others to consume. So we'll go through that end-to-end and we'll leave you with some great resources to help you get started. Once you leave today, the best way to learn Tableau is to really just jump in. So we're providing a trial for everybody who wants to try it in this room or anyone else you can share that with. There's no trouble but some people don't know how to get started and I think that would be one of the primary messages I'll leave you with today is just give it a try. You're not going to break anything and it might be kind of a fun way to work with your data. And then Trace, I don't know where Trace went, is going to walk us through some of his dashboards. He's been using Tableau as well so it'd be fun to get context from him how he's approached his data with Tableau software. So the fun thing about Tableau software is it started here at Stanford. Did anybody know that? Not too many people but one of our co-founders, so it started in 2003 and our headquarters was down here and then they moved to Seattle but Pat Hanrahan who is furthest to the right, he's a professor here in computer science and so he's on campus most of the time and then he shares his time at our other Tableau offices. But Pat was a professor here and he got together with Chris Stulte who's in the middle who was a PhD student in the computer science department, a data scientist. They got together to create our query language called VisQL. So there's some pretty fun information on our website out there to learn a little bit more about that query language but they teamed up with Christian Chabot who's furthest to the left. Christian was a student at the Graduate School of Business. So they teamed together to create Tableau software because they were funded originally from a project from the US Department of Defense to help people query large amounts of data quickly and easily. That was their main goal and the fun thing about it is Chris and Pat had done a lot of research of technologies. Okay, if we have data today, how are normal people in offices, in jobs that depend on that data and that information to do their jobs? How do they approach it today? So they tested all these systems out there, these business intelligence technologies end-to-end and it would take days or weeks to even set it up and to get started and they said this has to be, there has to be an easier way. There must be an easier way to do that. So that was the beginning of Tableau. Pat is a really interesting gentleman. We asked him to come today but he's in meetings already. I did find online that he's speaking at the School of Journalism on February 11th on campus. So you could probably find that online too but his background is in graphics. So bringing data to life. He was one of the developers of the rendering technology behind Pixar. So if you think about how they used to make animated films years ago, it would take years and teams of hundreds of people. They created a computer technology which allows that for animation. So he has three Academy Awards that he's gotten from his work and you know the first movie that that technology helped produce was Toy Story. So he has a really fun background. He's a great person. So their goal was to help people see and understand their data, simply put. We've developed our technology around connecting to a list of data sources. So depending on where your data lives, you'll be able to connect Tableau to that and better ask and answer your questions in a drag and drop format without having to do coding or knowing complex technical languages to get insight from that data. So that was their goal in the beginning and it remains their goal today and how we develop our technologies around that. So we have three products out there today and Tableau Desktop is what everybody would use to create a visualization. This is where the bulk of your time is spent. You can connect to data, do analysis, create calculated fields, build your visualizations, explore your data, do the data discovery and ad hoc analysis in desktop. And then the other two products you would use to share this information. So if we want to share a dashboard and with others in our organization or maybe a sensitive data that you want to stay behind a firewall, you could use Tableau Server and then Tableau Public will actually show quite a bit of examples that are posted to Tableau Public today because that's pretty relevant for people doing research. Tableau Public is free to use for non-sensitive data. Data that on the climate, data on politics, data on the weather, data on sports. There's literally hundreds of thousands of people that use Tableau Public just on their own for fun and they publish their visualizations on their blogs. Or there's commercial organizations that use it for journalism. So Wall Street Journal, USA Today, I've seen visualizations a lot that are created in Tableau and shared with the general population. It's kind of fun to think about when you look back at information and just if you're reading the news on your phone or on your iPad and you see a graph, it's become really natural for us to click or to touch it and want to drill down and interact, at least for me anyway. And so a lot of that is built with being able to ask questions and drill down and drill up with your data. And so people are doing that with Tableau Public. And that's where I found some of the visualizations I thought would be a little bit more relevant for the group today versus someone that's running a business and they're doing their financial reports in Tableau, things like that. A lot of commercial organizations use it to run their business, but there's a lot of more interesting ways to view data within the research world. And for a quick reference, there's a great community of Tableau people or people that are using Tableau on campus. Whether it's in these groups, but also a lot of professors are using it more and more. And then students have free access to Tableau software as well. So I know there's a couple courses that have just begun where Tableau is being used. And even a data visualization program that's beginning on campus as well where Tableau will be used. So it is a nice community on campus and then within the Bay and then globally, we have a large community of people. If you have a question, there's probably somebody out there that's answered that and would love to connect with you on that. So I'll jump into a couple examples right now, but it'd help us for context. If you've got a data set today, would some of you volunteer the programs or technologies you use to ask questions or to create a graph? Excel? Most people use Excel. Anything else? R. Okay, nice. Tableau integrates with R, which is, I hear R is used for very complicated things, but I hear that the output, the graphical presentation layer isn't quite as strong. And so people will use R and then have Tableau sit on top of that, which works really nice. And then the same thing with, or close to with SPSS and SAS and things like that. So when I was looking at visualizations, I thought of Ramon Martinez. And I've worked with Ramon probably for about six and a half years because he spent a lot of his time in Central America. And he was a guy that was out on site doing research for the Pan-American Health Organization on disease control. He spent some time in Africa doing malaria research, things like that. So he was literally on his own, somehow got connected to the internet, and somehow found Tableau. And it was pretty fun to work with him because he took to it right away. And it blew his mind how he was able to get more from his health data than ever before. So I really like his blog. It's called Health Intelligence. He uses Tableau Public a lot. So we're going to reference quite a few of these examples here today. But I think he's a really good starting point. He has a great way of explaining his goals and how he's working with data. So this is a visualization that was created in Tableau Desktop, published to Tableau Public because it's all public-facing data. And then he embedded it into his website. So it's all, we're in Chrome right now. It's all URL-driven. And this is an interactive visualization that talks about infant mortality. A little bit of a dim subject. But right away, what I can tell, which I didn't know before looking at this visualization, is in Africa, that's a major outlier compared. And so he's really looking into a lot of the breakdowns of the different areas by their infant mortality. So just as an end user that's never quite seen this data before, naturally I just want to start clicking. So I can click on the little date filter up here in the right. And I can change the date depending on what year I want to look at this data and maybe understand how it's changed. Hopefully gotten better. Yeah. And then you can hover over some of the points and view the underlying details. So this is how Ramon thought it would be helpful to share some of this information with other people. And a lighter note, here's another beautiful visualization on diabetes worldwide. So right away I can see, we probably don't have data for these countries in Africa, but Canada has got really lower rates of diabetes compared to a lot of other countries. So this is, his are really revolved around healthcare information, but if you think about it, any type of data that you have can be represented in Tableau. Another fun one is the Scripps Institution of Oceanography in San Diego. So we started working with DataMars on some of their fisheries data and they've done a really nice job of communicating that information to the public on their website. So on DataMars.ucsd.edu, there's Tableau visualizations on most of these pages. But for example, this one is tracking mantas. So they literally have sensors on mantas and they're tracking the paths of where those mantas go. I think there was about 20 of them. And they tracked them for six months. So to understand what is their, I guess, what are their trends within what they do and their behavior for these different ways. And so there's, maybe there's just five of them. They named their mantas and then the color represents the name of the manta. So you can see, here we go, McConnell is moving around here. And they put this on a map. A lot of the public facing data has geographic information. People really like to share the maps with other folks. So it's really fun to understand and take a look at some of their behavior. They have a lot of examples here on DataMars. And then the, this is another one I found online. It's just completely different context, but out of the University of Washington, they have a rowing club. They were tracking data as they were on an expedition from Africa to the U.S. So this one they published directly to Tableau Public. They didn't embed it in their own site. But it's the same type of idea where we want to take a look at the data that they captured when they were on this expedition, literally on a boat. And some of the different filters they chose is you can look at this by the fluorescence, the time, and then the temperature. So apply these filters and look at the data a little bit differently. There's a lot of other use cases, especially in healthcare. Some of the other, UW Medical Center in Seattle is using Tableau to take a, basically to keep their beds empty. So what is going on in the climate and how can we keep people out of the hospital, which is really nice to think about because none of us want to be there either. And so they're taking a look at a lot of the climate data or where people live, maybe what's going on in the environment where they live, disease tracking especially. Sports is a whole other world. There's a lot of great examples out there on Tableau Public. So the website is, it's an extension of our regular website, but it's the public facing information right. And there's literally thousands and thousands of visualizations that you can just browse through the gallery and through the community to take a look at how other people have approached their data. And a lot of the time you can download these and open them up in your own version of Tableau software. And you can see how they were built. If there's something on our website or on this website that you're curious to be like, that's what I want, I want trend analysis over time with these types of reference lines, how do they build it, you can download it and open it locally and see exactly how they did that and try to replicate it with your data. So that's a good segue into how to get started is our website, Tableau.com. There's, the number one place I would recommend people get started is choose a data set and start your trial and then come watch the training. We have a lot of different training options. A lot of times people are doing this maybe over the weekend, on a Sunday afternoon they want to take a look. We have training that you can access anytime. It's the on demand training. So I'd watch this 20 minute video that just helps you kind of wrap your head around connected data, the drag and drop interface, how to get started. And then if you want to get into more advanced topics, then you can go to, you can look at the calculations and statistics. There's some training on R integration as well. And then mapping, there's so many advanced things that you can do with mapping. So drilling in here is really nice. And then you can also sign yourself up for hour long training courses with an instructor that's usually Tuesdays at 11. Just put that on your calendar. And then there's a lot of other nice options too, but it's good to point out that once you get started there's some really great guidance to help you kind of wrap your head around it. And because it, Tableau's easy to use, but it's a new language. You're learning a new way of working with data and there can be a learning curve. Some things will come, I'm sure Chase could help us with how he approached it, but some things will come very naturally because it's somewhat similar to Excel or other technologies we've used, but then it's a completely different approach. And I'd like to point out as well our community. I mentioned there is a community on campus, but there's a whole world of people that love to use Tableau rather than do their day jobs. So they are happy to answer your questions on the forum. You can literally post a question on the forum or search the forum. Most likely someone's asked that question before. And then even just the World Wide Web on Google, I use that more and more than searching our website even. If I'm looking for table calculations, then I'll just search that on Google and these will also be indexed, our help documentation and then partners out there that love spending time in Tableau. We have something called Zen Masters, which are some folks that do, Ramon is a Zen Master of Tableau software. These are folks that truly embody information and sharing information with other people and they're on there all the time answering people's questions, so it's pretty fun. Thank you.