The Beautiful Science of Data Visualization

so good afternoon everyone my name is Ashley Howard Nevel I am a senior Technical Evangelist for tableau and that's just a really really fancy way of saying I know our software pretty good and it's my job to go talk to people about it to not sell them on it but to empower them to understand our software the philosophy behind our software and how they best can use our software I get to do a lot of fun things in this job I get to work with our product development team on new features I get to meet with our user research team who does studies to try and better understand how people like you use our software so we can make it the best it can be and then my funnest job of all is I get to help with the keynotes and I get to help design all of the visits that you guys see up there today so I have brought those visits here and we are going to spend some time looking at the visits that were in keynote yesterday and doves on stage this morning and we even have copies of the iron vis visits to take a look at a little bit later and we're going to accumulate at the end of this talk we're going to talk about best practices we're going to look at them in practice and then we're all going to pull out our phones and vote on which iron vis we think best applied visual best practices and we're going to crown a best practices winner to the iron fist so as you're learning and listening for the next 40 or so minutes keep what you saw yesterday and iron vis in mind because we're going to we're going to talk about that in depth at the end my twitter handle is at data Ashley feel free to tag me take pictures and then if you run into me in the hall love to chat more so we're going to start with a couple of games I want you guys to I'm gonna put something up on the screen I want you to figure out how many of the object there is ready raise your hand when you got it hands went up pretty fast how many are there I heard a 10 there's 9 up there and but this is my point exactly is that the way we get to this number is we actually sit there and count each dot here so when this went up on the screen you were like okay five on the top four on the bottom that's nine so that's our brain processing and thinking it and it takes a bit of time how about and put something up on the screen how many nines are there 64 any others Minnie Minnie this is a lot harder our brain did the first one really quickly how many I'm still hearing lots of answers how about if I do this is that easier yeah how many are there 11 so so it took me coloring it for us to get the answer right how about when we make data more complicated like this how many eights are on that screen I don't know I don't expect you to know either there's a bunch of decimal numbers in there but this is a crosstab it's a spreadsheet it's really really hard for our brains to comprehend what is happening and that's because when our eyes take in information it actually passes all the way back to the back of our brains so back here and we have what's called a visual cortex layer here and our brains have been adapted to be able to they're not adapted for numbers maybe if we like keep on this industrial age in this digital age like 10,000 years from now our brain will adapt to the numbers but they're not our brains are actually adapted visually and so when you see berries on a bush when you see a tiger movement these are all things that our brains have evolutionarily evolved to be able to best leverage and so we're tableau comes to the table is we say we don't think that you should be doing math to understand numbers we think that there's a faster and a quicker way because when I show you a picture your brain can process it in milliseconds versus taking five 10 20 seconds to get to a number and that's really the core of what tableau is rooted in it was actually our second patent is something called vis Kewell and it's an actual language that translates numbers into pictures and its core to tableau there's no other data visualization software out there that has this language and thankfully we have the patent for a little bit longer but that's what's powering tableau underneath it's not some wizard that you're going through and clicking and saying I want a chart type let's pick donut let's add in some values we're trying to get your brain out of that space of thinking into a place of reacting so let's go ahead and look at this set of numbers in tableau cuz this is actually a really special set of numbers has anyone ever seen these numbers before I got a hand up there what's special about these numbers what they have the same for statistics so let's go ahead and jump over we're going to do a little jumping back and forth between tableau and here so this is that same set of numbers here and I've go ahead and and if you're sort of new to tableau tableau this isn't the friendliest form for a computer to read so I've actually gone ahead and unfitted this data here you can see I have mother's XY coordinates still and I have that set with the point I'm going to go ahead copy all of this data and we're going to go paste it into tableau let's go ahead and oh well open up a new sheet that wasn't the workbook I expected to open up here autosave great future okay so what ahead ctrl z pasted this in you could also drag a file into tableau but if we go ahead and open this up I'm gonna make it bigger for you all it's really small unless you have like eagle-eyes let's go ahead here and hit format and make this a little bit bigger for you guys a little bit bigger to see okay so all of these here have I have a set and I have an x and a y everyone see that and I can go ahead and change this right now there are some I can change this to an average and all of these actually have the exact same number so I'm gonna change this from an average to a median and the number is actually going to still hold and this is a very special set of data for this but each of these sets of data is very different they're very different from one another so let's go ahead and create a new sheet and this time I'm gonna grab set and X&Y and this time I'm gonna use show me who knows show me lots of hands most people get started with show me show me is a really great feature um and I'm gonna go ahead and make a visualization with this data here okay I have sets and I'm gonna go ahead and pull out my point let's see we got X we got Y here this wasn't the workbook I expected it supposed to all automatically do this we're doing this on the fly together so I have my X I have my Y I have my set and I need my point here you can see that tableau is now drawing all of these values that we had before on to the visualization what's going to make that a little bit bigger for you guys so you can see drawing all of these numbers and is automatically coloring these based on that set so the first set is blue I'm going to go ahead and click on it here and we can actually see the distribution of these blue dots here and this is a if you look at it it's just sort of a widely dispersed there's sort of no rhyme or reason no trend of these blue dots how about if we click set to a pattern starting to emerge do you see something in that orange how about if we move to this one over here set three anything interesting popping out to you how about this last one here I'm going to go ahead and make that dark for you there anything jumping out to you in that set how about if we split these up side-by-side do that even though they have the same average and the same sum and the same median and actually the same standard deviation these statistical principles that we heavily rely on these datasets are very different but it's not until we apply visual best practices it's not until we allow our brains to access our pre-attentive attributes do we really start making sense of the data okay so pre-attentive attributes allow our brain to very very quickly process data within milliseconds but not all pre-attentive attributes are equal so let's jump back to PowerPoint for a second here our PowerPoint so we are going to start with another game so I want you to go ahead and find in this next game the one color for which there's only one block any one figure out what color only has one block light blue it's sort of mixed in there it's a little bit harder to see okay how about this next one dark blue got some hands awesome how about this next one it's pretty easy how about this one right it got progressively easier to find that one color dot and that's because we were leveraging that pre attendant attribute that under innate sense that our brain has of understanding color to encode information and so um so one of the sort of pioneers in this field is Kelly Martin and Kelly Martin unfortunately passed away earlier this year but she brought color theory to data visualization in a way it hadn't been before so if you want to know more about color I highly recommend you visit viz candy all of the things she wrote but what she did was she applied this principle that we had in that last data visualization of using a grayscale and then using color to draw attention to the thing that mattered she didn't just put color anywhere she put color where it was really important for you to see and and understand so this was a data visualization she made back in 2013 on birdstrikes and you can actually see very quickly the yellow stands out you guys see the yellow standing out there and what she was saying is that most birdstrikes actually happened during the day 62% of bird strikes happen during the day but more importantly than that she said that birds she shows the bird strikes happen very close to the ground and they happen very high up in the air those are so the two places that bird strikes happen you can see that in the visualization and then she has colored those on the nut earth created the size of them on the number of strikes so this is a visualization that is sort of applying best practices of color okay so we we sort of found out earlier we can't even highlight things with color we can encode that information the more we can combine that with like position now I'm gonna and sighs to add more information to quickly get to an answer and we're gonna get to the last one here so um we're gonna do one more game it's called what is different okay so what is different right I'll do it really quickly again for that one was pretty easy okay how about this one circle okay I'll show it again for those of you who everyone fine find the circle okay how about this next one oh that was someone from before okay how about this one I'll show it a couple more times everyone feel like they found the thing that's different okay let's see if I can can force it up there there you go anyone see it now I put a little circle around it so there is a red circle hiding amongst red squares everyone see that all of the other circles are green but there's one red circle up there and so this is the last piece of data we can encode we looked at position we looked at size we looked at color and the last one is shape so I want you to look at these two data visualizations I'm going to put side by side which is easier to understand the one on the left or the one on the right the one on the left is coloring regardless of shape the one on the right is kyle is segmented by shape instead of color but the one on the right looks completely random to our brain and this is actually what Where's Waldo leverages this idea of combining color and pattern together to trick your brain into not being able to find things so we played some games and I hope that the games just reinforced to you the sense that these things actually do matter that the colors that you choose the patterns that you choose the size that you apply in your vis all matter to your data visualization and they matter for two reasons the first is they can make it really quick and fast for you to find insights in your data but more importantly than that when you share your visualizations with someone else you want them to take away the same meaning that you found and if you've crossed the position and size and color and you don't put the right measures on the right items you're in you're emphasizing the wrong things to someone else and they're not going to understand what you're saying so there's actually a lot of pre-attentive attributes there are about ten that really matter so the first one is the length of a line this is position same thing with width width is also position the next one is orientation and then size shape enclosure the 2d difference so we saw that in that first example that we looked at where we looked at the the distribution of those statistically similar datasets right the 2d position was different grouping color and then intensity and intensity is sort of the light to dark shading that we saw so these pre-attentive attributes all have a best-practice associated with them some of them you can use to denote the order of things and for others they help you understand quantity and so we're gonna walk through those here really quickly so we're gonna look at size color intensity and color hue remember those are two different things orientation and shape so if you want to explain to someone quantity the only pre-attentive attribute you can use for someone to effectively understand is size so when I'm making a data visualization I choose I look at my my measures and I say what is sort of the most important numerical number for me to communicate and I start by putting that on size the next thing that you might want to look at is order or rank what is bigger or smaller what came first second third and you can use that on size or you can actually use that on both types of color the gradiation of color is important to help you understand the ordering of something the next thing is selection and and selection is is something that stands out from the rest of the group so say an outlier and for those you can use size if you haven't used it already color or the one new thing you can use for that is orientation and then finally Association Association is grouping does this belong with other things and so you can use any of them but if you've used all the rest of them before that's the one you use for shape that makes sense I see some pictures taking so I'm gonna hold off on forwarding this for a second the PowerPoint presentation will be available afterwards if you would like to have it up on the TC website so all for you taking pictures but if you want these slides because you want to reference them later and they will be available so there's actually an ordering in our brain of how important things are this is a much more detailed version of what I just showed you but what I'm trying to get at at some of these things quantitative things that right that's the the first one we talked about there is actually an order of importance in your brain that you rank things and you can see on the bottom that texture connection containment and shape actually don't apply to quantitative at all if I say a circle triangle and square you have no idea what is more or less than another right and so that applies to ordinal that rank too and then finally categorical I'm drawing your attention to the very last line on the this slide if you're sort of looking and trying to understand what I'm doing categorical means maybe furniture sales versus home office sales versus what's the last one in in superstore I'm blanking on it we've got a office supplies and I can't use something like volume to communicate that right I have to use something like color which is at the top of the list blue orange red so don't expect you to memorize this slide but what I want you to take away is there is an order of importance for these things when you're when you're messaging so this is the order color is more important position is most important shape is least and sizes less this isn't though a really effective way of communicating at this I could actually apply this best practice to this list so instead if I rank them I positioned them in order from most important at the top to least important at the bottom it's a little bit easier to understand position comes first then color then size then shape now how about if I add size to it starting to become a more more apparent that position is important and then if I apply intensity it gets an even stronger message and finally I'm going to add some color on top to denote position so if you take one thing away from today this is what I want you to take away that in our brains position is the strongest factor for us to understand data then color then size then shape so as you're building data visualizations think about position first color second size third and shape last tableau tries to do some of this heavy lifting for you so underneath tableau there are best practices that are already applied and these are the rules that power show me so you can see the VIS types on the left and there is a rule underneath so if we're looking at the horizontal bar there's one quantity element and so that is what tableau is going to show you if you have two quantities and one quality or two categorical information and one quantity element tableau is going to show you a stacked bar if you have one continuous date and one quantity you're gonna get a line chart and so forth and so on and so if you've ever noticed when you drag something out in tableau and it starts building stuff for you this is what's powering it underneath so when you start out that's really really helpful and then it gets annoying yeah everyone here experienced that where you drag something out new on the screen because you want to build something specifically and tableau just like goes and does its own thing the heck and that's because tableau is trying to apply one of these best practice rules on top I know it's annoying I wish there was like a way to go turn that off it would totally make my life easier and I bet it would make your guys's life easier but do know it's tableaus best intentions at heart when it does that it's not being glitchy it's not being strange it's not possessed by some dead relative it's like really trying to help you out with the best practices all right so we're going to go ahead and we're going to jump into tableau here in a minute because I want to talk with you about how you apply these things to tableau yourself so yeah everyone here has used desktop before yeah raise your hand some strong lines how about if you've been using desktop for less than three months raise your hand we got some pretty newbies welcome to the data family all right so if you will just do a quick overview of tableau and then we'll jump in so tableau has these shelves and you can drag a pill out onto a shelf and tableau will create a visualization for you so it's the premise of tableau and there are different places where you can look for position color size and shape so position is denoted up in the top with rows and call and color size and shape are all set on the marks card so let's jump over to tableau it opened up this visit earlier so now I gotta find it okay who remembers this viz from yesterday yeah so Ann told us yesterday in the opening keynote that she was afraid of aliens so I asked her if we could borrow this data set here so she's using color to denote a seasonality in this viz let's go ahead jump out of full screen mode here and let's go create a visualization together about UFO data so I know this is small up here but I'll try and talk you through it so when we create a visualization the first step that I always do is I choose the dimensions and measures that are most important to me so in this case I want to understand in what season winter spring summer fall had the most alien sightings or UFO sightings so I'm going to go ahead and click season hold down my control key and click number of record number of records here so I have two things highlighted if I go over to show me here tableau you can see is highlighting some of these visits and what tableau is saying is these are visits that match best practices so I want you to pay attention to what happens when I click on one of these visualizations I'm going to click on this a bar chart right here you guys see what happened I'm gonna undo it and we'll do it again tableau took these fields and put them out on these shelves so the number of records is on columns and season is on rows this is very dark we'll make that bigger for you guys so you can you can see it here right I got fall spring summer and winter here and I can very clearly see that summer is the longest bar chart Tablo was applying those rules of position first to this visualization okay now what sure what happens when I change this from a bar to a heat map in this visualization we're no longer looking at position we're looking at size okay and to achieve that you will notice that this number of records green pill is now over here on sighs if I want to get back to a bar chart I can take this pill and drag it back to columns and tableau will draw a bar chart again okay take this and drive it back and drop it on sighs and I'll get that heat map again okay do you guys see what's going on a pillow is an instruction for tableau on what to draw this is the second thing I want you to take away from today there's an order to things you can influence that order by where you put the pills in tableau so if we want to make this easier to see I can copy I'm holding down command on my Mac and I believe it is control on a PC I'm copying this field and this time I'm going to drop it on color do you did you see that slight shift difference the tableau made here I'm gonna undo it and redo it you see that like slight difference here some nodding other heads okay that's because tableau is applying a gradient from the least value to the biggest value okay and you can influence this gradient by clicking here in the menu and clicking on edit colors here and this brings up a whole menu so it makes sense that we can look at we're gonna come back to this menu in a second because sometimes this menu can be a little finicky okay I am going to go ahead this time and instead of putting number of records I'm gonna go ahead and copy the seasons and drive it and drop it on color this time and instead of using a gradient tableau is applying a different color to each of the seasons so that's a categorical color there are two types of color legends in tableau and you access the different types of color legends if you're using a green pill or a blue pill so a green pill will always give you a gradient a blue pill will always give you distinct colors tableau is applying best practices to the colors so this time I'm going to look at these colors here and you can see that there's a different set of colors being applied and tableau actually has a bunch of built in different colors here I really like new Nerello stone and and I think it's a beautiful color palette here let's go ahead and apply it here and but one of the things that I love about this palette is this palette is named after our researcher who specializes in color at table and so all of the color palettes that are designed and set in tableau are designed to have the biggest visual differences between the colors so it's really easy for your brain to comprehend the different colors there's about 20 different shades that your brain can very quickly pick out your brain can actually tell apart about a million different colors if you put them side-by-side but when you want quick and ease of use there's about 20 colors that your brain understands um and those are called the tableau 20 there are ten main colors with a hue difference from dark blue to light blue okay and so what I recommend is all of these color palettes are really great for you to use because you have the confidence of knowing that your end user will be able to tell those colors apart really well so let's go back to that gradient color I'm going to go ahead and take number of records drop it on color this time and I have now that gradient again you also have control over that gradient if you go into edit colors here and tableau again has different gradients that you can use what I like to do I'd like to do two different things when I used these pallets I actually like to use stepped color stuck color takes and segments the gradients to help me see groupings a little better so I can layer on Association on top and then I like to use the advanced feature down here this allows me to control where the color starts and where the color ends so if I want to say make these cut up colors stand out a little bit more I can go ahead and say well anything that's maybe over a thousand I want to be the same color here and I can affect the color and you can sort of control the color that way does that make sense all right so we talked about position being on the XY axis we talked about size we talked about color the last one is shape so shape is hidden we hide it because we don't want you to use it a lot that is because shape is the hardest for our brains to understand so shape is hidden on the drop-down menu on the marks card and when you get to when you are on shape there's a new selector here okay and if I click shape and more shapes I can go in and affect this so this time let's go ahead and put season fall spring summer or winter on my shape and tableau just applying random shapes to us but there's a whole menu so let's go ahead and use filled because they're easy to see here and tell tableau to assign a palette shapes are hard because our brain doesn't have any association with them but that's why they're the hardest thing and so often what you see in a data visualization you might see a scatter plot that has like 27 different shapes on it and your brain really can't come pretend what's going on okay so we recommend use shapes sparingly use shapes for emphasis of something and often use shapes too just to note one difference or one change okay so let's go ahead and now apply these together to answer a question so I want to answer the question of our alien invasions increasing or not that was the question that Ann had so let's go ahead and look at a number of Records date and season altogether okay I'm going to look here and I'm going to go ahead and pick my bar chart and see what happens [Music] let's go ahead and format this you guys can see it um and so Tablo defaulted I'm gonna go ahead and hide these nulls for you guys there you go so we can look at this data and what we are seeing go ahead and make that black and bigger for you we are looking at year-over-year trends between 2018 and 2019 and this isn't a full data set it only goes about back about 18 months and this is actually you can see position wise is really hard for our brain to comprehend even though there's lines between fall and spring I can sort of tell that they are longer but is much easier for our brain if we go ahead and move here under season and now my brain is able to understand position by drawing a vertical line and I can now really easily tell that 2018 is hot lower than 2019 does anyone know why our brain is really good about drying vertical lines any guesses what horizon that's an actual I've actually not heard that one as many times if I have asked it's really interesting any other ideas here's the hint you've been training your brain since you were about five years old reading so our brain is really really good at drawing vertical lines because when we are reading we read over and then we come back to the same spot to Reena again and so every book in line you've read from see spot run until now has been training your brain to strengthen the muscles to tell the difference between two vertical places and so and in other cultures in China in particular they're actually much stronger than Americans in vertical lines because their traditional language runs vertically and they've actually been training their brain to run vertically in some cultures like Arabic where they write from right to left they're actually stronger at drawing lines the other direction so in America we are really good drawing them horizontally and China there they're really good at drawing them vertically and so we can go ahead now if we want to tell our story and apply this to color further we're making a stronger case and then I can apply it to size as well does anyone know why size is really hard for our brain it's relative yeah it's the reason why we don't like pie charts around here I mean we like pie we just don't like pie charts and that's because it's really really hard for your brain to calculate area you can sort of tell the relative nough some but you can't understand the deep the the deep differences so you can tell like yeah they're sort of in the similar ballpark but you can't tell much more beyond that all right so I'm gonna jump back to PowerPoint here there are some special things I love this about area so this is a map of Europe in the Middle East and it is being colored by GDP spending position geography is actually a position it's in coding context and now we are applying color to our quantity so it's an interesting visualization what what might you assume and take away based on this visualization that the Middle East spends more money on there I'm sorry this is a share of military spending on GDP left that fact out that's maybe helpful what might you take away then knowing that the color denotes especially yellow denotes share of GDP spending yeah based on this map it actually seems like the middle-east spends a lot right on military spending but in fact they spend far less than Europe does right so what I put on sighs here is the the absolute amount that is spent so when we look at these two visualizations side-by-side they're actually telling someone a different message and so when you use size it's really important to understand that that that the size of the country is actually lending more information into the story than maybe you intend so this is something to be aware about especially in tableau we use a type of map that maybe isn't the best in sharing area and so on this is Texas down here and this is Texas in Greenland and so when you are looking at geographic information particularly within the world you need to pay attention to make sure that the size of the country and the type of map meet being used isn't shifting the analysis and the story that you want to tell so that is the one thing that you really need to pay attention to when using maps I was going to talk about another special thing of position so who was in deaths on stage this morning some hands oh and who watched it online were there more hands and the rest of you just were out playing craps really late last night that well no I'm like I'm sort of excited because I get to share something with you that a bunch of you maybe don't know so this morning tableau released a new feature it's a really awesome feature its marked animation so in this viz this is a viz of us music revenue by format so 8-track tapes on the bottom CDs over the last 40 years CDs have far outsold cassettes vinyl digital and streaming but if I start removing the decades we can watch as streaming moves from the bottom up to the top so there's 80s gone now we're just looking at the 2000s 2010 to present so animations are a special type of position they allow a relative miss but we know points of time I'll show you another one here and this is maybe the best visualization that I think we made for for devs on stage here so this is a recreation of hands Roslin's Gapminder and pay attention to the red dot of iran over time each of the different continents is denoted by a different color and what's happening is the average family size is on the bottom and the average life expectancy is on the y-axis and what you can actually see is as the average family size decreases life inspectin C actually goes up these these are correlated measures and you can actually watch what happens to Iran specifically and so this visualization is great I'm actually going to pause it here let's see if I can pause it well we'll just move here because we need to use animation sparingly the one thing to remember about animations is we are very sensitive to movement and so if I keep playing this animation you will not listen to me you can literally not hear what I'm saying and so it's really good on animations to animate and then stop because it is so powerful more power then position size color shape well I guess is a type of position but the in a moment position that it will overpower every other message you are trying to say because we are so fascinated and that's because I think we're trying to understand if there is a threat happening to us movement used to mean a threat to us it's when you're in a restaurant and someone like walks in you're like oh what's going on what's going on what's over there my really annoys my husband he's in the room somewhere it's all my brain it's not me I promise Hans Rosling is probably the person who made data visualization famous if you haven't read this book tactfulness I would highly highly recommend it so we just have a couple minutes left I know we went over so you guys mind stay in just a couple minutes um what I want to tell you is there's a difference between function and form function is about speed and accuracy form is about aesthetics sometimes in beautiful in visualization we confuse these two things we in the effort of trying to have form we lose what message we're trying to say I think that we have come really far I think maybe Apple is the best example of someone who's taken function and form and brought them together so we've talked about color we've talked about position we talked about size we've talked about shape I'm going to go ahead and look at the iron visit and then give you an opportunity to vote on who you think is the best practice and we'll talk about them together so this is Joshua's example here he looked at the taste of America and he yep it did not update did it do go and so this was Joshua's example of the taste of America and Joshua's premise was he used color really well he actually got asked about this about why he used blue and defaults on the left who remembers his answer yeah cuz tab was done the science for him about what's best but he also used blue on right hand side and I think that was confusing to a lot of people because we have to be careful not to use the same color to denote different things because our brain is applying categorical information to it and say blue and blue those must be the same things even though in this visualization the blue on the left and the blue on the right are different things same thing on the top he has orange and red but he's using it in a different way on that that bottom map what is cool what I think he did really well in this visualization is that map in the bottom right hand corner he's getting around the whole states have a different geographic sizes by geographically showing where they're at but representing them by the same size box okay and so I think he did a really really great job at that I think this visualization in the bottom is probably the best part of his biz okay and in fact there's something that maybe you didn't see before was this line here where he's actually taking each state and showing the position of it it's relative Ness and I thought that was really cool and then he went and he switched over his map and he said what's missing there is data and that is not here there are countries that are just not represented at all he said something like of all of the African cuisine out there in the United States something like 85 percent of it is just categorized by Africa even though there are some 7080 state countries in Africa and so he was making this case and using color really effectively to show what is missing Lindsay took Kellie Martin's approach to data and data visualization she used color to denote the same categorical information across all of her visits right so subway is represented pink and so it's really clear on this line graph here that this line is subway and I can tell that 7-eleven is represented in orange down here one of the things that I think Kelly could have done better if she could have better leverage position it's really hard on these upper visualizations to tell the relative nosov how subway compares over zip codes locations and population represented and so if maybe she had stacked these on top of each other we could have gotten more insights from the data finally Hisham made this visualization he chose to use two colors a red and a yellow to denote diverse cuisine versus traditional cuisine traditional cuisine was when over 50% of a country's cuisine was represented by their own cuisine somewhere like Greece most of their food is Greek where in the United States most of our food is from another country actually over 50% of our restaurants in the United States are Mexican restaurants that was really really interesting and he's using that red and yellow across the visualization and even though he has red and yellow on the map on the left the position of his bars down here make it very clear to a user not to be confused about the size representation here and then he has gone ahead and combined a bar graph showing position with another level of data here is each of the cuisines and I'm actually going to switch over to the visit self so you can see how it works so if I select a country like the United States the map will update I can see just the United States here and I can see in fact a Mexican has the most cuisine so I'm gonna go ahead and I'm going to put a URL up I want you to go ahead and vote and we'll actually crown and they will get an additional small trophy as the best practice vis from this group so let me go ahead and put that up for you guys here so go ahead and if you text TC 19 2 2 2 3 3 3 you can go ahead and vote on who you think had the best practices and as it comes in here we should you should be able to vote a for the black and white viz be for Lindsey's vis and c4 he shuns vis and then if you didn't know our iron vis Championship yesterday resulted in a tie and some of you might have some questions about that it actually turned out that they were within five decimal places of the same answer it was a dead heat between the two so one scored a little higher with judges the other scored higher with the Twitter vote and it came out to a dead tie so we can maybe break the tie a little and so the votes are still coming in but it's it's starting to look pretty apparent that we do have a best practices winner I would agree with you all that C was the one that used best practices to the best thank you for joining us today I hope you have a great rest of the conference [Applause]

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Keywords: Visual data, Visual analytics, Business analysis, Business analytics, Business analysis tool, Data analytics tool, Data Analytics, Analytics, Analytics platform, Cloud application, Business analytics platform, data analysis, data visualization, business dashboards, business intelligence, tableau, tableau software

Id: OhjoCbVxHDU

Length: 54min 9sec (3249 seconds)

Published: Fri Nov 15 2019