 Welcome to Using Tableau to Visualize Data, part of the research and assessment cycle toolkit project offered by the Association of Research Libraries and made possible by a grant from the U.S. Institute of Museum and Library Services. This presentation, which is part of a module that focuses on organizing and analyzing data, provides a brief introduction about using Tableau for data visualization. We hope the content is useful to library practitioners seeking to conduct assessment projects. At the close of the presentation, you'll find a link to a feedback form. Please let us know what elements were useful to you. This presentation will provide a basic overview of Tableau, what it is, how it can be helpful, and then with some explanations and demonstrations, I'll share some basic steps for connecting data, describe the key features, demonstrate how to create some simple visualizations with filters, and then combine visualizations into interactive dashboards that can be shared with others. If you'd like to follow along with the demonstrations on your own computer, please download the Excel file using Tableau to visualize data that is available with the module materials. You will also need to have Tableau downloaded to your computer. To download a free seven day trial version, visit Tableau.com. Tableau is a data visualization and analysis tool that allows you to easily create interactive visualizations and has a very low learning curve for getting started. Tableau enables you to create dashboards that contain multiple visuals on a single screen. You and your viewers can then apply filters for categorical variables in your data set that allow you to identify trends and nuances in your data. Tableau desktop creator license is needed to take advantage of the full functionality of the Tableau tool. You can try it out for seven days. And there's also a free Tableau app that allows you to create visualizations, though the ability to share your work is limited to doing so on the Tableau public server only. Finally, Tableau allows students to download a 12 month license for free. Tableau allows you to go from a cleaned data source to interactive visualizations. For example, what you see on the left of the screen is a screenshot of an Excel file with library checkout data that was downloaded from Primo, a library integrated system. And there you can create, you can connect your data to Tableau and then create visualizations, such as this dashboard dashboard in a matter of minutes. To use Tableau, you will need to connect to a cleaned data source. If this is a new concept to you, I recommend watching the video video cleaning and organizing data that is part of the same module cleaning and analyzing data in the same training series. In other words, to get started, Tableau requires a connection to a data set rather than being a data set in and of itself. There are many different file types that you can connect to Tableau as shown here on this screen. You can connect to a traditional spreadsheet, statistical file, or a database file such as Excel, SPSS, or Microsoft Access. You can also connect to data that is stored on a server, such as a Microsoft SQL server or a MySQL server. Finally, you can connect to cloud-based data files that may be stored in Box, Dropbox, or Google. In my own work, I most often connect to Excel or Google Sheet files, Google Analytics, or data stored on my organization's MySQL server. For the demonstrations in this video presentation, I'll first connect to an Excel file with library checkout data, create a few visualizations, and then create an interactive dashboard that can be shared with others. Once you connect your data file, you'll see a mirror version of that data source on your screen. You can also connect several files together, so long as they each have a key identifier that can be used to link your files or database tables together. Once you have your data connected, then it's time to open a worksheet and begin creating your first visualization, which requires some familiarity with basic features and terminology specific to Tableau. Visualizations are created in Tableau worksheets. Each visualization will require its own worksheet. The first thing to take note of is the section called Tables. In this area, the fields or the columns in your Excel worksheet are organized into dimensions and measures. Dimensions are most typically qualitative values that are fields that can be used to categorize or segment data. This often includes demographic data, names, dates, or geographic data. Measures contain the numeric quantitative values that can be measured, calculated, aggregated in some way that may result in a sum or an average. Think of the measures as data that can be collected, counted, calculated, or combined in some way to return a single value. In research terminology, you can also think of dimensions as independent variables in measures as your independent variables. So in this screenshot, the dimensions are things like academic year, borrower category, the date, timestamps, etc. The default measure is typically counts. Sometimes Tableau's default sorting of fields into dimensions and measures might be off a little bit, such as the case of the item barcode. Because the barcode came through in a numeric format, Tableau automatically judged it to be a measure or something that we would calculate when in fact it is a dimension, a representation of a specific item that was checked out. This is a simple adjustment. You can simply drag that field up into dimensions and you'll be all set. Every visualization will need at least one measure and either a dimension or a date. The other key features you'll need to create visualizations are rows and columns. You don't always have to have both rows and columns in play at the same time, but you'll need at least one or the other. To get started, you simply drag your fields of interest up into the rows and columns space. If you don't like a particular format, the fields can be easily moved around. The real magic happens in Tableau once you create some simple visualizations and then add filters. In this screenshot, we're looking at a simple visualization of the number of checkouts in the data set that occurred based on a day of week. You can see we use the event date time field and put it into the column section to narrow down the data to day of week. You can also use this same field to select year, quarters, months, weeks, specific dates of a month, hours and more. On the right highlighted in red, you can also see different filters that I added including academic year, term, month, hour and hour category. And then in the upper right corner of your screen, you can also see the show me icon. Clicking on the show me icon opens up a dropdown menu that allows you to see the different types of graphics you can create with your selected dimensions and measures. Options that are grayed out are visualizations that won't work unless you add more or different dimensions or measures. A few of the options that would work nicely to visualize checkouts by day of week formats are on the right side of the screen including text tables, highlight tables, tree maps, pie charts, bar graphs or packed bubbles. So now with that basic overview in mind, let's first take a look at the Excel file we want to visualize to understand what we're working with. So this is the sample Excel file that you can find with your module materials. You can see we have just a few columns or fields we have our date time stamps which include year, month, day, hours, minutes and seconds, our borrower category. Then for the specific items we have a barcode, a title, and a call number, and a format, shelving location. And then finally these final two categories are term and academic year, and those really are associated with the event date time. Just new fields were created by me when I cleaned the data set so that I would be able to filter or organize the data in ways that made sense to me. We'll be connecting our Tableau file to this Excel data file. You don't need to keep your Excel file or your data source open. I just simply wanted to give you a quick peek at what it looks like. So I'm going to go ahead and close this for now. And now I'm going to open up Tableau. And we'll connect to the Library Checkouts Excel file which is very simple to do. This is just the first screen once I open up Tableau. And I'm going to under connect. I'm just simply going to say to a file Microsoft Excel. And now I'm going to find the location where that file is stored. I happen to store mine on the desktop. So I'm just going to click it and say open. And now what you see on the screen is a mirror copy of that Excel file, though we're looking at it in Tableau. So our data files are now connected. Now that the data are connected, let's go ahead and create a simple visualization by clicking on sheet one down here at the bottom of the screen. Take a look at the dimensions and measures. As I said earlier, the item barcode really is a dimension, not a measure. So I'm just going to simply slide that up there up into the dimensions section. So now it's a dimension. So as simple as that. Let's create a bar chart based on checkouts by day of the week. So that's to do that is really quite simple. The first thing I'm going to do is day of the week comes from the date time stamp. So I'm just going to pull this up under columns, just dragging it over. And the default is year, but to change that to other options related to time. I'm just going to click on this downward carrot. And I am going to go slide down here under more, and I'm going to select weekday. So now you see we have weekdays displayed here across the top of our screen. And I'm going to under the measures. They have the little there in green, I'm going to bring up checkout data and slide that under rows. And the actualization that automatically popped into our screen as a line graph. But let's say we wanted that vertical bar chart instead. Under show me the closest thing to the vertical bar chart is the horizontal bars. So let's go ahead and click on that. We can easily, you know, the horizontal bars may perfectly suit your needs but if we wanted them to be vertical bars. So let's go up here to this transpose icon and swap our rows for columns. Just click. And so now we have our days of the week, cross the bottom of the screen and the counts on the vertical axis. So that's looking pretty good. We can increase the font size across all of our tableau work, which I think, you know, the default is always size font size nine, which I always think is a little small. So I'm just going to go to format. And I'm going to format the whole workbook. And I'm going to go to. This is just different. Tableau fonts. I'm going to make the font black. And I'm going to increase the font size to 10. That's just a matter of personal preference. We can change the, if we didn't want to spell off the entire days of the week, we wanted to abbreviate them to save some space. We could simply just right click over any given day of the week at the bottom of the screen and say format. And then over on the left is the format window where it says date Sunday. I'm just going to click and say abbreviation. And so now down on the bottom you see we just have the three day abbreviation. Let's go ahead and give this a meaningful title. So where it says sheet one, I'm just going to double click there and say checkouts by day of week. You can adjust the font if you wish. I'm also down on the bottom I'm going to change that where it says sheet one to day of week also. This is just something that'll help you once you get to the point of creating your dashboards just having some your worksheet tabs to have some names. We can add a couple of filters for good measure. So let's go ahead and do that. Let's, I'm going to click this format. I'm going to close this format box over here on the left, which gets suspect to our tables and dimension. So let's say we wanted to have a filter for year and a filter for month. To do that we're going to use that date time stamp. We're going to click that downward carrot carrot and say show filter. So now you see we have filters here and also shows up over here on the right. And this is on the right is where I'm going to spend most of my time formatting and adjusting. So I'm just going to simply click this downward carrot. I want this to be a dropdown option where my users can pick multiple values. And then I'm just going to edit the title to just be here, just trying to keep things as simple as possible. So it's not to overwhelm our viewers. I'm going to add another filter for month. So I'm going to use that same date time field. And we're just going to add another option for months. This time I'm going to drag date time over into the filter section and select months. And I'm going to say we want the default to just be everything all options. These happen to be the months that are in their data set. And then I'm going to show that filter. I'm going to just do some quick modifications to make it look nice. If you want to reorder your filters into a particular order, you just can drag those fields up and down. Let's add two more filters. Let's do the borrower category. And I'm just making it a dropdown list. Maybe I want to adjust this just to be borrower category. And then maybe let's add one final filter for format. And maybe I just wanted to shorten that title as well. So now we have a simple visualization if we want to filter and only look at particular like transactions that happened in 2020 versus 2021. We could do that. We could see what the trends look like for our faculty. Faculty coming in Tuesdays that looks like Tuesdays and Thursdays. If we wanted to look at the seniors, they come in on Mondays and Tuesdays, etc. So we have a simple visualization for checkouts by day of the week. Let's create two more simple little visualizations and then we'll bring them all into a dashboard. This time let's create a visualization based on borrower type and the number of checkouts. So I'm going to just click on another worksheet down at the bottom. New worksheet. I'm just going to call it borrower type here. Just double clicked and gave it a name. And this time let's create a table that shows the counts of loans to each borrower type and then the percentage of total. So this time I'm not going to worry so much about filters. So long as we have one visualization that has the filters for a set that we want to combine into a dashboard, we only only one of the business needs to have the filters. I'll show you what I mean shortly. So let's work on. Let's give it a table to help us keep track of what we're doing checkouts by borrower type. All right, so let's drag event borrower category to columns like so. Let's drag counts up to rows. And you can see the default here was bar charts don't worry about that quite yet. Let's drag. So we have the counts, but let's try count this checkout count data up here again. And we're going to create, we're going to turn one of these into percent of total so we're going to have a basic count here and we're going to have percent of total for the other. So the second one. We want to change that. So let's just go and click on that downward Carol carrot quick table calculation and percent of total. So now let's go ahead and change this visualization to a simple table. Sometimes tables are are the most optimal. So I went to show me and clicked on the icon that looked like a table. We have a simple table. We have our event borrower categories are percents of total and then the counts. So we're looking pretty good just need to make a few little cosmetic adjustments to aid our viewers make things a little easier for them. The first thing we can do is go to analytics, click on totals, and we're going to add a grand total at the bottom. So now at the bottom you can see that there are 6651 checkouts, and then the percents of total. So each category, the checkouts has a percent of total. If you wanted to change the percent of total and move it over. I'm just clicked on it and dragged it. Just very simple. And maybe I want to change these headers just to shorten up the titles a little I can do that by right clicking and clicking alias. And I'm just going to say count here, just try to minimize some of the visual clutter. And then I'm going to do the same thing right clicking at an alias percent of total. If we wanted to reduce the number of decimal points. We could just hover over one of these figures right click. Save format. Now over here under format font, we could click fields. Select percent of total. It's a percentage. And we want to reduce that to one. If you so right now all of the different borrower category types are listed alphabetically. If you, if there were some particular fields that you just didn't really want to see you could like maybe retirees or cooperative borrowers, you could just right click on any of those. And you could select exclude which is going to exclude them from the entire analysis of this biz, or you could hide them. So if you exclude them, the number, numbers in the totals will be reduced by that. If you're in that data set, or if you hide them, the totals remain the same to just start aren't shown on your screen. I'm going to just go ahead and remove a couple of these that are perhaps of less interest. If you wanted to reorder the names of these fields, maybe you want it to be like this, the freshman, sophomore, juniors, seniors, let's see, let's do grad students, faculty and staff. And then maybe you're a little less interested in some of these other ones I'm going to go ahead and exclude the friends of the library borrowers. I'm going to actually move up early college and distance learning students. So I feel pretty good about that. Let's create one simple last visualization. I'm going to click one last time on new worksheet. Time. Let's do formats. Let's create a packed bubble chart related to format. Very, very easy to do. We are just going to drag up item format to columns counts under rows. Now let's go over to show me and select packed bubbles. Here you can see just gives you read relative sizes so you can see that we have way more books that were checked out compared to visual materials, and this little orange circle is music so not too many checkouts related to music. And I'm just going to say checkouts by item format. So now we have three visualizations. I'm just going to click on labels under marks. I'm going to click on label and say show mark label. And with that in mind, perhaps we don't need this vertical axis anymore. I'm just going to say the select show header. Again, I'm just trying to minimize as much visual clutter as possible. So I'm just hiding some of these things that are maybe obvious and we don't need to have labels for them. Let's return back to our slides for just a moment or two. Once you have a few visualizations that you think make sense to be displayed together on a single screen, you can then create a dashboard. Kind of like the dashboard in your car so you can see multiple things at once. On this slide, you can see I created six different visualizations. Six was more than I wanted to look at it a single time on a dashboard so I elected to create two dashboards I would only be looking at one dashboard at a time. Both of these dashboards are in the same tableau file just will be displayed differently upon clicks. You can set the dashboard so that the filters will apply to all of the visualizations that are displayed. And creating the dashboard and adjusting the filter settings is very simple and I'll show you how. So I'm going to return back to our tableau file. And this time I'm going to select the icon at the bottom of the screen that kind of looks like a window pane that says new dashboard and over on the left. These are the three different worksheets that we have to choose from if we had more worksheets that we created, we could select those that were of interest to us. So I'm just going to over on the left under sheets, I'm just going to drag each sheet over into the active pane. And then we can rearrange as we feel make sense to us. So here I have the day of the week displayed in bars I have the checkouts by borrower type down here in the left, and then I have the formats. I'm actually quite satisfied with that but if I wanted to move things around I certainly could. I could just clicking or clicking on this little visual and just moving it over, or I could move it up, etc. I could create a little separation borders between each of the visuals, so they don't all appear to run together. It's a matter of personal taste I'm just going to do that by clicking on each visual at a time. Then on the left I'm going to select layout and add a border. Maybe I wanted to add a background color. This kind of gives it again a little more visual separation and doing the same thing for each of these other visual visualizations. One more time. And then I can this one already if you wanted to this one already fits the width here and the height. So I just click this downward Carol carrot and said fit entire view. We can do the same for bubbles and our table. This, this little legend goes to this visual so I'm actually going to slide this over so that things will be kind of side by side with each other. And I want this legend to be more in line with this particular visualization. So I'm going to add a little empty space here. Just going to go to dashboard. Down towards the bottom and going to select blank. And I just added a big blank space. A couple of last things right now the filters only apply to this bar chart. We want them to apply to everything on our screen. So I'm just going to make some simple adjustments here for each filter. I'm going to select the downward carrot, say apply to worksheets. It says right now only this worksheet. But we want to have them apply to all worksheets on the dashboard. So activating the filter downward carrot, apply to worksheets, selected worksheets and all on dashboard. Two more times. So now you can just check things I like to check every filter to make sure I haven't missed anything. So here, nothing is selected. If we wanted 2020 to be selected, or all, this is what we want to be happening. So maybe we want to just see what happened in December or November or maybe everything. We want to look at behavior for particular groups. We could do that. You can see faculty mostly are checking out books. Whereas seniors is a little more balanced here between books and visual materials. And then format, if we just want to look at behavior, comparative behavior for books or music, let's see who checks out the music. Mostly staff or visual materials that could be we have a lot of DVDs, for example. So now we have a nice tiny little dashboard. If you wanted to take a look to see how that would display when it's published, you could go to window and select presentation mode. That eliminates all of the Tableau creation clutter. Everything still works. I'm just going to escape. And then if you wanted to publish it so that it could be shared with others, you could publish it depending upon your preferences. I'm going to return back to the slides to finish up the presentation. Once you feel pretty confident about how things look and work, then it's time to share your dashboards with others so they too can interact with your data. Once you publish your data, and if you want to make any adjustments, you can always go back and make those adjustments republish and then reshare. There are four primary ways that you can share your Tableau dashboards. The most popular and easiest thing to do is publish to Tableau public under your profile. If you do this, be sure your visualization visualizations don't include personally identifiable or sensitive data. Posting to Tableau public will give you a URL that you can share so that anyone you wish may interact with the dashboard. You can put many of our libraries dashboards on Tableau public and then share the link with the entire library team or those who who may find it beneficial so they can explore the nuances in the data on their own. If you don't want to make your dashboard publicly available, you can share access to colleagues who may have a Tableau viewer license. Tableau viewer license carries a monthly fee but allows you to easily share visualization files with select others who have that license. Our library dean and associate deans have Tableau viewer licenses and I often share internal budget dashboards or things related to personnel to those select individuals. I often share a full Tableau workbook files with others to have Tableau creator licenses so they can work on the same files. In this case, you both need to have the creator license to interact with and edit the files. And finally, many organizations pay for a Tableau server. This is the most secure option for organizations. An institution's server will most likely be password protected and may be limited to senior administrators and assessment and data analysts. Costs for the servers is dependent upon core licensing agreements. So to recap Tableau is a wonderful tool for creating visualizations that allow you to create and share interactive visualizations with others. Using visualizations and dashboards with easy to use filters facilitates data exploration in important and nuanced ways. For Tableau to work, it will require a connection to a data source. This could be as simple as an Excel or Google Sheets file or a statistical data file or data that's stored on a server. Visualizations will require both a dimension or a date time field and a measure. Several visualizations can be combined into a single dashboard so you can see the data displayed in several ways at a single time. And then filters can be adjusted so that they apply to all of your visualizations on a single dashboard. And remember, there are many ways that your dashboards can be shared with the most common being via Tableau public, which enables you to share a simple link that anyone can use to interact with your data. And does not require a license. Thank you for viewing this presentation on using Tableau to visualize data. Please use the link provided to complete a feedback form for the usefulness of this information for your purposes. Thank you.