WEBVTT 00:00:00.000 --> 00:00:00.499 align:middle line:90% 00:00:00.499 --> 00:00:03.000 align:middle line:90% Welcome to Getting Started with Tableau. 00:00:03.000 --> 00:00:09.560 align:middle line:84% You can download the data sets to follow along in your own copy of Tableau. 00:00:09.560 --> 00:00:11.210 align:middle line:90% This is the start screen. 00:00:11.210 --> 00:00:16.910 align:middle line:84% Here, we can connect to new data, connect to saved data sources, 00:00:16.910 --> 00:00:20.960 align:middle line:90% or open recently used workbooks. 00:00:20.960 --> 00:00:24.720 align:middle line:84% In the Connect pane, we can see the wide variety of data sources 00:00:24.720 --> 00:00:27.820 align:middle line:90% Tableau connects to natively. 00:00:27.820 --> 00:00:31.890 align:middle line:84% For this video, we’ll connect to the global Superstore data available 00:00:31.890 --> 00:00:33.490 align:middle line:90% for download. 00:00:33.490 --> 00:00:38.410 align:middle line:84% The Superstore data is an Excel file that looks like this. 00:00:38.410 --> 00:00:41.310 align:middle line:84% The data is shaped like a database table: 00:00:41.310 --> 00:00:44.480 align:middle line:84% The first row contains the column headers. 00:00:44.480 --> 00:00:51.430 align:middle line:84% This data set contains transactions of customers purchasing specific products. 00:00:51.430 --> 00:00:56.340 align:middle line:84% Let’s go back to Tableau Desktop…and choose connect to Excel. 00:00:56.340 --> 00:00:58.400 align:middle line:90% Navigate to the file on 00:00:58.400 --> 00:01:02.540 align:middle line:84% your machine and double click to open it. 00:01:02.540 --> 00:01:04.670 align:middle line:90% Now we’re on the Data Source Page. 00:01:04.670 --> 00:01:09.040 align:middle line:84% From here, we can choose which sheets or tables we’d like to use. 00:01:09.040 --> 00:01:11.435 align:middle line:90% We can drag Orders to the canvas. 00:01:11.435 --> 00:01:14.310 align:middle line:90% 00:01:14.310 --> 00:01:17.470 align:middle line:84% If we want to bring out more information from the same data source, 00:01:17.470 --> 00:01:22.490 align:middle line:84% we simply drag the other table onto the canvas. 00:01:22.490 --> 00:01:27.410 align:middle line:84% Alternatively, if we have related data in another data source, 00:01:27.410 --> 00:01:31.250 align:middle line:84% we can create an integrated data source by adding a connection, 00:01:31.250 --> 00:01:37.910 align:middle line:84% by clicking Add, here we’ll bring in a Text file of our returned orders, 00:01:37.910 --> 00:01:42.990 align:middle line:84% stored as a csv (this file is also available for download). 00:01:42.990 --> 00:01:46.630 align:middle line:84% The sheet has automatically been added to the canvas, 00:01:46.630 --> 00:01:50.520 align:middle line:84% and here we can see our cross-database join. 00:01:50.520 --> 00:01:53.200 align:middle line:84% We’re using flat files so you can follow along, 00:01:53.200 --> 00:01:55.900 align:middle line:84% but this could be a join on data from, say, 00:01:55.900 --> 00:02:02.430 align:middle line:84% Hadoop and Redshift—cross-database joins are extremely powerful. 00:02:02.430 --> 00:02:06.720 align:middle line:84% Tableau Desktop automatically creates a default join as we can see in the icon 00:02:06.720 --> 00:02:07.590 align:middle line:90% here. 00:02:07.590 --> 00:02:10.870 align:middle line:84% Clicking on the icon brings up the details of the join, 00:02:10.870 --> 00:02:13.690 align:middle line:90% and we can edit it directly. 00:02:13.690 --> 00:02:18.380 align:middle line:84% We’ll chose a left join, so we get all the information from the Orders table, 00:02:18.380 --> 00:02:22.940 align:middle line:84% and only bring in relevant Returns information for transactions that were 00:02:22.940 --> 00:02:23.950 align:middle line:90% returned. 00:02:23.950 --> 00:02:27.190 align:middle line:84% It’s already based on order ID as the join clause, 00:02:27.190 --> 00:02:31.080 align:middle line:90% but we could change this if desired. 00:02:31.080 --> 00:02:35.440 align:middle line:84% The grid, below, allows us to verify what data we have—we can see we have 00:02:35.440 --> 00:02:39.250 align:middle line:84% a lot of nulls from the returns database in yellow (which is great, 00:02:39.250 --> 00:02:44.710 align:middle line:84% we don’t like returns!), and all our orders information is here in blue. 00:02:44.710 --> 00:02:48.240 align:middle line:84% In this grid view, we can do some basic metadata management. 00:02:48.240 --> 00:02:54.740 align:middle line:84% We can change Row ID from a number to a string just by clicking the icon. 00:02:54.740 --> 00:03:00.980 align:middle line:84% The Order ID field in this dataset has multiple parts, the distribution center 00:03:00.980 --> 00:03:04.780 align:middle line:84% code, the year, and two additional codes. 00:03:04.780 --> 00:03:09.120 align:middle line:84% If we want to split this field and keep only the distribution center code, 00:03:09.120 --> 00:03:15.120 align:middle line:84% it’s easy – just click on the drop-down and select Custom Split. 00:03:15.120 --> 00:03:19.840 align:middle line:84% We’ll split on a hyphen, and just keep the first column. 00:03:19.840 --> 00:03:22.950 align:middle line:90% 00:03:22.950 --> 00:03:25.940 align:middle line:84% Let’s rename this field “Distribution Center”. 00:03:25.940 --> 00:03:28.980 align:middle line:90% 00:03:28.980 --> 00:03:33.840 align:middle line:84% Next, we can decide if we’d like to connect live to the data or extract it. 00:03:33.840 --> 00:03:38.750 align:middle line:84% Connecting live is great when we have constantly changing data or when we 00:03:38.750 --> 00:03:42.980 align:middle line:84% want to leverage the high performance database we’re connected to. 00:03:42.980 --> 00:03:47.400 align:middle line:84% Alternatively, we may choose to import data into Tableau’s fast data engine 00:03:47.400 --> 00:03:48.840 align:middle line:90% with an extract. 00:03:48.840 --> 00:03:53.310 align:middle line:84% This takes the data offline, and allows us to minimize performance impact 00:03:53.310 --> 00:03:57.980 align:middle line:84% critical systems, while still allowing for regular, scheduled refreshes 00:03:57.980 --> 00:04:00.790 align:middle line:90% to keep the data up to date. 00:04:00.790 --> 00:04:06.570 align:middle line:84% We’ll connect live and click on our sheet tab down here at the bottom. 00:04:06.570 --> 00:04:08.660 align:middle line:90% We’re now connected to that data set. 00:04:08.660 --> 00:04:11.960 align:middle line:84% Let’s see how easy it is to dive into our data. 00:04:11.960 --> 00:04:20.519 align:middle line:84% We simply drag the fields out, let’s bring: Category to rows, 00:04:20.519 --> 00:04:30.190 align:middle line:84% Segment to rows, Quantity to columns, Market to columns, 00:04:30.190 --> 00:04:32.640 align:middle line:84% and let’s bring Market to color, as well. 00:04:32.640 --> 00:04:37.150 align:middle line:84% It’s that easy to create a visualization of how our Sales are looking per 00:04:37.150 --> 00:04:42.500 align:middle line:84% category, customer segment and market, in terms of number of items sold. 00:04:42.500 --> 00:04:47.395 align:middle line:84% We can quickly see that Africa is an emerging market for us. 00:04:47.395 --> 00:04:50.270 align:middle line:84% You’ll notice that I brought in those fields from this data pane here 00:04:50.270 --> 00:04:51.330 align:middle line:90% on the left. 00:04:51.330 --> 00:04:55.670 align:middle line:84% It’s broken up into dimensions and measures that represent the column 00:04:55.670 --> 00:04:57.750 align:middle line:90% headers in the excel sheet. 00:04:57.750 --> 00:05:00.520 align:middle line:90% What are dimensions and measures? 00:05:00.520 --> 00:05:04.700 align:middle line:84% Dimensions are categorical fields, in this case, fields 00:05:04.700 --> 00:05:07.920 align:middle line:90% such as date, customer, and Category. 00:05:07.920 --> 00:05:11.860 align:middle line:84% These are fields that we want to slice and dice our numerical data by. 00:05:11.860 --> 00:05:14.460 align:middle line:90% Dimensions are often discrete. 00:05:14.460 --> 00:05:17.390 align:middle line:84% Discrete fields create labels in the chart 00:05:17.390 --> 00:05:21.600 align:middle line:84% and are color coded blue in the data pane and in the view. 00:05:21.600 --> 00:05:25.040 align:middle line:84% Measures, on the other hand, are our metrics. 00:05:25.040 --> 00:05:27.940 align:middle line:90% They are the numbers we want to analyze. 00:05:27.940 --> 00:05:30.380 align:middle line:90% Measures are often continuous. 00:05:30.380 --> 00:05:33.190 align:middle line:84% Continuous fields create axes in the chart 00:05:33.190 --> 00:05:37.170 align:middle line:90% and their pills are color coded green. 00:05:37.170 --> 00:05:40.400 align:middle line:84% Now, let’s say we’re interested in our total sales number. 00:05:40.400 --> 00:05:42.220 align:middle line:90% Let’s place Sales in the view. 00:05:42.220 --> 00:05:44.540 align:middle line:90% 00:05:44.540 --> 00:05:45.040 align:middle line:90% We 00:05:45.040 --> 00:05:47.200 align:middle line:84% can see that Tableau queries the database 00:05:47.200 --> 00:05:50.770 align:middle line:84% and returns a single result giving us the sum of Sales. 00:05:50.770 --> 00:05:55.200 align:middle line:84% This company has done a little over 12 and a half million in sales. 00:05:55.200 --> 00:06:01.190 align:middle line:84% If we want to see this over time, we can drag Order Date to the top of the view. 00:06:01.190 --> 00:06:05.310 align:middle line:84% Tableau Desktop aggregates our dates at the year level. 00:06:05.310 --> 00:06:08.930 align:middle line:84% We can expand this with the plus ( ) symbol on the pill. 00:06:08.930 --> 00:06:13.670 align:middle line:84% Now we see both quarters and years in the view. 00:06:13.670 --> 00:06:16.660 align:middle line:84% To see how all our Q1s are doing over the years, 00:06:16.660 --> 00:06:21.080 align:middle line:84% we can easily pivot the data so Quarter is in front of Year. 00:06:21.080 --> 00:06:26.480 align:middle line:84% Now we can compare how our growth looks by quarter across the years. 00:06:26.480 --> 00:06:31.670 align:middle line:84% Moving Year to Color shows us all the years on top of each other. 00:06:31.670 --> 00:06:36.820 align:middle line:84% If, instead of drilling down further, we want to change quarters to months, 00:06:36.820 --> 00:06:40.490 align:middle line:84% we can click on the pill to bring up the drop-down menu and change it. 00:06:40.490 --> 00:06:43.070 align:middle line:90% 00:06:43.070 --> 00:06:46.600 align:middle line:84% If looking at an average of sales is more useful than sum of sales, 00:06:46.600 --> 00:06:50.060 align:middle line:84% we can simply change that by using the dropdown menu 00:06:50.060 --> 00:06:53.760 align:middle line:90% and changing the aggregation to average. 00:06:53.760 --> 00:06:57.530 align:middle line:90% But let’s undo that for now. 00:06:57.530 --> 00:07:01.160 align:middle line:84% What about if we want to know about something like year over year growth? 00:07:01.160 --> 00:07:05.080 align:middle line:84% In Tableau Desktop, calculations like this are easy. 00:07:05.080 --> 00:07:09.060 align:middle line:84% Once again, clicking on the pill’s dropdown brings up the menu, 00:07:09.060 --> 00:07:11.850 align:middle line:84% and now going to Quick Table Calculation, 00:07:11.850 --> 00:07:16.260 align:middle line:84% we can see common business calculations as single click options. 00:07:16.260 --> 00:07:18.610 align:middle line:90% Let’s select “Year over Year Growth”. 00:07:18.610 --> 00:07:21.440 align:middle line:90% 00:07:21.440 --> 00:07:23.355 align:middle line:84% If we still want to see the original Sales, 00:07:23.355 --> 00:07:25.480 align:middle line:84% we can simply place it back into the visualization. 00:07:25.480 --> 00:07:28.310 align:middle line:90% 00:07:28.310 --> 00:07:31.050 align:middle line:84% Perhaps we want to have the Year over Year Growth values 00:07:31.050 --> 00:07:34.450 align:middle line:84% appear in a tooltip instead of a graph, we can simply 00:07:34.450 --> 00:07:36.670 align:middle line:90% move it to the Tooltip shelf. 00:07:36.670 --> 00:07:39.320 align:middle line:84% The tooltip provides additional information 00:07:39.320 --> 00:07:41.260 align:middle line:90% when we hover over marks in the view. 00:07:41.260 --> 00:07:47.190 align:middle line:84% For example, here in November of 2015, we see we’re almost 50% up from 00:07:47.190 --> 00:07:49.750 align:middle line:90% the previous year. 00:07:49.750 --> 00:07:53.470 align:middle line:90% Let’s drag Category to the Rows shelf. 00:07:53.470 --> 00:07:57.030 align:middle line:84% We can now see which categories are doing well, 00:07:57.030 --> 00:07:58.850 align:middle line:90% and when they were doing well. 00:07:58.850 --> 00:08:01.150 align:middle line:90% We could even leave comments. 00:08:01.150 --> 00:08:05.130 align:middle line:84% For example, we see there’s a yearly dip in sales in July, 00:08:05.130 --> 00:08:07.160 align:middle line:90% but we rebound in the fall. 00:08:07.160 --> 00:08:12.880 align:middle line:84% We can leave an annotation by right-clicking, selecting Annotate, 00:08:12.880 --> 00:08:14.615 align:middle line:90% and adding a point Annotation. 00:08:14.615 --> 00:08:18.720 align:middle line:90% 00:08:18.720 --> 00:08:22.400 align:middle line:84% This is a useful view--if we wanted to easily share this, 00:08:22.400 --> 00:08:27.630 align:middle line:84% we could now right-click, copy the image, 00:08:27.630 --> 00:08:31.740 align:middle line:84% and quickly share it with other people in our organization. 00:08:31.740 --> 00:08:37.690 align:middle line:84% But for now we’ll double click on the sheet tab and rename this “Sales 00:08:37.690 --> 00:08:40.059 align:middle line:90% Seasonality”. 00:08:40.059 --> 00:08:42.909 align:middle line:84% What if we want the raw numbers behind this timeline? 00:08:42.909 --> 00:08:46.010 align:middle line:84% Tableau Desktop makes this very easy to do. 00:08:46.010 --> 00:08:49.600 align:middle line:84% We can right click on the viz and copy the data, 00:08:49.600 --> 00:08:58.300 align:middle line:84% and then paste it into Excel – this includes even that Quick Table 00:08:58.300 --> 00:09:02.750 align:middle line:84% calculation we did—or we can simply right- 00:09:02.750 --> 00:09:07.470 align:middle line:84% click on the tab and “Duplicate as a Crosstab”. 00:09:07.470 --> 00:09:13.810 align:middle line:84% We can easily swap our axes and move Category to the Rows shelf. 00:09:13.810 --> 00:09:16.320 align:middle line:90% Let’s make this fit a little better. 00:09:16.320 --> 00:09:19.970 align:middle line:90% 00:09:19.970 --> 00:09:23.840 align:middle line:84% This looks nice, but I’m worried that profits for our Office Supplies weren’t 00:09:23.840 --> 00:09:26.960 align:middle line:84% good during our sale and into the end of the year. 00:09:26.960 --> 00:09:30.970 align:middle line:84% Let’s add profit to the crosstab and find out how we’re doing. 00:09:30.970 --> 00:09:35.430 align:middle line:84% Adding Profit to color gives us a clearer understanding 00:09:35.430 --> 00:09:37.710 align:middle line:90% of overall trends. 00:09:37.710 --> 00:09:41.830 align:middle line:84% These colors are a bit pale, though, so let’s edit how we display this. 00:09:41.830 --> 00:09:45.840 align:middle line:84% We’ll click on color and click “Edit Colors”. 00:09:45.840 --> 00:09:49.850 align:middle line:84% Here, we can choose from a wide variety of colors in the drop- down menu, 00:09:49.850 --> 00:09:58.840 align:middle line:84% I like green-gold, and we’ll use stepped colors and make 6 of them. 00:09:58.840 --> 00:10:04.360 align:middle line:84% Let’s change the mark type to square and turn on mark labels. 00:10:04.360 --> 00:10:08.410 align:middle line:84% Now we have a highlight table for profit. 00:10:08.410 --> 00:10:15.830 align:middle line:84% We can right click on the Category pill and select Show Highlighter – if we 00:10:15.830 --> 00:10:21.100 align:middle line:84% select Office Supplies, we can see that the fall of 2015 is dark green, 00:10:21.100 --> 00:10:23.730 align:middle line:84% so our profits for those months are strong. 00:10:23.730 --> 00:10:25.210 align:middle line:90% Great! 00:10:25.210 --> 00:10:28.560 align:middle line:84% Hovering over those categories in the highlighter, 00:10:28.560 --> 00:10:31.970 align:middle line:84% we can quickly see that although our fall profits are doing well 00:10:31.970 --> 00:10:36.400 align:middle line:84% in technology and office supplies, furniture doesn’t have that same dark 00:10:36.400 --> 00:10:38.910 align:middle line:90% green upswing in profit. 00:10:38.910 --> 00:10:40.960 align:middle line:90% Is this happening across all stores? 00:10:40.960 --> 00:10:42.330 align:middle line:90% Let’s find out! 00:10:42.330 --> 00:10:47.470 align:middle line:84% We’ll double click on the sheet tab and rename this sheet “Crosstab” and create 00:10:47.470 --> 00:10:48.140 align:middle line:90% a new sheet. 00:10:48.140 --> 00:10:50.900 align:middle line:90% 00:10:50.900 --> 00:10:52.810 align:middle line:84% We know that furniture’s profits are bad, 00:10:52.810 --> 00:10:54.860 align:middle line:90% and we think this may vary regionally. 00:10:54.860 --> 00:10:58.130 align:middle line:84% But we don’t necessarily know the best way to view the data. 00:10:58.130 --> 00:11:02.950 align:middle line:84% Tableau Desktop provides a simple tool called “Show Me” to help in cases where 00:11:02.950 --> 00:11:06.770 align:middle line:84% we know the data we want to look at, but don’t know how to create an effective 00:11:06.770 --> 00:11:07.900 align:middle line:90% view. 00:11:07.900 --> 00:11:11.840 align:middle line:84% “Show Me” contains a list of common chart types that can help you start 00:11:11.840 --> 00:11:14.070 align:middle line:90% your analysis. 00:11:14.070 --> 00:11:18.220 align:middle line:84% NOTE: it’s possible to build an enormous variety of charts in Tableau – Show Me 00:11:18.220 --> 00:11:18.720 align:middle line:90% is the 00:11:18.720 --> 00:11:23.540 align:middle line:84% one-click options, not a comprehensive list of possibilities. 00:11:23.540 --> 00:11:27.400 align:middle line:84% Let’s see Show Me at work by selecting different dimensions and measures while 00:11:27.400 --> 00:11:29.230 align:middle line:90% holding down the control key. 00:11:29.230 --> 00:11:34.950 align:middle line:84% We’re curious about our Sales, and how they’re doing in different Countries. 00:11:34.950 --> 00:11:38.644 align:middle line:84% Notice how different chart types come available based on what measures 00:11:38.644 --> 00:11:39.810 align:middle line:90% and dimensions we’ve chosen. 00:11:39.810 --> 00:11:42.410 align:middle line:90% 00:11:42.410 --> 00:11:45.880 align:middle line:84% Symbol maps look like a good choice for these fields. 00:11:45.880 --> 00:11:48.025 align:middle line:90% Let’s also add State. 00:11:48.025 --> 00:11:54.000 align:middle line:90% 00:11:54.000 --> 00:11:59.990 align:middle line:84% We can increase the size of these dots by clicking on the size shelf, 00:11:59.990 --> 00:12:05.515 align:middle line:84% let’s also adjust the transparency and add some borders. 00:12:05.515 --> 00:12:10.740 align:middle line:90% 00:12:10.740 --> 00:12:15.940 align:middle line:84% We’ll hide the size legend, and let’s color these states by Profit. 00:12:15.940 --> 00:12:18.610 align:middle line:90% 00:12:18.610 --> 00:12:22.640 align:middle line:84% Note that we can do geographic search here – if we want to see how profits 00:12:22.640 --> 00:12:26.350 align:middle line:84% are doing in a certain location, we can navigate right to it. 00:12:26.350 --> 00:12:30.410 align:middle line:90% Let’s unpin to zoom back out. 00:12:30.410 --> 00:12:34.660 align:middle line:84% Now, we’re a global company, and there’s that dip in sales in July. 00:12:34.660 --> 00:12:38.270 align:middle line:84% Is that because of an action of ours, driven from headquarters, 00:12:38.270 --> 00:12:40.460 align:middle line:90% or is that a seasonal effect? 00:12:40.460 --> 00:12:44.400 align:middle line:84% We could tell by breaking up our sales over time by Hemisphere, 00:12:44.400 --> 00:12:46.750 align:middle line:84% but we don’t have that field in the data. 00:12:46.750 --> 00:12:51.270 align:middle line:84% However, we can create that custom territory ourselves, directly 00:12:51.270 --> 00:12:53.050 align:middle line:90% in the map. 00:12:53.050 --> 00:12:55.410 align:middle line:84% Let’s right click and duplicate this sheet, 00:12:55.410 --> 00:12:58.040 align:middle line:84% so we can leave our original view intact. 00:12:58.040 --> 00:13:02.280 align:middle line:84% We can simplify the view, stripping out everything but Country. 00:13:02.280 --> 00:13:05.890 align:middle line:90% 00:13:05.890 --> 00:13:10.710 align:middle line:84% Next, we’ll use the lasso select tool and lasso marks covering 00:13:10.710 --> 00:13:16.030 align:middle line:84% the approximate southern hemisphere—note this is very rough. 00:13:16.030 --> 00:13:20.070 align:middle line:84% Clicking the paperclip icon in the tooltip creates a group for those 00:13:20.070 --> 00:13:24.680 align:middle line:84% countries, and we’ve made a new field in the data pane. 00:13:24.680 --> 00:13:29.430 align:middle line:84% If we go back to our sales seasonality tab and add this new field 00:13:29.430 --> 00:13:32.760 align:middle line:90% to Columns…it looks 00:13:32.760 --> 00:13:35.690 align:middle line:84% like we have less revenue overall from the southern hemisphere, 00:13:35.690 --> 00:13:41.830 align:middle line:84% but if we keep only this column, there’s no clear evidence of seasonality. 00:13:41.830 --> 00:13:43.030 align:middle line:90% Good to know! 00:13:43.030 --> 00:13:51.900 align:middle line:84% We can leave this avenue of analysis—and even delete this sheet and head back 00:13:51.900 --> 00:13:53.300 align:middle line:90% to our original map. 00:13:53.300 --> 00:13:58.630 align:middle line:90% We’ll name it “Global Sales and Profits” 00:13:58.630 --> 00:14:01.460 align:middle line:84% Earlier, we found that furniture had poor profits. 00:14:01.460 --> 00:14:06.870 align:middle line:84% To investigate this further, let’s drag Category to the filters shelf. 00:14:06.870 --> 00:14:08.545 align:middle line:90% We’ll choose Furniture. 00:14:08.545 --> 00:14:11.560 align:middle line:90% 00:14:11.560 --> 00:14:15.680 align:middle line:84% To make this an interactive filter, we’ll right click the pill and select 00:14:15.680 --> 00:14:18.620 align:middle line:90% “Show Filter”. 00:14:18.620 --> 00:14:22.670 align:middle line:84% We can also modify filters by selecting their drop-down menu 00:14:22.670 --> 00:14:25.130 align:middle line:90% and choosing from a variety of options. 00:14:25.130 --> 00:14:28.290 align:middle line:90% Here we’ll choose “Single Value List”. 00:14:28.290 --> 00:14:32.450 align:middle line:84% Now anyone can easily choose the categories they’re interested in, such 00:14:32.450 --> 00:14:35.310 align:middle line:90% as Furniture or Technology. 00:14:35.310 --> 00:14:41.900 align:middle line:84% So we know we have problems with furniture, but what types of furniture 00:14:41.900 --> 00:14:43.120 align:middle line:90% are doing poorly? 00:14:43.120 --> 00:14:48.960 align:middle line:84% Let’s create a new sheet, and use Show Me to find out. 00:14:48.960 --> 00:14:53.490 align:middle line:84% Again, as we hold down control and select the variables we’re interested 00:14:53.490 --> 00:14:58.580 align:middle line:84% in such as Category, Sub-Category and Sales, 00:14:58.580 --> 00:15:01.660 align:middle line:84% we see Show Me making various suggestions. 00:15:01.660 --> 00:15:05.670 align:middle line:84% We can click through a few charts to see which one looks best. 00:15:05.670 --> 00:15:08.400 align:middle line:90% 00:15:08.400 --> 00:15:12.740 align:middle line:84% There is a hierarchical nature between Category and Sub-Category in our data. 00:15:12.740 --> 00:15:13.660 align:middle line:90% In Tableau 00:15:13.660 --> 00:15:18.090 align:middle line:84% Desktop, we can create hierarchies by simply dragging and dropping fields 00:15:18.090 --> 00:15:20.510 align:middle line:90% on top of each other in the data pane. 00:15:20.510 --> 00:15:27.020 align:middle line:84% Let’s drag Sub-Category on top of Category and we’ll call this 00:15:27.020 --> 00:15:27.520 align:middle line:90% “Products”. 00:15:27.520 --> 00:15:32.600 align:middle line:90% 00:15:32.600 --> 00:15:37.130 align:middle line:84% We can add Product Name to this hierarchy as well. 00:15:37.130 --> 00:15:39.260 align:middle line:84% Creating this hierarchy in Tableau Desktop 00:15:39.260 --> 00:15:42.430 align:middle line:84% only takes seconds and gives us full drill down capabilities. 00:15:42.430 --> 00:15:47.070 align:middle line:90% 00:15:47.070 --> 00:15:50.060 align:middle line:84% To sort the three Categories by overall sales, 00:15:50.060 --> 00:15:53.430 align:middle line:84% we can click the appropriate sort button in the toolbar. 00:15:53.430 --> 00:15:58.010 align:middle line:84% Now we see that technology has the most total sales. 00:15:58.010 --> 00:16:03.880 align:middle line:84% If we expand out to see Sub-Category, we see that those bars aren’t sorted. 00:16:03.880 --> 00:16:07.820 align:middle line:84% Let’s sort again, this time using a quick sort from the axis, 00:16:07.820 --> 00:16:12.990 align:middle line:84% like so – note that the order of categories stayed the same and we’re 00:16:12.990 --> 00:16:16.450 align:middle line:84% only sorting the bars WITHIN each category. 00:16:16.450 --> 00:16:20.550 align:middle line:84% We can see the actual sales values by clicking on the “T” button 00:16:20.550 --> 00:16:25.160 align:middle line:84% in the toolbar to turn on or off the mark labels. 00:16:25.160 --> 00:16:27.120 align:middle line:90% But again, how’s profit? 00:16:27.120 --> 00:16:30.300 align:middle line:90% Let’s place Profit on Color. 00:16:30.300 --> 00:16:34.630 align:middle line:84% We quickly see that Tables are doing poorly from a profitability standpoint, 00:16:34.630 --> 00:16:36.970 align:middle line:90% despite how good the sales looked. 00:16:36.970 --> 00:16:40.490 align:middle line:84% Is this happening across all our markets? 00:16:40.490 --> 00:16:44.230 align:middle line:90% Let’s place Market here on the top. 00:16:44.230 --> 00:16:48.650 align:middle line:84% We quickly see that several markets seem to be having this same profitability 00:16:48.650 --> 00:16:51.940 align:middle line:90% problem when it comes to furniture. 00:16:51.940 --> 00:16:55.770 align:middle line:84% In this view, it’s useful to note that we can group items together. 00:16:55.770 --> 00:17:00.910 align:middle line:84% We see in Office Supplies that several items have very small sales. 00:17:00.910 --> 00:17:06.480 align:middle line:84% We can select the headers and group them using the paperclip icon. 00:17:06.480 --> 00:17:11.310 align:middle line:84% To rename that row, right click and select Edit Alias. 00:17:11.310 --> 00:17:14.650 align:middle line:90% 00:17:14.650 --> 00:17:19.569 align:middle line:84% Let’s remove Market again and swap the axes. 00:17:19.569 --> 00:17:23.180 align:middle line:84% We can also right click on the header for columns and hide that label. 00:17:23.180 --> 00:17:26.630 align:middle line:90% 00:17:26.630 --> 00:17:33.510 align:middle line:84% Let’s call this sheet, “Sales by Sub-Category” and create a new sheet. 00:17:33.510 --> 00:17:36.080 align:middle line:84% We’ve seen that we have some profitability issues, 00:17:36.080 --> 00:17:39.190 align:middle line:84% and I have a hunch that this may be due to shipping costs eating 00:17:39.190 --> 00:17:40.800 align:middle line:90% into our profits. 00:17:40.800 --> 00:17:44.550 align:middle line:84% Let’s take a look at our profit and shipping numbers. 00:17:44.550 --> 00:17:52.490 align:middle line:84% We’ll place: Profit on the Rows shelf and Shipping Cost on the Columns shelf 00:17:52.490 --> 00:17:56.880 align:middle line:84% Tableau makes a mark for the sum of profit and shipping cost. 00:17:56.880 --> 00:18:01.100 align:middle line:90% If we put Category on Color. 00:18:01.100 --> 00:18:05.640 align:middle line:84% That first mark is broken out by category and we wind up with 3 marks. 00:18:05.640 --> 00:18:13.120 align:middle line:84% And if we add Customer ID onto Detail, Tableau 00:18:13.120 --> 00:18:16.940 align:middle line:84% makes a mark for each customer for each category. 00:18:16.940 --> 00:18:21.850 align:middle line:84% These marks represent the total shipping cost and profit for all transactions 00:18:21.850 --> 00:18:24.950 align:middle line:84% within a single category for each customer. 00:18:24.950 --> 00:18:28.020 align:middle line:84% We could also fully disaggregate our data 00:18:28.020 --> 00:18:31.800 align:middle line:84% to plot each and every transaction at the record level. 00:18:31.800 --> 00:18:34.400 align:middle line:90% 00:18:34.400 --> 00:18:37.380 align:middle line:84% We can assign fields on the Marks card to different roles. 00:18:37.380 --> 00:18:41.630 align:middle line:84% For instance, we can click on the color icon in front of Category 00:18:41.630 --> 00:18:43.780 align:middle line:90% and change it to Label. 00:18:43.780 --> 00:18:47.870 align:middle line:84% We can bring fields directly to the label shelf, such as Sub-Category. 00:18:47.870 --> 00:18:51.090 align:middle line:90% 00:18:51.090 --> 00:18:57.530 align:middle line:84% We can edit this label by clicking and then again by text and modifying 00:18:57.530 --> 00:18:58.220 align:middle line:90% as we see fit. 00:18:58.220 --> 00:19:03.250 align:middle line:90% 00:19:03.250 --> 00:19:06.400 align:middle line:84% From here, we can see that we have a significant number of customers with 00:19:06.400 --> 00:19:09.850 align:middle line:84% low profits in various categories, so there’s definitely something worth 00:19:09.850 --> 00:19:11.440 align:middle line:90% looking into. 00:19:11.440 --> 00:19:14.900 align:middle line:84% I wonder if those low profit orders were returned. 00:19:14.900 --> 00:19:18.120 align:middle line:90% We can bring “returned” to Size. 00:19:18.120 --> 00:19:22.070 align:middle line:84% It looks like the mark with the highest shipping cost was returned, 00:19:22.070 --> 00:19:25.260 align:middle line:90% but not the low profit orders. 00:19:25.260 --> 00:19:27.980 align:middle line:84% But is there a relationship between our shipping cost and profit, 00:19:27.980 --> 00:19:29.550 align:middle line:90% as I think there might be? 00:19:29.550 --> 00:19:36.140 align:middle line:84% We can take off our labels and size to stay focused. 00:19:36.140 --> 00:19:38.640 align:middle line:90% Let’s add a trend line. 00:19:38.640 --> 00:19:45.070 align:middle line:84% We can do this easily from the analytics pane, selecting trend line 00:19:45.070 --> 00:19:46.570 align:middle line:90% and bringing it into the view. 00:19:46.570 --> 00:19:49.260 align:middle line:90% 00:19:49.260 --> 00:19:53.750 align:middle line:84% As shipping cost goes up, profits go up less sharply in furniture. 00:19:53.750 --> 00:19:58.840 align:middle line:84% But if we hover over this trend line, we can see it’s got a very low R-squared, 00:19:58.840 --> 00:20:01.120 align:middle line:90% so it’s not particularly meaningful. 00:20:01.120 --> 00:20:05.090 align:middle line:90% Let’s drag off these trend lines. 00:20:05.090 --> 00:20:08.030 align:middle line:84% However, there are some pretty extreme low-profit marks. 00:20:08.030 --> 00:20:12.440 align:middle line:84% We can quickly identify customers that are contributing to profit problems. 00:20:12.440 --> 00:20:16.130 align:middle line:84% Selecting these marks, we can look at the underlying data directly. 00:20:16.130 --> 00:20:21.660 align:middle line:90% 00:20:21.660 --> 00:20:25.510 align:middle line:84% Let’s change Category to be shape instead of color, 00:20:25.510 --> 00:20:27.210 align:middle line:90% and change the color to Grey. 00:20:27.210 --> 00:20:30.060 align:middle line:90% 00:20:30.060 --> 00:20:31.895 align:middle line:84% We’ll call this sheet “Customer Breakdown”. 00:20:31.895 --> 00:20:35.130 align:middle line:90% 00:20:35.130 --> 00:20:38.170 align:middle line:84% We’ve created some insightful views of this data set. 00:20:38.170 --> 00:20:42.560 align:middle line:84% Now, we want to share this with our team and compile a dashboard. 00:20:42.560 --> 00:20:47.220 align:middle line:84% Multiple individual views can be combined into a single dashboard. 00:20:47.220 --> 00:20:49.620 align:middle line:90% Click the new dashboard tab. 00:20:49.620 --> 00:20:53.990 align:middle line:84% We’ll name it Sales Dashboard, and we’ll size it to Laptop. 00:20:53.990 --> 00:20:58.220 align:middle line:90% 00:20:58.220 --> 00:21:00.380 align:middle line:90% All of our sheets are here to the left. 00:21:00.380 --> 00:21:03.600 align:middle line:90% Hovering brings up a preview. 00:21:03.600 --> 00:21:11.180 align:middle line:84% Let’s drag our Map into the view, and place “Sales by Sub-Category” 00:21:11.180 --> 00:21:16.370 align:middle line:84% and “Customer Breakdown” below it, and add a dashboard title. 00:21:16.370 --> 00:21:21.760 align:middle line:84% On the interactive filter, notice that when we click on various categories, 00:21:21.760 --> 00:21:24.590 align:middle line:84% our map will change to reflect what we’ve selected. 00:21:24.590 --> 00:21:27.430 align:middle line:84% But what if we want all the visualizations in the workbook 00:21:27.430 --> 00:21:28.680 align:middle line:90% to change? 00:21:28.680 --> 00:21:32.530 align:middle line:84% We can select the drop-down menu and choose 00:21:32.530 --> 00:21:36.460 align:middle line:90% apply to All using this data source. 00:21:36.460 --> 00:21:38.850 align:middle line:90% Now all of our sheets will update. 00:21:38.850 --> 00:21:41.570 align:middle line:90% 00:21:41.570 --> 00:21:44.400 align:middle line:84% But what if we want to drill down to details on the map? 00:21:44.400 --> 00:21:50.490 align:middle line:84% For instance, there’s a low- profit mark on the map in Texas and we may want 00:21:50.490 --> 00:21:52.440 align:middle line:90% to see what makes up that mark. 00:21:52.440 --> 00:21:56.590 align:middle line:84% When we’ve clicked on the map, we can turn on the filter icon here 00:21:56.590 --> 00:22:00.820 align:middle line:84% in the border, and the entire map has now been turned into a filter. 00:22:00.820 --> 00:22:04.860 align:middle line:84% The bar chart and scatter plot have updated to show just that mark’s 00:22:04.860 --> 00:22:07.410 align:middle line:90% information. 00:22:07.410 --> 00:22:10.240 align:middle line:84% What if want to lead our audience through the path of our discovery 00:22:10.240 --> 00:22:12.210 align:middle line:90% of these profitability issues? 00:22:12.210 --> 00:22:15.660 align:middle line:84% Tableau Desktop offers a feature called Story Points that 00:22:15.660 --> 00:22:18.100 align:middle line:84% lets you assemble a series of specific views 00:22:18.100 --> 00:22:20.740 align:middle line:84% to walk the audience through an analysis. 00:22:20.740 --> 00:22:24.620 align:middle line:84% We can build a story by clicking the New Story tab. 00:22:24.620 --> 00:22:27.005 align:middle line:90% I’ll make mine size to automatic. 00:22:27.005 --> 00:22:31.050 align:middle line:90% 00:22:31.050 --> 00:22:34.970 align:middle line:84% Just like with a dashboard, we can bring in any visualizations we’d previously 00:22:34.970 --> 00:22:36.280 align:middle line:90% made. 00:22:36.280 --> 00:22:42.340 align:middle line:84% Let’s pull out Global Sales and Profits and name this point “Overall, 00:22:42.340 --> 00:22:44.410 align:middle line:90% our profits look strong”. 00:22:44.410 --> 00:22:48.330 align:middle line:84% We can easily add more content – let’s bring out our dashboard. 00:22:48.330 --> 00:22:51.700 align:middle line:90% 00:22:51.700 --> 00:23:00.790 align:middle line:84% And size it to the story, and turn off the title again. 00:23:00.790 --> 00:23:07.700 align:middle line:84% The viz is still fully interactive – we can filter, 00:23:07.700 --> 00:23:10.150 align:middle line:90% and call out that mark in Texas. 00:23:10.150 --> 00:23:14.710 align:middle line:84% When we do, the word Update appears above the navigator. 00:23:14.710 --> 00:23:18.110 align:middle line:84% Clicking “update” will save this state of the viz, 00:23:18.110 --> 00:23:21.390 align:middle line:84% so everyone will see exactly this information. 00:23:21.390 --> 00:23:24.660 align:middle line:84% We’ll title this “But there are problem areas”. 00:23:24.660 --> 00:23:29.880 align:middle line:84% This is one of the key aspect of Story Points, the ability 00:23:29.880 --> 00:23:32.840 align:middle line:84% to snapshot a specific insight of a visualization 00:23:32.840 --> 00:23:36.550 align:middle line:90% while still maintaining interactivity. 00:23:36.550 --> 00:23:39.660 align:middle line:84% Now that we have gone from raw data to insight in this workbook, 00:23:39.660 --> 00:23:42.910 align:middle line:84% we want to think about how to distribute it to others. 00:23:42.910 --> 00:23:45.550 align:middle line:84% The most effective way to share a workbook 00:23:45.550 --> 00:23:49.320 align:middle line:84% is to publish it with Tableau Server or Tableau online. 00:23:49.320 --> 00:23:54.360 align:middle line:84% Published workbooks are fully interactive, up-to-date, secure, 00:23:54.360 --> 00:23:58.500 align:middle line:84% and can be accessed by browser or mobile app. 00:23:58.500 --> 00:24:04.080 align:middle line:84% To publish, open the Server menu and select Publish Workbook. 00:24:04.080 --> 00:24:07.100 align:middle line:84% We could also choose to publish the data source, 00:24:07.100 --> 00:24:11.130 align:middle line:84% if we only want to publish the data itself for others to use. 00:24:11.130 --> 00:24:18.870 align:middle line:84% We can publish to a specific project, name the workbook, enter a description, 00:24:18.870 --> 00:24:27.435 align:middle line:84% tag the content, choose exactly what to publish, and control permissions. 00:24:27.435 --> 00:24:31.750 align:middle line:90% 00:24:31.750 --> 00:24:35.200 align:middle line:84% Once published, interacting with content is easy, 00:24:35.200 --> 00:24:41.200 align:middle line:84% and everything is still fully interactive, right in the browser. 00:24:41.200 --> 00:24:43.950 align:middle line:84% We can subscribe to content to get updates 00:24:43.950 --> 00:24:50.380 align:middle line:84% emailed on a set schedule, favorite content, and search and filter. 00:24:50.380 --> 00:24:52.940 align:middle line:90% 00:24:52.940 --> 00:24:56.030 align:middle line:84% With iOS and Android apps, dashboards and data 00:24:56.030 --> 00:25:00.770 align:middle line:84% are securely available wherever you have a phone or tablet. 00:25:00.770 --> 00:25:02.630 align:middle line:90% Thank you for watching Getting Started. 00:25:02.630 --> 00:25:07.470 align:middle line:84% We invite you to continue with the Free Training videos to learn more.