This chapter is an introduction to the Tableau workspace. A Tableau chart begins on the Data Source page when you create connections to files or databases. When creating Tableau worksheets, you’ll work with cards, shelves, controls, and legends. Adding fields from the Data pane to shelves, tiles on the Marks card, or tooltips add data to the view. The Analytics pane controls totals, trend lines, reference lines and more. Dashboard, Worksheet, Data, Format, and Analysis menus complement or enhance view objects.

The first step for any chart is to connect to a data source. Tableau has approximately 100 connectors to files, databases, data warehouses like Snowflake, web data connectors, and native API connectors where you provide a hostname, port, username, password, authentication key, or token. Once connected to a data source, you might need to create aliases, create filters, create an extract, hide unused fields, or transform or split strings, and we’ll look at those common tasks. I have included a section on what to watch out for when moving a data source file or replacing a data source. There is also a step-by-step guide for replacing a data source since renamed fields, custom colors and shapes, and data types can all cause issues.

Several fundamental Tableau concepts are crucial to successful chart development. Because I have included fifty step-by-step chart examples and dozens of task examples, you can relax and learn about dimensions, measures, geographic roles, groups, sets, discrete and continuous dates and measures, aggregation, parameters, the measure names field, the measure values field, and actions at your own pace. In addition, while not specific to Tableau, concepts like “placeholders” and “green and blue pills” are also commonly used with Tableau.

Data has a unique vocabulary that includes data types, null values, totals, subtotals, grand totals, logical and physical layers, joins, and unions. In Tableau, you will also work with partitions, scope, aggregation, and the concept of tall data. To join tables with related fields, choose fields that are the same data type. For example, consider a join for an Excel data source with the column ‘Account Number’ on both worksheets, and both columns are an ‘integer’ data type. Both columns could also be a ‘string’ data type, but you would not want one column data type to be ‘integer’ and the other ‘string.’ When working with numbers, you may use rounding, set the number of decimals to display, and utilize percentage formats. For mathematical operations like ‘sum,’ number data types are floats (decimals) or integers (whole numbers.) Conversely, the house number in ‘1368 First Avenue’ is considered a string. Date formats vary across the globe, with US dates usually displayed as month-day-year, while day-month-year is common in other countries. Internally, Tableau uses the ISO date format of yyyy-MM-dd. Tableau can format months and weekdays as numbers, abbreviations, or with the first letter. 

With data visualizations, you will often hear about the importance of storytelling, but knowing where and how to begin the story can be overwhelming. An effective chart or dashboard has good data, answers questions at a glance, and targets the audience. Visually appealing dashboards have interesting chart types, are uncluttered, and might have helpful annotations and legends. A blank canvas is daunting, so I often start the development discussion with a mock-up. I say discussion because I ask my audience what they want, and I involve them in the process with checkpoints along the way. Simplicity can be a challenge, so I have broken the tasks into a beginning, middle, and end. For example, near the end, you might review the checklist of enhancements or use the validation and testing ideas. Depending on my audience, I might change how I share the dashboard or choose some features and ignore others. Each chart will be unique to your needs.

Tableau charts with multiple measures are extremely common and are often used to show comparisons, add formatting, or show additional marks. For example, a sparkline combination chart has both a line and circle marks colored to show whether the value is up or down. A donut chart is two circle charts of different sizes stacked on top of each other, and the two measures are simply “placeholder” fields. Depending on the mark type, two measures will mean two axes, but you can synchronize the axes so the axes are blended into one axis, and then you hide the second axis. Additional measures can show trends, a range of values, top and bottom values, the percentage of the whole, changes over time, related metrics, year-over-year comparisons, top and bottom values, first and last, minimum or maximum, or compare target or goal to actual performance. 

This chapter is full of dozens of easy-to-follow examples that will surely impress your audience. We will look at a Square mark type that creates a heat map, treemap, or highlight table. A Gantt mark type is sometimes used to create a bullet graph in addition to a Gantt char. Bar marks combined with Circle marks create a lollipop chart. Bar marks also create histogram charts. Circle marks create word cloud charts and bubble charts. A box-and-whisker chart uses a circle mark type with reference lines and a reference band. A Dumbbell chart combines the circle and line mark types. A slope chart combines line marks with area marks. Scatter Plots use two measures with a Shape mark type, and RAG ratings utilize colored shapes to show red, amber, and green performance indicators. We will also look at an example of a bar chart with yellow diamond-shaped marks to call attention to the top three values. A Timeline chart also uses a Shape mark along a linear path. Shape marks are an excellent way to add colored arrows with BANs (big numbers) on a dashboard. If you are like me, you can not resist adding custom shapes and colors, and we look at those examples along with transparent color and shape.

The concept of filtering is simple, but the implementation of filters in Tableau is anything but simple because you can use multiple filters on a worksheet or dashboard. Also, you can create filters by adding fields to the Filters shelf, adding ‘data source’ and ‘extract’ filters, setting up filter actions, or adding parameters to calculated fields. Filters are also different based on whether you are filtering a dimension, measure, date, set, or group. Finally, Tableau’s Order of Operations logic decides how and when filters are applied, and you can also change a filter on the Filters shelf to a context filter to change when the filter is applied. Sorting is straightforward in Tableau with manual sorts, nested sorts, or computed sorts, although you can’t sort a continuous field. You can sort from the field context menu, within field labels or legends, or use the sort tool in the axis or toolbar. The sort examples in this chapter show how to click data points to sort, choose a sort field by hovering, sort within a stacked bar with a combined field, and sort by rank.

Many of my Tableau charts use dates extensively. I may need date headers instead of an axis with a range of dates, and in that case, I need a discrete date field instead of a continuous date field. I often use dates in titles where the date field is not already in the view, so I use a date parameter or add a date field to the Detail tile of the Marks card so it is available for titles. In the Format pane, you can configure Tableau to use numbers or text for each date level you include in your view, such as month, weekday, and year. We’ll look at examples that illustrate the difference between aggregated “date parts” and “date values,” and explore the meaning of each. After we look at several common date functions, we look at three examples of dates in titles and how to use time duration. 

Table calculations are ideal when you need a basic calculation like rank, percent of total, a running total, or a year-over-year comparison. Table calculations are based on the level of detail data; if you exported the data from a worksheet, the level of detail would be a table that contains the fields and filtered data from that specific view. After you add a field to the view, click the drop-down arrow to open the field’s context menu and select a table calculation option. Tableau creates a calculated field with the correct expression and functions. The first example looks at a Pareto chart with a running total and a percent of the total table calculations. All Table Calculations have a ‘compute using’ choice where you can decide how the dimensions are grouped for addressing and partitioning. We look at twelve detailed scope examples that demonstrate partitioning and scope direction.

While it certainly is easier to write Tableau calculations if you have a programming background, the Calculation Editor has a reference pane on the right with sample syntax. The categories are around numbers, strings, dates, type conversion, logical expressions, aggregate functions, user functions, table calculations, which we looked at previously, and spatial functions. Tableau also has Level of Detail functions that are unique to Tableau, so I’ve included two very detailed LOD examples from the point of view without an LOD and then again with an LOD. I’ve also listed some examples of my favorite functions with cross-references to examples of those functions in other areas of this book. First, Last, Index, Lookup, Rank, Window Average, and Window Sum functions are all Table calculation functions, and we also look at simple examples to explore that syntax. In addition, we touch on Average, Count, CountD, Case Statements, Max, Min, Round, ATTR, and ZN functions and how you might use them. 

Formatting in Tableau can be a challenge because there are many ways to accomplish the same task. There’s also a lot going on in a relatively small space: shading, alignment, lines, headers, axes, titles, tables, totals, annotations, reference lines, trend lines, shapes, fonts, alignment, number formats, date formats, cell size, row height, column width, chart fit settings, and more. To begin, I label chart elements like panes, column and row headers, field labels, and marks. Then, we’ll use that knowledge to format chart elements. The final example illustrates using colored symbols (arrows) to indicate if values are up or down compared to the previous month. We’ll also save time by copying worksheet formatting and with default properties.

Labeling in Tableau encompasses mark labels, worksheet titles, axis titles, annotations, legends, row and column headers, and other text elements. Tableau is very flexible. You can use ‘measure names’ as labels, reposition mark labels, and choose only to show the first or last mark label, show only one mark label, or show any combination of mark labels. We’ll look at several real-world label examples including adding a header for a field on the text tile. We’ll review examples from other chapters that add a layer for headings in a small multiples chart and a dashboard container for custom column headers. There’s an interesting example that uses custom-colored shapes to combine a color and shape legend into one legend. We’ll also add dates and other field data to worksheet titles.

Tableau dashboards may combine several charts, text objects, navigation buttons, and images. You can set filters to apply to all charts or selected charts. Dashboards also have their actions that filter, go to a URL or sheet, change a parameter, or change set values. This dashboard chapter is by far the longest, with ten detailed step-by-step examples of KPI dashboards, dynamic zone variability, a sheet selection menu, a pop-out chart with a filter action, a collapsible container for filters, a sheet selection menu, radial buttons to switch sheets or change filters. We also look extensively at the containers that hold all the objects, and I’ve included nine tips to make it easier to position and resize objects within containers. Finally, we’ll take a brief look at stories

Tableau’s interactive features include tooltips, highlighting, drill-down hierarchies, parameters, and actions. Tooltips have command buttons to filter, group, view the underlying data, launch Explain Data, and create sets. We will look at an example of a calculated field to turn off highlighting. Actions can go to worksheets or URLs, change set values, send emails, or change parameters. Actions run on hover, select, or in menus, and we will look at when you want to use each type. As we explore parameters, we will look at how to populate a parameter with field values when the workbook opens and many step-by-step examples to switch between aggregations, measures, or dimensions, an action to change set values, open another worksheet from within a tooltip, and an action to drill down into a hierarchy.