Tableau is one of the leading tools used to solve business intelligence (BI) and analytics challenges. With this book, you will master Tableau’s features and offerings in various paradigms of the BI domain. As an update to the successful Mastering Tableau series, this book covers the essential Tableau concepts, data preparation, and calculations with Tableau, all the way up to machine learning use cases.

This edition comes with new datasets, more examples of how to improve dashboard performance, and the most up-to-date know-how on data visualization, Tableau Server, and Tableau Prep Builder.

This new edition will also explore Tableau’s connections with Python and R, Tableau extensions, joins, and unions, and last but not least, three new use cases of powerful self-service analytics, time-series analytics, and geo-spatial analytics in order to implement the learned content. By the end of this book, you’ll have mastered the advanced...

At the heart of Tableau are worksheets and dashboards. Worksheets contain individual visualizations and dashboards contain one or more worksheets. Additionally, worksheets and dashboards may be combined into stories to communicate particular insights to the end user through a presentation environment. Lastly, all worksheets, dashboards, and stories are organized in workbooks, which can be accessed using Tableau Desktop, Server, Reader, or the Tableau mobile app.

At this point, I would like to introduce you to Tableau Public (https://public.tableau.com/app/discover). At times, you might need some inspiration, or you might want to replicate a dashboard created by another Tableau user. In this case, Tableau Public will be your place to go! It is a web-based collection of dashboards, as well as a creator’s platform that allows you to design beautiful dashboards without a license or installation.

You can create your own profile—registration...

At the time of writing, Tableau’s data connection menu includes more than 90 different connection types. And that’s somewhat of an understatement since some of those types contain multiple options. For example, Other Files includes more than 30 options. Of course, we won’t cover the details for every connection type, but we will cover the basics. The official documentation on all connectors can be found here: https://help.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm.

Upon opening a new instance of Tableau Desktop from within Tableau Desktop (File | New), you’ll notice a Connect to Data link in the top-left corner of the workspace. Clicking on that link will enable you to connect to the data. Opening a new instance of Tableau from the application’s location on your computer will bring up the blue Connect pane right away. Alternatively, you can click on the New Data Source icon on the toolbar...

I’ve observed the following scenario frequently: a new Tableau author creates a worksheet and drags a measure to the Text shelf. They drag the second measure to various places on the view and get results that seem entirely unpredictable. The experience is very frustrating for the author since it’s so easy to accomplish this in Microsoft Excel! The good news is that it’s also easy to accomplish this in Tableau. It just requires a different approach.

Measure Names and Measure Values are generated fields in Tableau. They don’t exist in the underlying data, but they’re indispensable for creating many kinds of views. As may be guessed from its placement in the Data pane and its name, Measure Names is a dimension whose members are made up of the names of each measure in the underlying dataset. Measure Values contains the numbers or values of each measure in the dataset.

In this section, we’ll watch what happens...

An important stop on the road to mastering Tableau involves three essential concepts. In this section, we’ll discuss each of them:

• Dimensions and measures
• Row-level, aggregate-level, and table-level calculations
• Continuous and discrete

We’ll start by defining dimensions and measures.

Dimensions and measures

Tableau categorizes every field from an underlying data source as either a dimension or a measure. A dimension is qualitative or, to use another word, categorical. A measure is quantitative or aggregable. A measure is usually a number but may be an aggregated, non-numeric field, such as MAX (Date). A dimension is usually a text, Boolean, or date field, but may also be a number, such as Number of Records. Dimensions provide meaning to numbers by slicing those numbers into separate parts/categories. Measures without dimensions are mostly meaningless.

Let’s look at an example to understand...

Once a dashboard looks as it’s expected to, the developer has different choices for sharing the work. An upload to Tableau Server is the most likely option. The end user might not look at the results on just a laptop; they could use a tablet or cellphone, too.

Exporting data to a mobile phone

While developing a dashboard, Tableau Creator has the option to take a look at Device Designer or Device Preview. Whenever you are on a Dashboard tab, you can find it here:

Figure 1.47: Device Preview

Tableau comes with default phone settings. If needed, those defaults can be adjusted by clicking on Phone and then on the three dots. Once you’re in the Device Designer mode, select a Device type option and you’ll get choices of the most common models:

Figure 1.48: Device type set to Phone

Please be aware that you can only use the sheets that are in the default layout of your dashboard. If you want to add a default...

In this chapter, we covered the basics of Tableau. We began with some basic terminology, then we looked at the basics of creating worksheets and dashboards. We focused on default behavior and how to override that behavior, and we considered some best practices. Then, we reviewed the fundamental principles of Measure Names and Measure Values. After that, we explored three essential Tableau concepts: dimensions and measures; row-, aggregate-, and table-level calculations; and the concepts of continuous and discrete. Of particular importance is understanding that row- and aggregate-level calculations are computed by the data source engine, while table-level calculations are handled by Tableau. Finally, we saw how to adjust your dashboard for other devices, such as a cellphone or tablet and Tableau Mobile in action.

In the next chapter, we’ll continue our Tableau exploration by looking at data. We’ll consider how data is prepared using Tableau’s data handling...