Mastering Tableau 2019.1 - Second Edition

4 (3 reviews total)
By Marleen Meier , David Baldwin
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  1. Getting Up to Speed - A Review of the Basics

About this book

Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain.

This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you’ll be able to handle and prepare data easily. You’ll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you’ll learn how to perform data densification to make displaying granular data easier. Next, you’ll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you’ll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you’ll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB.

By the end of this book, you’ll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain.

Publication date:
February 2019
Publisher
Packt
Pages
558
ISBN
9781789533880

 

Chapter 1. Getting Up to Speed - A Review of the Basics

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 business intelligence domain. It's an update to the successful Mastering Tableau series, which covers essential Tableau concepts, data preparation, and calculations with Tableau. But this book will also include examples on improving dashboard performance, the know-how of data visualizations, and connecting to Tableau Server. This book covers the latest and most exciting features, such as Tableau Prep, the connections with Python and MATLAB, Tableau Extensions, Joins, and Unions, and last but not least, three use cases of powerful Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics in order to manifest the learned content. By the End of this book, you'll have mastered the advanced offerings of Tableau and its latest updates, up to Tableau version 2019.1.

Those who are fairly new to Tableau should find this chapter helpful in getting up to speed quickly; however, since this book targets advanced topics, relatively little time is spent considering the basics. For a more thorough consideration of fundamental topics, consider Learning Tableau Edition 3.0, written by Joshua Milligan and published by Packt Publishing.

In this chapter, we'll discuss the following topics:

  • Creating worksheets and dashboards
  • Connecting Tableau to your data
  • Connecting to Tableau Server
  • Connecting to saved data sources
  • Measure Names and Measure Values
  • Three essential Tableau concepts
  • Exporting data to other devices
 

Creating worksheets and dashboards


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 that can be accessed with the Tableau desktop, Server, reader or the Tableau mobile app. In this section, we'll survey creating worksheets and Dashboards, with the intention of communicating the basics, but we'll also provide some insight that may prove helpful to more seasoned Tableau users.

Creating worksheets

At the most fundamental level, a visualization in Tableau is created by placing one or more fields on one or more shelves. As an example, note that the visualization created in the following diagram is generated by placing the Sales field on the Text shelf:

Exercise: fundamentals of visualizations

Let's explore the basics of creating a visualization using an exercise:

  1. In the workbook, find the tab labeled Fundamentals of Visualizations:

 

  1. Locate Department within the Dimensions portion of the Data pane:
  1. Drag Department to the Color shelf:
  1. Click on the Color shelf and then on Edit Colors to adjust the colors as desired:
  1. Move Department to the Size, Label/Text, Detail, Columns, and Rows shelves. After placing Department on each shelf, click on the shelf itself to access additional options.
  1. Drop other fields on various shelves to continue exploring Tableau's behavior.

As you explore Tableau's behavior by dragging and dropping different fields onto different shelves, you'll notice that Tableau responds with default behaviors. These defaults, however, can be overridden, which we'll explore next.

Beyond the default behavior

In the preceding exercise, Fundamentals of visualizations, we can notice that the Marks card reads Automatic. This means that Tableau is providing the default view. The default view can be easily overridden by choosing a different selection from the drop-down menu:

Another type of default behavior can be observed when dragging a field onto a shelf. For example, dragging and dropping a measure onto a shelf will typically result in the SUM () aggregation.

Note

In Windows, you can override this default behavior by right-clicking and dragging a field from the Data pane and dropping it onto a shelf. Tableau will respond with a dialog box with possible options.

Here's a screenshot of the popup that will appear:

Exercise: overriding defaults

Let's walk through an exercise where we'll override the two default behaviors shown in the preceding screenshot:

  1. In the workbook associated with this chapter, navigate to the Overriding Defaults worksheet.
  2. Right-click and drag Date of Hire to the Columns shelf.

 

  1. In the resulting dialog box, choose the second instance of MONTH (Date of Hire):
  1. Place Number of Records on the Rows shelf and Department on the Detail shelf.

 

  1. Click on the dropdown in the Marks card and select Area:

Show Me

Show Me allows the Tableau author to create visualizations at the click of a button. To understand how it works, let's refer to the following screenshot:

 

Now let's look at the following aspects that are highlighted in the preceding screenshot:

  • A: Selected fields in theDatapane.
  • B: Fields deployed in the view, that is, pills.
  • C: The recommended view.
  • D: Help text that communicates the requirements for creating the recommended view or any selection choice over which the cursor is placed.

Every icon in Show Me that isn't greyed out represents a visualization that can be created simply by clicking on it. For example, in the diagram preceding, the Tableau author may choose to click on the pie chart icon to create a pie chart based on the selected and deployed fields.

Note

Show Me options are highlighted based on two criteria: the selected fields in the Data pane and the fields deployed in the view.

Show Me may be effectively used for the following reasons:

  • Efficiency: The proficient Tableau author already knows how to create the basic visualization types.Show Meautomates these basic types and thus may be used for quicker production.
  • Inspiration: Determining an effective way to visualize a dataset can be challenging.Show Mecan help with this challenge by allowing the Tableau author to quickly consider various options.
  • Education: An inexperienced Tableau author may accessShow Meto better understand how various visualizations are created. By reading the help text displayed at the bottom ofShow Meand observing the results generated by clicking on various options, much can be learned.

These three reasons demonstrate the strong capabilities that Show Me provides for worksheet creation, however, be careful not to use it as a crutch. If you click on the various options without understanding how each visualization is created, you're not only shortchanging the educational process, but you may generate results that aren't well-understood, and could thus lead to detrimental business decisions.

Creating dashboards

Although, as stated in the Creating worksheets and dashboards section, a Dashboard contains one or more worksheets, and Dashboards are much more than static presentations. They're an essential part of Tableau's interactivity. In this section, we'll populate a Dashboard with worksheets and then deploy actions for interactivity.

Exercise: building a dashboard

The following are the steps for building a Dashboard:

  1. In the Chapter 1 workbook, navigate to the Building a Dashboard tab.

 

  1. In theDashboard pane, located on the left side of the screen, double-click on each of the following worksheets (in the order in which they are listed) to add them to the Dashboard pane: Age/State, Pay Rate, Tree Map, Date of Hire, and Date of Termination:

 

  1. In the bottom-right corner of the Dashboard pane, click in the blank area to select a container. After clicking in the blank area, you should see a blue border around the filter and the legends. This indicates that the vertical container is selected:

 

  1. Select the vertical container handle and drag it to the left side of the Customers worksheet. Note the grey shading, which communicates where the container will be placed:

Note

The grey shading provided by Tableau when dragging elements, such as worksheets and containers, onto a Dashboard, helpfully communicates where the element will be placed. Take your time and observe carefully when placing an element on a Dashboard or the results may be unexpected.

  1. Format the dashboard as desired. The following tips may prove helpful:
    • Adjust the sizes of the elements on the screen by hovering over the edges between each element and then clicking and dragging as desired.
    • Note that the Age legend and Department filter in the following screenshot are floating elements. Make an element floating by right-clicking on the element handle and selecting Floating (see the previous screenshot and note that the handle is located immediately above the word Region in the top-right corner).
    • Create horizontal and vertical containers by dragging those objects from the bottom portion of the Dashboardpane.
    • Drag the edges of containers to adjust the size of each worksheet.
    • Display theDashboardtitle through the Dashboard, right-click Show Title:

Exercise: adding interactivity to a dashboard

One of the primary benefits of Tableau is the interactivity it provides the end user. Dashboards aren't simply for viewing; they're meant for interaction. In this exercise, we'll add interactivity to the Dashboard that was created in the previous exercise:

  1. Starting where the previous exercise ended, click the drop-down menu associated with the Department filter and select Apply to Worksheets, and then All Using This Data Source:
  1. To use the map as a filter for the other worksheets on the Dashboard pane, click the Use as Filter icon located at the top-right corner of the Age/State worksheet:
  1. Set Pay Rate to Use as Filter.
  2. Navigate to Dashboard > Actions.

 

  1. In the dialog box, click Add Action > Filter and create a filter, as shown:

Having completed the preceding dashboard exercise, you should now be able to click on various objects on the dashboard to observe the interactivity. To learn advanced dashboard techniques, be sure to check out Chapter 11, Visualization Best Practices and Dashboard Design.

 

Connecting Tableau to your data


At the time of writing, Tableau's data connection menu includes 70 different connection types. And that's somewhat of an understatement since some of those types contain multiple options. For example, the selection choice, Other Files, includes 34 options. Of course, we won't cover the details for every connection type, but we will cover the basics.

Upon opening a new instance of Tableau Desktop, you'll notice a link in the top-left corner of the workspace. Clicking on that link will enable you to connect to the data. Alternatively, you can click on the New Data Source icon on the toolbar:

Although in future chapters we'll connect to other data sources, here we'll limit the discussion to connecting to the Microsoft Excel and text files.

Exercise: observing metadata differences

Let's compare the instance of the Superstore data source with a new connection to the same data:

  1. In a new instance of Tableau, navigate to Data | New Data Source | Excel to connect to the sample—Superstore dataset that installs with Tableau desktop (it should be located on your hard drive under My Tableau Repository | Datasources).
  2. Double-click on the Orders sheet.
  3. Click on the Sheet 1 tab.
  4. Place Discount on the Text shelf.
  5. Double-click on Profit and Sales.
  6. Compare the results of the new worksheet to that of the worksheet entitled Observing Metadata Differences in the Chapter 1 workbook:
    • A: The data source name has been altered in the Chapter 1 workbook.
    • B: In the Chapter 1 workbook, the default aggregation of Discount is AVG. In the unaltered instance, the default is SUM.
    • C: Product Hierarchy exists only in the Chapter 1 workbook.
    • D: The format of Discount, Profit, and Sales differs between the two instances.
    • E: Profit Ratio exists only in the Chapter 1 workbook:
 

Connecting to Tableau Server


Connecting to Tableau Server is perhaps the single most important server-connection type to consider, since it's frequently used to provide better performance than may otherwise be possible. Additionally, connecting to Tableau Server enables the author to receive not only data, but information regarding how that data is to be interpreted; for example, whether a given field should be considered a measure or a dimension.

Exercise: connecting to Tableau Server

The following are the steps for connecting to Tableau Server:

  1. To complete this exercise, access to an instance of Tableau Server is necessary. If you don't have access to Tableau Server, consider installing a trial version on your local computer.
  2. In the workbook associated with this chapter, navigate to the Connecting to Tableau Server worksheet.
  3. Right-click on the Superstore data source and select Publish to Server.
  4. Log in to Tableau Server and follow the prompts to complete the publication of the data source.
  5. Open a new instance of Tableau Desktop and select Data | New Data Source | Tableau Server to connect to the data source published in the previous step.
  6. Click on Sheet 1 in the new workbook and observe that the changes made in the Chapter 1 workbook have been preserved.
  7. In the Data pane, right-click on Profit Ratio and note that it isn't directly editable.

Having completed the preceding two exercises, let's discuss the most germane point, that is, metadata. Metadata is often defined as data about the data. In the preceding case, the data source name, default aggregation, default number formatting, and hierarchy are all examples of Tableau remembering changes made to the metadata. This is important because publishing a data connection allows for consistency across multiple Tableau authors. For example, if your company has a policy regarding the use of decimal points when displaying currency, that policy will be easily adhered to if all Tableau authors start building workbooks by pointing to data sources where all formatting has been predefined.

 

In step 7 of this exercise, the fact that the Profit Ratio calculated field wasn't directly editable when accessed by connecting to Tableau Server as a data source has important implications. Imagine the problems that would ensue if different Tableau authors defined Profit Ratio differently. End users would have no way of understanding what Profit Ratio really means. However, by creating a workbook based on a published data source, the issue is alleviated. One version of Profit Ratio is defined and it can only be altered by changing the data source. This functionality can greatly assist consistency across the enterprise.

 

Connecting to saved data sources


Connecting to a saved data source on a local machine is very similar to connecting to a data source published on Tableau Server. Metadata definitions associated with the local data source are preserved just as they are on Tableau Server. Of course, since the data source is local instead of remote, the publication process is different. 

Exercise: creating a local data connection

Let's explore the following steps for creating a local data connection using an example:

  1. In the workbook associated with this chapter, navigate to the Local Data Connection tab.
  2. In the Data pane, right-click on the Superstore data source and select Add to Saved Data Sources.
  3. Using the resulting dialog box, save the data source as Superstore in My Tableau Repository | Datasources, which is located on your hard drive.
  4. Click on the Go to Start icon located in the top-left part of your screen and observe the newly-saved data source:

Note

You can save a local data source that points to a published data source on Tableau Server. First, connect to a published data source on Tableau Server. Then right-click on the data source in your workspace and choose Add to Saved Data Sources. Now you can connect to Tableau Server directly from your Start page!

 

Measure Names and Measure Values


I've observed the following scenario frequently, wherein a new Tableau author creates a worksheet and drags a measure to the Text shelf. The author does this in order to create another row to display a second measure but doesn't know how. They drag the second measure to various places on the view and gets 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. Let's explore the solution with an exercise.

 

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. Watch what happens when measure names and measure values are used independently. Then observe how they work elegantly together to create a view.

Exercise: Measure Names and Measure Values

The following are the steps for the exercise:

  1. In the workbook associated with this chapter, navigate to the MeasureNames/Values worksheet.
  2. Drag Measure Values to the Text shelf and observe the results:
  1. Clear the worksheet by clicking on the Clear Sheet icon on the toolbar:
  1. Drag Measure Names to the Rows shelf and observe that the view merely displays No Measure Value.
  2. Drag Measure Values to the Text shelf. Note the list of measures and associated values.

Perhaps the interrelationship between Measure Names and Measure Values is best explained by an analogy. Consider several pairs of socks and a partitioned sock drawer. Step 2 is the equivalent of throwing the socks into a pile. The results are well, disorganized. Step 4 is the equivalent of an empty sock drawer with partitions. The partitions are all in place but where are the socks? Step 5 is a partitioned drawer full of nicely-organized socks. Measure Names is like the partitioned sock drawer. Measure Values is like the socks. Independent of one another, they aren't of much use. Used together, they can be applied in many different ways.

Exercise: Measure Names and Measure values shortcuts

Tableau provides various shortcuts to quickly create a desired visualization. If you're new to the software, this shortcut behavior may not seem intuitive. But with a little practice and a few pointers, you'll quickly gain an understanding of it. Let's use the following exercise to explore how you can use a shortcut to rapidly deploy Measure Names and Measure Values:

  1. In the workbook associated with this chapter, navigate to the MeasureNames/Values ShrtCts worksheet.

 

  1. Drag Age directly on top of the Pay Rate number in the view (Show Me appears):
  1. Observe the results, including the appearance of the Measure Values shelf, and the deployment of Measure Names on the Rows and Filters shelves and Measure Values on the Text shelf:

 

Exercise: commentary

Several things happened in step 2 of the Measure Names and Measure Values shortcuts exercise. After placing Age on top of the Pay Rate number in the view, Tableau did the following:

  1. Deployed Measure Names on the Filters shelf.
    • Open the Measure Names filter and observe that only Age and Pay Rate are selected. This limits the view to display only those two measures.
  1. Deployed Measure Names on the Rows shelf.
    • Measure Names is acting like a partitioned container, that is, like the sock drawer in the analogy. Because of the filter, the only rows that display are for Age and Pay Rate.
  1. Displayed the Measure Values shelf.
    • The Measure Valuesshelf is somewhat redundant. Although it clearly shows the measures that display in the view, it essentially acts as an easy way to access the filter. You can simply drag measures on and off of theMeasure Valuesshelf to adjust the filter and thus display/hide additional Measure Values. You can also change the order within theMeasure Valuesshelf to change the order of the measures in the view.
  1. Deployed Measure Values on the Text shelf.
    • Measure Values is simply defining the numbers that will display for each row; in this case, the numbers associated with Age and Pay Rate.

If the visualization has an axis, the shortcut to deploy Measure Names and Measure Values requires the placement of a second measure on top of the axis of an initial measure, as follows:

 

 

Three essential Tableau concepts


The road to mastering Tableau begins with three essential concepts. We'll discuss each of the following concepts:

  • Dimensions and Measures
  • Row Level, Aggregate Level, Table Level
  • Continuous and Discrete

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 of Hire). A dimension is usually a text, Boolean, or date field, but may also be a number, such as Pay Rate. Dimensions provide meaning to numbers by slicing those numbers into separate parts/categories. Measures without dimensions are mostly meaningless.

Exercise: dimensions and measures

Let's look at an example to better understand:

  1. In the workbook associated with this chapter, navigate to the Dimensions and Measures worksheet.
  2. Drag Number of Records to the Rows shelf.

 

  1. Place Date of Hire and Department on the Columns shelf:

The result of step 2 is mostly meaningless. The Number of Records measure is about 302, but without the context supplied by slicing the measure with one or more dimensions, there is really no way to understand what it means. Step 2 brings meaning. Placing Date of Hire and Department on the Columns shelf provides context, which imparts meaning to the visualization.

Row level, aggregate level, table level

There are three levels of calculations in Tableau: Row, Aggregate, and Table. To understand how these three levels function, it's important to know the Tableau process flow.

 

We can see the process flow in the following diagram:

Let's follow the flow to understand where the three levels of calculations take place. We'll do so with an example that considers the Number of Records and Quantity fields. Assuming we're using SQL, consider the following calculation types, calculated fields, and queries. Note that the SQL is slightly simplified for the sake of this example.

Let's take a deeper look at the three levels of calculations and consider the example in the following table:

Calculation type

Calculated field in Tableau

Query passed to data source

Aggregate level

Sum([Number of Records])/Sum(Quantity)

SELECT SUM([Profit]), SUM(Sales) FROM [Orders]

Table level

WINDOW_AVG(Sum([Number of Records])/Sum(Quantity))

SELECT SUM([Profit]), SUM(Sales) FROM [Orders]

 

For the Row- and Aggregate-level calculations, the computation is actually completed by the data source engine. Tableau merely displays the results. This, however, isn't the case for the Table-level calculation. Although the query passed to the data source for the Table-level calculation is identical to the query for the Aggregate-level calculation, Tableau performs additional computations on the returned results. Let's explore this further with an exercise using the same calculated fields.

 

Exercise: row level, aggregate level, table level

Let us look at the following steps and begin our exercise:

  1. In the workbook associated with this chapter, navigate to the Row_Agg_Tbl worksheet.
  2. Select Analysis > Create Calculated Field to create the following calculated fields. Note that each must be created separately, that is, it isn't possible in this context to create a single calculated field that contains all three calculations:

Name

Calculation

Lev – Row

[Number of Records]/[Quantity]

Lev – Agg

SUM ([Number of Records])/SUM (Quantity)

Lev – Tab

WINDOW_AVG ([Lev - Agg])

 

  1. In the Data pane, right-click on the three calculated fields you just created and select Default Properties | Number format.
  2. In the resulting dialog box, select Percentage and click OK.
  3. Place Order Date on the Columns shelf.
  4. Place Measure Names on the Rows shelf, and Measure Values on the Text shelf.
  5. Exclude all values except for Lev - Row, Lev - Agg, and Lev - Tab:

 

Exercise: commentary

Lev - Agg is an aggregate-level calculation. The computation is completed by the data source engine. The sum of [Number of Records] is divided by the sum of [Quantity]. The results of the calculation are likely useful for the Tableau author.

Lev - Row is a row-level calculation. The computation is completed by the data source engine. [Number of Records] is divided by [Quantity] for each row of the underlying data. The results are then summed across all rows. Of course, in this case, the row-level calculation doesn't provide useful results; however, since a new Tableau author may mistakenly create a row-level calculation when an aggregate-level calculation is what's really needed, the example is included here.

Lev - Tab is a table calculation. Some of the computation is completed by the data source engine, that is, the aggregation. Tableau completes additional computation on the results returned from the data source engine. Specifically, the results of Lev - Agg are summed and then divided by the number of members in the dimension. For the preceding example, this is (26.29% + 26.34% + 26.30% + 26.55%)/4. Once again, the results in this case aren't particularly helpful but do demonstrate knowledge the budding Tableau author should possess.

Continuous and discrete

Continuous and discrete aren't concepts that are unique to Tableau. Indeed, both can be observed in many arenas. Consider the following example:

The preceding diagram is of two rivers: River-Left and River-Right. Water is flowing in River-Left. River-Right is composed of ice cubes. Could you theoretically sort the ice cubes in River-Right? Yes! Is there any way to sort the water in River-Left? In other words, could you take buckets of water from the bottom of the river, cart those buckets upstream and pour the water back into River-Left and thereby say, I have sorted the water in the river? No. The H2O in River-Left is in a continuous form, that is, water. The H2O in River-Right is in a discrete form, that is, ice.

 

 

Having considered continuous and discrete examples in nature, let's turn our attention back to Tableau. Continuous and discrete in Tableau can be more clearly understood with the following seven considerations:

  • Continuous is green. Discrete is blue:
    • Select any field in the Datapane or place any field on a shelf and you'll note that it's either green or blue. Also, the icons associated with fields are either green or blue.
  • Continuous is always numeric. Discrete may be a string.
  • Continuous and discrete aren't synonymous with dimension and measure:
    • It's common for new Tableau authors to conflate continuous with measure and discrete with dimension. They aren't synonymous. A measure may be either discrete or continuous. Also, a dimension, if it's a number, may be discrete or continuous. To prove this point, right-click on any numeric or date field in Tableau and note that you can convert it:
  • Discrete values can be sorted. Continuous values can't:
    • Sortable/Not sortable behavior is most easily observed with dates, as shown in the following example:
  • Continuous colors are gradients. Discrete colors are distinct.
    • The following example shows Profit as continuousand then as discrete. Note the difference in how colors are rendered. The left portion of the screenshot demonstrates that continuous results in gradients, and the right portion demonstrates that discrete results in distinct colors:

 

  • Continuous pills can be placed to the right of discrete pills, but not to the left.
    • The Tableau author is able to place Region to the right of Year when Year is discrete.
    • The Tableau author is unable to place Regionto the right of Year when Year is continuous:
  • Continuous creates axes. Discrete creates headers:
    • Note in the left portion of the following screenshot that Year(Order Date)is continuous and theYear of Order Dateaxis is selected. Since Year of Order Date is an axis, the entire x-plane is selected. In the right portion of the following screenshot,Year(Order Date)is discrete and 2012 is selected. Since 2012 is a header only, it's selected and not the entire x-plane:

 

 

Exporting data to other devices


Once a Dashboard looks as it's expected to, the developer has different choices of sharing the work. An upload to the 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, the Tableau Creator has the option to take a look at Device Designer or Device Preview. You can find it here: 

Please be aware that you can only use the sheets that are in the default layout of your Dashboard. Once you're in the Device Designer mode, select a Device type and you'll get choices of the most common Models:

 

 

 

 

 

 

A cellphone is usually designed in portrait orientation. Now move the content in a way that the sheets you want to see on your phone are within the device frame. Satisfied? Then add this layout (top-right corner) to the workbook. It will appear under the Default one on the top-left side:

The user can now select the design needed, whenever opening a Workbook from the Tableau Server.

A Tablet Dashboard works exactly the same as the cellphone one. Follow the preceding steps to create it, except you have to choose the Tablet Device Type of course and a Tablet's Dashboard is usually in Landscape orientation. 

 

 

Summary


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, how to override that behavior, and we considered best practices. Then we reviewed Measure Names and Measure Values. 

After that, we explored three essential Tableau concepts: Dimensions and Measures, Row-, Aggregate-, and Table-level, and 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.

In the next chapter, we'll continue our Tableau exploration by looking at data. We'll explore how to prepare data for Tableau by looking at joins, blends, and data structures, such as data densification, cubes, and big data.

About the Authors

  • Marleen Meier

    Marleen Meier has worked in the field of data science and business intelligence since 2013. Her experience includes Tableau training, proof of concepts, implementations, project management, user interface designs, and quantitative risk management. In 2018, she was a speaker at the Tableau conference, where she showcased a machine learning project. Marleen uses Tableau, combined with other tools and software, to get the best business value for her stakeholders. She is also very active within the Tableau community, and recently joined the Dutch Tableau user group as one of their four leaders.

    Browse publications by this author
  • David Baldwin

    David Baldwin has provided consultancy services in the business intelligence sector for 17 years. His experience includes Tableau training and consulting, developing BI solutions, project management, technical writing, and web and graphic design. His vertical industry experience includes the financial, healthcare, human resource, aerospace, energy, education, government, and entertainment sectors. As a Tableau trainer and consultant, David enjoys serving a variety of clients throughout the USA. Tableau provides David with a platform that collates his broad experience into a skill set that can service a diverse client base.

    Browse publications by this author

Latest Reviews

(3 reviews total)
It lacks the flow and needs to be sharper in terms of explaining the concept
il libro può anche essere buono ma è molto basato sui workbook allegati e io ho molte difficoltà nell'utilizzare il materiale allegato. i workbook a volte sembrano incompleti, vengono richiamate pagine che non esistono (e i richiami nel testo sono anche sono vaghi).
Great book. Concise and easy to follow.

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Python Machine Learning - Third Edition

Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.

By Sebastian Raschka and 1 more