Exploring GUI of Tableau Prep Builder  Exploring GUI of Tableau Prep Builder 
Tableau Prep Builder was introduced with version 2018.1 of Tableau Desktop, but what can we use Tableau Prep Builder (henceforth referred to in this article as Prep) for? The core purpose... Exploring GUI of Tableau Prep Builder 

Tableau Prep Builder was introduced with version 2018.1 of Tableau Desktop, but what can we use Tableau Prep Builder (henceforth referred to in this article as Prep) for? The core purpose of the tool is data preparation. The good news is, Prep is fully compatible with Tableau Desktop, and also with Tableau Server. That means you can execute jobs in Prep to clean your data with the click of a button. Additionally, Prep is as visual as its big brother, Tableau Desktop, meaning that you can see every step of data preparation in a fully visual format. 

This article is an excerpt taken from the book “Mastering Tableau 2021, Third Edition by Marleen Meier and David Baldwin – a guide to master your Tableau skills and become a BI expert. You learn to build advanced dashboards and improve your storytelling to derive key business insights. An all-in-one resource to become well versed with advanced functionalities of Tableau in the business intelligence domain. 

Therefore, let’s dive into the Graphical User Interface (GUI) and be amazed by another high-end product, which will allow you to get initial data insights, enabling you to decide faster if your dataset is worth analysis. Prep will pave the way for an even smoother Tableau Desktop experience. 

In this article, the following topics will be discussed: 

  • Connecting to data 
  • The Tableau Prep Builder GUI

In order to get started, we need to load data. How to do so in Prep will be described in the following section.  

Connecting to data

If you are familiar with Tableau Desktop, Tableau Prep Builder will be an easy game for you. The handling and interfaces are very similar, and connecting to data, if the connector is available in Prep, works all the same whether it’s a text file, a database, or an extract. At first sight, you might not even notice a difference between the Tableau Prep Builder and the Tableau Desktop GUI, which provides the handy advantage that you can start prepping right away.  

To get started, begin by opening Tableau Prep Builder:

Figure 1: Tableau Prep Builder  

From here, click on the + in order to open a file. After doing so, the following screen will appear: 

Figure 2: Connecting to data  

From the preceding screenshot, we can see that you can choose the type of data you want to connect to in the search bar. Just as in Tableau, the repertoire of Tableau Prep Builder includes multiple databases. 

Now let’s connect to a dataset with a practical exercise. For this exercise, we need the following dataset: https://www.kaggle.com/airbnb/boston. Please download calendar.csv, listings.csv, and reviews.csv.  

First, we are going to start with the calendar.csv file. Add it to the empty Prep canvas by making a connection with a text file, followed by the selection of your .csv file. You will now see the following screen:

Figure 3: Input data 

Congratulations—you’ve just made your first Tableau Prep Builder connection. Here, you can manipulate and visualize your connected dataset as required!

In the following section, I will describe the GUI in more detail.

The Tableau Prep Builder GUI 

User experience is an important topic, not only when you build a dashboard but also when you use other aspects of Tableau. One of the biggest selling points of Tableau is and has always been the ease of using the GUI, and is only one of the reasons Tableau is a much-loved tool by its customers.  

The Tableau Prep Builder GUI has two important canvases to look at. Right after you have connected data to Tableau Prep Builder, the workspace will split into several parts:

Figure 4: Prep workspace sections 

Let’s look at what we can see from the preceding screenshot: 

  • A: The connection pane, showing you the input files available at the location selected. 
  • B: The flow pane, which shows your current Prep flow. This always starts with an input step. 
  • C: The input pane settings, which give you several options to configure your input. 
  • D: The input pane samples, showing the fields you moved to the connection pane, including sample values. 

In the input pane (the section marked with C), you can use the wildcard union (multiple files) function to add multiple files from the same directory. Also, you can limit the sample set that Tableau Prep Builder will print in order to increase performance. In the input pane samples (the section marked with D) you can select and deselect the fields you want to import and change their data types. The data type options are, for example, strings, dates, or numbers.

https://odsc.com/california/#registerThe second GUI is the profile pane. Once you’ve selected the input data needed, click on the + in the flow pane and select Add: Clean Step. Now the profile pane will appear:

Figure 5: Cleaning data

In the preceding screenshot, the profile pane shows every column from the data source in two sections. The upper sections show aggregates. For example, column 2, date, shows the number of rows per date in a small histogram. The columns can all be sorted by clicking on the sort icon (a mini bar-chart that appears when your mouse is hovering over a column) next to the column name and by selecting one item. Let’s take, for example, True, in available (column 3). All related features will be highlighted:

Tableau Prep Builder

Figure 6: Visual filtering 

This gives you the chance to get some insights into the data before we even start to clean it up. In the following screenshot, each row is shown as it is in the data source in the lower part of the profile pane:

Tableau Prep Builder

Figure 7: Data overview

So far we have seen that, after loading data in Prep, visual filters can be applied by clicking on a field or bar in one of the columns. The lower pane will always show the data source of the selection made at the row level. Next, we will continue by adding more data sources.  

Getting to know Tableau Prep Builder 

Let’s start with a practical example. 

Next to the calendar.csvfile, connect to the following files: 

  • listings.csv 
  • reviews.csv 

Now, drag them onto the flow pane:

Tableau Prep Builder

Figure 8: Multiple tables input

Can you answer the following questions? 

  • How many listings use the word “beach” in their description? 
  • What is the percentage of condominiums that are marked with “exact location”? 
  • On which day were the most reviews entered? 

Without a tool like Tableau Prep Builder, it is much more difficult to find the solution to these types of questions. Prep makes our data analytics journey much faster and easier and that is exactly the reason why I encourage you to spend the additional time and learn Prep as well as Tableau Desktop! 

Here you see, as an example, I used the sort function on date in order to answer the third question: On which day were the most reviews entered?

Tableau Prep Builder

Figure 9: Sorting by date

As you can see, sorting this field ordered the dates by the number of entries, thus making it very simple to answer the question, on which day were the most reviews entered? After the first few clicks, it already starts to feel natural, doesn’t it?  


We started this article with an introduction to Tableau Prep Builder. We looked at the GUI and how we can connect data to it. Further in the book, you will perform exercises regarding data preparation. You will study data preparation in five parts: data cleaning, unions and joins, aggregating, pivoting, and scripting. Just like Tableau Desktop, Tableau Prep Builder is very much self-explanatory and highly visual. Colors, symbols, and highlights make it easy to get used to this extract, transform, and load tool, which is invaluable for preparing your data before manipulating it on the main Tableau interface! 

You’ll continue your exploration of data in Tableau in this book and explore how to prepare data for Tableau by looking at joins, blends, and data structures. 

About the Authors 

Marleen Meier has been working in the field of data science since 2013. Her experience includes Tableau training, proof of concepts, implementation, enablement as well as quantitative analysis, machine learning and AI. In 2018, she was a speaker at the Tableau conference, where she showcased an anomaly detection model using neural networks, visualized in Tableau.   

David Baldwin has been providing consulting in the business intelligence sector for 22 years. His experience includes Tableau training and consulting, developing BI solutions, project management, technical writing, and web and graphic design. His vertical experience includes financial, healthcare, human resources, aerospace, energy, education, government, and entertainment industries.

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