Preface

Tableau Prep is a relatively new tool for data preparation. It is designed around a core set of data preparation capabilities such as cleaning, joining, and aggregating data in preparation for analysis. Tableau Prep leverages a modern and intuitive user interface to allow you to create new data flows quickly and efficiently in a fraction of the time it may have taken in traditional, complex ETL tools.

In this book, you'll learn how to perform key actions in Tableau Prep, in order to build your own data flow, from data ingestion, cleaning, and transforming, to creating an output for data analysis.

Who this book is for

This book is for business intelligence professionals, data analysts, and Tableau users looking to learn Tableau Prep essentials and create data pipelines or ETL processes using it. Basic knowledge of data management will be beneficial to understand the concepts covered in this Tableau Prep cookbook more effectively.

What this book covers

Chapter 1, Getting Started with Tableau Prep, runs through the various use cases in which you can employ Tableau Prep as a tool for data analysis.

Chapter 2, Extract and Load Processes, explains how to connect to various data source types and write your output to different destinations.

Chapter 3, Cleaning Transformations, covers how to apply cleaning operations to your dataset, including filtering, validation, and splitting columns.

Chapter 4, Data Aggregation, looks at how to aggregate data using aggregation and grouping functions.

Chapter 5, Combining Data, addresses how to join various disparate datasets using join and union tools.

Chapter 6, Pivoting Data, looks at how to pivot the orientation of your data from columns to rows and vice versa.

Chapter 7, Creating Powerful Calculations, explains how to add calculated fields to your dataset.

Chapter 8, Data Science in Tableau Prep Builder, covers how to add R or Python code to your Tableau Prep data flow.

Chapter 9, Creating Prep Flows in Various Business Scenarios, lets you practice a full end-to-end flow creation using a variety of methods discussed in this book.

To get the most out of this book

You will need to have Tableau Prep Builder installed on your desktop, preferably the most recent version. All exercises in this book have been tested with version 2021.1 on Windows 10 and macOS Big Sur.

Note that Python, R, and RStudio are only required to complete the exercises in Chapter 8, Data Science in Tableau Prep Builder.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Tableau-Prep-Cookbook. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://static.packt-cdn.com/downloads/9781800563766_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Open the Tableau Prep Superstore flow to follow along with the steps outlined."

A block of code is set as follows:

IF [Segment] = "Consumer" THEN TRUE ELSE FALSE END

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "If you do have a product key, you can always add it via the Help menu under Manage Product Keys."

Tips or important notes

Appear like this.

Get in touch

Feedback from our readers is always welcome.

General feedback: If you have questions about any aspect of this book, mention the book title in the subject of your message and email us at [e-mail].

Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packtpub.com/support/errata, selecting your book, clicking on the Errata Submission Form link, and entering the details.

Piracy: If you come across any illegal copies of our works in any form on the Internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [e-mail] with a link to the material.

If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.

Reviews

Please leave a review. Once you have read and used this book, why not leave a review on the site that you purchased it from? Potential readers can then see and use your unbiased opinion to make purchase decisions, we at Packt can understand what you think about our products, and our authors can see your feedback on their book. Thank you!

For more information about Packt, please visit packt.com.