Book Image

Mastering Tableau 2023 - Fourth Edition

By : Marleen Meier
Book Image

Mastering Tableau 2023 - Fourth Edition

By: Marleen Meier

Overview of this book

This edition of the bestselling Tableau guide will teach you how to leverage Tableau's newest features and offerings in various paradigms of the BI domain. Updated with fresh topics, including the newest features in Tableau Server, Prep, and Desktop, as well as up-to-date examples, this book will take you from mastering essential Tableau concepts to advance functionalities. A chapter on data governance has also been added. Throughout this book, you'll learn how to use Tableau Hyper files and Prep Builder to easily perform data preparation and handling, as well as complex joins, spatial joins, unions, and data blending tasks using practical examples. You'll also get to grips with executing data densification and explore other expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. Later chapters will teach you all about improving dashboard performance, connecting to Tableau Server, and understanding data visualization with examples. Finally, you'll cover advanced use cases, such as self-service analysis, time series analysis, geo-spatial analysis, and how to connect Tableau to Python and R to implement programming functionalities within Tableau. By the end of this book, you'll have mastered Tableau 2023 and be able to tackle common and advanced challenges in the BI domain.
Table of Contents (19 chapters)
17
Other Books You May Enjoy
18
Index

Integrating programming languages

How does integration empower Tableau? It happens through calculated fields. Tableau dynamically interfaces with Rserve or TabPy to pass values and receive results. And Tableau Prep Builder also has R and Python integration as we saw in Chapter 3, Using Tableau Prep Builder! So, let’s not waste any time and jump right in.

Basic Tableau-to-R and Tableau-to-Python integration is quite simple: the view shows data based on a calculated field, with the help of which Tableau pushes data to Rserve or TabPy respectively and then retrieves the results via a table calculation:

Figure 15.1: Tableau external services

Naturally, whether you are viewing a workbook on Tableau Desktop or via Tableau Server, if you wish to run R and Python calculations, then Rserve or TabPy must be accessible.

For a proper understanding of the integration, let’s also look at the Tableau/R workflow as an example. The terms used in the following diagram...