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
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18
Index

Connecting to data sources

One of the beauties of Tableau is the ease with which you can connect to many different data sources in various ways. As mentioned earlier in this book, there are many connectors defined in Tableau for interfacing with a variety of data sources. Furthermore, this flexibility extends beyond simply connecting to single tables or files.

Although Tableau makes it easy to connect to various data sources, it should be stressed that Tableau is not an Extract, Transform, and Load (ETL) tool. If complex joins and complex data blending are required to generate useful results, it may be advisable to perform ETL work outside of Tableau, for example, in Tableau Prep Builder (see Chapter 3, Using Tableau Prep Builder, for more information on this service). ETL work will ideally lead to better data modeling and thus easier authoring and quicker performance in Tableau.

The four ways in which Tableau connects to data are as follows:

  • Tableau...