Book Image

Tableau Desktop Specialist Certification

By : Adam Mico
Book Image

Tableau Desktop Specialist Certification

By: Adam Mico

Overview of this book

The Tableau Desktop Specialist certification is fundamental for any data visualization professional who works in the field with Tableau. This book gets you started by covering the exam format, Tableau basics, and best practices for preparing data for analysis and visualization. It also builds on your knowledge of advanced Tableau topics to get you up to speed with the essential domains and domain objectives. Although the guide provides an outline and starting point to key in on what needs to be understood before the examination, it also delivers in context to give you a strong understanding of each piece before taking the exam. Instructions on how to get hands on with examples, a common data source, and suggested elements are also included. Understanding the concepts will not only assist you in passing the examination, but will also help you work effectively with the tool in your workspace. By the end of this book, you'll be able to efficiently prepare for the certification exam with the help of mock tests, detailed explanations, and expert advice from the author.
Table of Contents (17 chapters)
Part 1: Introduction to Tableau
Part 2: Mastering the Exam
Part 3: The Final Prep

Grasping data dimensions

In the data dimensions section, we will look at data dimensions in the Superstore dataset to understand each one, how they can be used, and what they represent.

In Figure 4.1, you can see a snapshot of various data dimensions in one view:

Figure 4.1 – Data dimensions from Tableau’s Superstore dataset

Figure 4.1 – Data dimensions from Tableau’s Superstore dataset

As you can see, there are many items to consider when working with data dimensions. The following list breaks down the necessary components:

  1. Group: You can create groups for a single data dimension field. Groups are created manually and are identified by a paperclip in front of a field name. More information on creating and manipulating groups will be covered in Chapter 7.

Important group note

Groups can only be made with data dimensions and not data measures.

  1. String dimensions: String dimensions include an Abc identifier. They contain qualitative data that helps define the level of data aggregation...