#### 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.
Preface
Part 1: Introduction to Tableau
Free Chapter
Chapter 1: Tableau Desktop Specialist Certification Overview
Chapter 2: Data Ingestion
Chapter 3: How to Interpret Data in a Tableau Visualization
Chapter 4: Working with Dimensions, Measures, and Marks (Oh My)
Chapter 5: Calculations and Functions Syntax
Part 2: Mastering the Exam
Chapter 6: Connecting to and Preparing Data
Chapter 7: Understanding and Creating Fundamental Charts in Tableau
Chapter 8: Data Organization and Worksheet Analytics
Chapter 9: Sharing Insights
Part 3: The Final Prep
Chapter 10: Exam Preparation
Chapter 11: Mock Test
Index
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# Data measures

Data measures provide the meaning behind the context. Measures make it possible to create graphic representations of what data dimensions cover. Figure 4.3 shows how dimensions and measures are defined in the Data section:

Figure 4.3 – The (faint) line separating dimensions and measures on each table in the Data pane. This snapshot comes from the Orders table in the Superstore dataset

Important number note

Figure 4.3 has a # field called Row ID. Although a number field defaults to a measure, it can be converted to a dimension. When converted to a dimension, it cannot be used to measure dimensions but can be converted back to a measure if needed.

Any string or geographic dimension can be converted to a measure, but that measure will be a count distinct from the former dimension. Other dimensional fields such as dates and Boolean cannot be converted to measures (unless a new calculated field is made).

The field representations...