Book Image

Mastering Tableau

By : David Baldwin
Book Image

Mastering Tableau

By: David Baldwin

Overview of this book

Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0. You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool’s inner workings and creatively exploring possibilities. You’ll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently. By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau.
Table of Contents (18 chapters)
Mastering Tableau
Credits
About the Author
www.Packtpub.com
Preface

About data densification


Data densification is a largely undocumented aspect of Tableau that can be useful in many circumstances but can also be confusing when encountered unexpectedly. This section will provide information about data densification with the intent of dispelling confusion and providing the Tableau author with sufficient knowledge to use this feature advantageously.

To begin to understand data densification, four terms should be defined. Data densification, sparse data, domain completion, and domain padding. The first two terms will be defined immediately, and the last two within the context of the rest of this section of the chapter. In addition to the definitions, each term will be discussed in detail via examples to help improve understanding.

Note

Data densification: A behavior wherein Tableau displays marks in the view for which there is no corresponding underlying data. Sparse data: An intersection of one or more dimensions and one measure for which there is no value.

Domain...