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

Summary


We began this chapter with a discussion of data densification and discovered that there are two types of data densification: domain completion and domain padding. While reviewing these two types of data densification, we learned how to how each can be deployed, when each is useful, and when each can be a problem.

Next, we learned how to work with cubes. Tableau knowledge base articles were discussed, as well additional techniques using data blending to address some of the limitations that are inherent when accessing cubes as data sources.

Lastly, we explored big data. We surveyed Massively Parallel Processing (MPP) and walked through an example of using Tableau to connect to Google BigQuery.

Having completed three chapters of data-centric discussion, we will discuss table calculations in the next chapter. We will focus that discussion on directional and non-directional table calculation functions, as well as partitioning and addressing.