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

Tableau and big data


Perhaps the first challenge of big data is defining it adequately. It's a term so widely used as to be almost meaningless. For example, some may refer to data exceeding 1,048,576 rows as big data (that is, the row limit in Excel 2010 and 2013), while others would only apply the term to datasets in the multiple petabyte range. Definitions found on Wikipedia and Webopedia are so broad as to encompass both of these examples.

Note

Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate: https://en.wikipedia.org/wiki/Big_data

Big data is a buzzword, or catch-phrase, meaning a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques: http://www.webopedia.com/TERM/B/big_data.html

True, we should probably not consider data that merely exceeds Excel's row limitation as big data; nevertheless, from the perspective of the...