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Mastering Tableau

Mastering Tableau

By : Jen Stirrup, Baldwin
4.4 (10)
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Mastering Tableau

Mastering Tableau

4.4 (10)
By: Jen Stirrup, 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 (14 chapters)
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Chapter 3. All about Data – Joins, Blends, and Data Structures

Connecting Tableau to data often means more than connecting to a single table in a single data source. You may need to use Tableau to join multiple tables from a single data source. As of Tableau 10, you can also join tables from disparate data sources. Sometimes, you may need to merge data that does not share a common row-level key. In such cases, you will need to blend the data. Also, you may find instances where it is necessary to create multiple connections to a single data source in order to pivot the data in different ways. This may be required in order to discover answers to questions that are difficult or simply not possible to address with a single data structure.

In this chapter, we will discuss the following:

  • Complex joins
  • Data blending
  • Data structures

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