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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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Complex joins

The terms simple join and complex join mean different things in different contexts. For our purposes, we will consider a simple join to be a single join between two tables. Every other instance of joining will be considered complex.

Let's look at a star schema as an example of a complex join:

Complex joins

A star schema consists of a fact table referencing one or more dimension tables. The fact table typically contains measures, whereas dimension tables, as the name suggests, contain dimensions. Star schemas are an important part of data warehousing, since their structure is optimal for reporting.

The star schema pictured is based on the Adventure Works data warehouse for MS SQL Server 2014. The workbook associated with this chapter does not include the SQL Server database. Also, to keep the file size of the workbook small, the extract has been filtered to only include data for the United Kingdom. Access to the database may prove helpful when working through some of the exercises in...

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