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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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Using filters wisely


Filters generally improve performance in Tableau. For example, when using a dimension filter to view only the West region, a query is passed to the underlying data source, resulting in returned information for only that region. By reducing the amount of data returned, performance improves. Basically, this is because less data means reduced network bandwidth load, reduced database processing requirements, and reduced processing requirements for the local computer.

Filters can also negatively impact Tableau's performance. For example, using only relevant values causes additional queries to be sent to the underlying data source, thus slowing the response time. Also, creating quick filters from high-cardinality dimensions can slow performance.

Navigating filter usage so as to maximize efficient usage and minimize inefficient usage will be the focus of this section.

Extract filter performance

Extract filters remove data from the extracted data source. Simply put, the data isn...

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