Book Image

Mastering Tableau 2021 - Third Edition

By : Marleen Meier, David Baldwin
Book Image

Mastering Tableau 2021 - Third Edition

By: Marleen Meier, David Baldwin

Overview of this book

Tableau is one of the leading business intelligence (BI) tools that can help you solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you’ll be able to perform data preparation and handling easily. You’ll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Next, you’ll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You’ll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within it. By the end of this Tableau book, you’ll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain.
Table of Contents (18 chapters)
16
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17
Index

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 information returned for just that region. By reducing the amount of data returned, performance improves. 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, thereby slowing down the response time. Also, creating quick filters from high-cardinality dimensions can impair performance.

Tableau's filters are executed in a specific order, so keep this in mind when using them. Refer to the Tableau help pages here: https://help.tableau.com/current/pro/desktop/en-us/order_of_operations.htm. The...