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Mastering Tableau 2023 - Fourth Edition

You're reading from Mastering Tableau 2023 - Fourth Edition

Product type Book

Published in Aug 2023

Publisher Packt

ISBN-13 9781803233765

Pages 684 pages

Edition 4th Edition

Languages

Concepts

Business Intelligence

Author (1):

Marleen Meier

Table of Contents (19) Chapters

Preface

Reviewing the Basics

Getting Your Data Ready

Using Tableau Prep Builder

Learning about Joins, Blends, and Data Structures

Introducing Table Calculations

Utilizing OData, Data Densification, Big Data, and Google BigQuery

Practicing Level of Detail Calculations

Going Beyond the Basics

Working with Maps

Presenting with Tableau

Designing Dashboards and Best Practices for Visualizations

Leveraging Advanced Analytics

Improving Performance

Exploring Tableau Server and Tableau Cloud

Integrating Programming Languages

Developing Data Governance Practices

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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 being 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. The following flowchart, along with a link to an hour-long presentation, may help you grasp the concept fully...

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Authors (1)

Marleen Meier

Marleen Meier is an accomplished analyst and author with a passion for statistics and data. By using traditional methodologies and approaches such as Machine Learning and AI, Marleen is dedicated to driving meaningful insights. Currently working as the APAC Data CoE Lead for ABN AMRO Clearing, Marleen is at the forefront of innovation and implementing data-driven strategies in a global financial environment. She has lived and worked in multiple countries, including Germany, the Netherlands, the USA, and Singapore, allowing her to bring a diverse and global perspective to her work. Through her writing and speaking engagements, she aims to empower individuals and organizations to unlock the full potential of their data assets.

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