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Mastering Tableau 2023

You're reading from Mastering Tableau 2023 Implement advanced business intelligence techniques, analytics, and machine learning models with Tableau

Product type Paperback

Published in Aug 2023

Publisher Packt

ISBN-13 9781803233765

Length 684 pages

Edition 4th Edition

Languages

Python

Tools

Tableau

Concepts

Business Intelligence

Author (1):

Marleen Meier

View More author details

Table of Contents (19) Chapters

Preface

1. Reviewing the Basics

2. Getting Your Data Ready FREE CHAPTER

3. Using Tableau Prep Builder

4. Learning about Joins, Blends, and Data Structures

5. Introducing Table Calculations

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

7. Practicing Level of Detail Calculations

8. Going Beyond the Basics

9. Working with Maps

10. Presenting with Tableau

11. Designing Dashboards and Best Practices for Visualizations

12. Leveraging Advanced Analytics

13. Improving Performance

14. Exploring Tableau Server and Tableau Cloud

15. Integrating Programming Languages

16. Developing Data Governance Practices

17. Other Books You May Enjoy

18. Index

Extending Tableau mapping with other technology

Next, we will consider how to extend Tableau’s mapping capabilities with other tools. Tableau’s developers were careful to create a mapping interface that is readily extensible. Some areas of this extensibility, such as connecting to a Web Map Service (WMS) server, are available directly from the interface; we’ll explore that next.

Using custom maps with a WMS

The easiest way to bring a custom map into Tableau is directly from Desktop. We need a properly formatted URL that points to a WMS server. Tableau Desktop can connect to any WMS server that supports the WMS 1.0.0, 1.1.0, or 1.1.1 standards.

A good place to find a list of such URLs is http://directory.spatineo.com, which provides information on a ton of different mapping services.

The following exercise was inspired by Jeffrey A. Shaffer’s article Building weather radar in Tableau in under 1 minute, which can be accessed here...

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Authors (1)

Marleen Meier

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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