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You're reading from  Mastering Tableau 2023 - Fourth Edition

Product typeBook
Published inAug 2023
PublisherPackt
ISBN-139781803233765
Edition4th Edition
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Author (1)
Marleen Meier
Marleen Meier
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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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Measure Names and Measure Values

I’ve observed the following scenario frequently: a new Tableau author creates a worksheet and drags a measure to the Text shelf. They drag the second measure to various places on the view and get results that seem entirely unpredictable. The experience is very frustrating for the author since it’s so easy to accomplish this in Microsoft Excel! The good news is that it’s also easy to accomplish this in Tableau. It just requires a different approach.

Measure Names and Measure Values are generated fields in Tableau. They don’t exist in the underlying data, but they’re indispensable for creating many kinds of views. As may be guessed from its placement in the Data pane and its name, Measure Names is a dimension whose members are made up of the names of each measure in the underlying dataset. Measure Values contains the numbers or values of each measure in the dataset.

In this section, we’ll watch what happens...

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Mastering Tableau 2023 - Fourth Edition
Published in: Aug 2023Publisher: PacktISBN-13: 9781803233765

Author (1)

author image
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.
Read more about Marleen Meier