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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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Introducing LODs

Tableau’s default is to show measures in a view based on the dimensions also present in the view. If you have a dashboard with Sales data and dimensions like State and City, and you drag the State and Sales data onto the view, the Sales data will be divided by State, showing you Sales per State. If you want to divide the Sales data further into smaller chunks, you might add the City field, resulting in Sales data per City, per State. LODs can manipulate this default behavior.

After completing this chapter, you will be able to divide or partition measures by dimensions that are not in the view and show measures using fewer dimensions than are visible in the view.

To do this, we will build and use two playgrounds. Delivering reports as required by one’s job duties may lead to a thorough knowledge of a limited set of capabilities; that is, a deep but narrow understanding. It can be difficult to set aside time (and justify that time) to explore...

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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