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Tableau Certified Data Analyst study guide : learn the core concepts and techniques necessary to ace the exam

By: ©2025Description: 343 pagesContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781098175078
Subject(s):
Genre/Form: LOC classification:
  • QA76.9.I52 2025
Summary: Gaining a Tableau Certified Data Analyst title is key to advertising your skill set in a data-hungry world. It advertises your ability to connect to, analyze, and describe data in an industry-leading data-visualization tool. This study guide provides example questions, terminology, walkthroughs, and best practices to help you learn key topics covered by this certification exam. Christopher Gardner, business intelligence analyst and lead Tableau developer for the University of Michigan, provides guidelines for first-time test-takers and a comprehensive review for Tableau veterans. You'll start by learning how to use Tableau's data Prep Builder and the Tableau Desktop software to connect to, prepare, manipulate, and combine datasets. Then you'll dive into the build interface to develop simple yet compelling data visualizations before moving into more complex topics such as table calculations, level-of-detail expressions, parameters, and predictive analytics tools
Item type: BOOKS
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Gaining a Tableau Certified Data Analyst title is key to advertising your skill set in a data-hungry world. It advertises your ability to connect to, analyze, and describe data in an industry-leading data-visualization tool. This study guide provides example questions, terminology, walkthroughs, and best practices to help you learn key topics covered by this certification exam. Christopher Gardner, business intelligence analyst and lead Tableau developer for the University of Michigan, provides guidelines for first-time test-takers and a comprehensive review for Tableau veterans. You'll start by learning how to use Tableau's data Prep Builder and the Tableau Desktop software to connect to, prepare, manipulate, and combine datasets. Then you'll dive into the build interface to develop simple yet compelling data visualizations before moving into more complex topics such as table calculations, level-of-detail expressions, parameters, and predictive analytics tools

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