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Learning Tableau 2019

You're reading from   Learning Tableau 2019 Tools for Business Intelligence, data prep, and visual analytics

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781788839525
Length 504 pages
Edition 3rd Edition
Tools
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Author (1):
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Joshua N. Milligan Joshua N. Milligan
Author Profile Icon Joshua N. Milligan
Joshua N. Milligan
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Tableau Foundations FREE CHAPTER
2. Taking Off with Tableau 3. Working with Data in Tableau 4. Venturing on to Advanced Visualizations 5. Section 2: Leveraging the Full Power of Tableau
6. Starting an Adventure with Calculations 7. Diving Deep with Table Calculations 8. Making Visualizations That Look Great and Work Well 9. Telling a Data Story with Dashboards 10. Digging Deeper - Trends, Clustering, Distributions, and Forecasting 11. Section 3: Data Prep and Structuring
12. Cleaning and Structuring Messy Data 13. Introducing Tableau Prep 14. Section 4: Advanced Techniques and Sharing with Others
15. Advanced Visualizations, Techniques, Tips, and Tricks 16. Sharing Your Data Story 17. Other Books You May Enjoy

Structuring data for Tableau

We've already seen that Tableau can connect to nearly any data source. Whether it's a built-in direct connection, ODBC, or using the Tableau data extract API to generate an extract, no data is off limits. However, there are certain structures that make data easier to work with in Tableau.

There are two keys to ensuring a good data structure that works well with Tableau:

  • Every record of a source data connection should be at a meaningful level of detail
  • Every measure contained in the source should match the level of detail or possibly be at a higher level of detail, but should never be at a lower level of detail

For example, let's say you have a table of test scores with one record per classroom in a school. Within the record, you may have three measures: the average GPA for the classroom, the number of students in the class, and the...

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