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Tableau 10 Complete Reference

You're reading from   Tableau 10 Complete Reference Transform your business with rich data visualizations and interactive dashboards with Tableau 10

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789957082
Length 496 pages
Edition 1st Edition
Tools
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Authors (2):
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Joshua N. Milligan Joshua N. Milligan
Author Profile Icon Joshua N. Milligan
Joshua N. Milligan
Tristan Guillevin Tristan Guillevin
Author Profile Icon Tristan Guillevin
Tristan Guillevin
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Table of Contents (20) Chapters Close

Title Page
About Packt
Contributors
Preface
1. Creating Your First Visualizations and Dashboard 2. Working with Data in Tableau FREE CHAPTER 3. Moving from Foundational to More Advanced Visualizations 4. Using Row-Level, Aggregate, and Level of Detail Calculations 5. Table Calculations 6. Formatting a Visualization to Look Great and Work Well 7. Telling a Data Story with Dashboards 8. Deeper Analysis - Trends, Clustering, Distributions, and Forecasting 9. Making Data Work for You 10. Advanced Visualizations, Techniques, Tips, and Tricks 11. Sharing Your Data Story 12. Catching Up with Tableau 2018 13. Deal with Security 14. How to Keep Growing Your Skills 1. Other Books You May Enjoy Index

Clustering


Tableau 10 introduces the ability to quickly perform clustering analysis in your visualizations. This allows you to find groups, or clusters, of individual data points that are similar based on any number of variables of your choosing. This can be useful in many different industries and fields of study, for example:

  • Marketing may find it useful to determine groups of customers related to each other based on spending amounts, frequency of purchases, times and days of orders, and so on
  • Patient care directors in hospitals may benefit from understanding groups of patients related to each other based on diagnoses, medication, length of stay, and number of read missions
  • Immunologists may search for related strains of bacteria based on drug resistance or genetic markers
  • Renewable energy professionals would like to pinpoint clusters of windmills based on energy production and then correlate that with geographic location

Note

Tableau uses a standard k-means clustering algorithm that will yield...

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