Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Learning Tableau 10

You're reading from   Learning Tableau 10 Business Intelligence and data visualization that brings your business into focus

Arrow left icon
Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781786466358
Length 432 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Joshua N. Milligan Joshua N. Milligan
Author Profile Icon Joshua N. Milligan
Joshua N. Milligan
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Creating Your First Visualizations and Dashboard FREE CHAPTER 2. Working with Data in Tableau 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

Practical examples of calculations and parameters


Let's turn our attention to some practical examples of calculations. These will be examples of Row Level and Aggregate Level calculations. These are merely examples. The goal is to learn and understand some of what is possible with calculations. You will be able to build on these examples as you embark on your analysis and visualization.

Note

A great place to find help and suggestions for calculations is the official Tableau forums at https://community.tableau.com/community/forums

Fixing data issues

Often, data is not entirely clean. That is, it has problems that need to be corrected before meaningful analysis can be accomplished. For example, dates may be incorrectly formatted or fields may contain a mix of numeric values and character codes that need to be separated into multiple fields. We'll look in depth at many ways of working with messy data in Chapter 9, Making Data Work for You.  Here, we'll consider how calculated fields can often...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime