Book Image

Tableau 10 Complete Reference

By : Joshua N. Milligan, Tristan Guillevin
Book Image

Tableau 10 Complete Reference

By: Joshua N. Milligan, Tristan Guillevin

Overview of this book

Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You’ll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: • Learning Tableau 10 - Second Edition by Joshua N. Milligan • Getting Started with Tableau 2018.x by Tristan Guillevin
Table of Contents (20 chapters)
Title Page
About Packt
Contributors
Preface
8
Deeper Analysis - Trends, Clustering, Distributions, and Forecasting
Index

Visualizing multiple axes to compare different measures


Often, you'll need to use more than one axis to compare different measures, understand the correlation, or analyze the same measure at different levels of detail. In these cases, you'll use the visualizations with more than one axis.

Scatterplot

A scatterplot is an essential visualization type for understanding the relationship between the two measures. Consider a scatterplot when you find yourself asking questions such as:

  • Does how much I spend on marketing really make a difference in sales?
  • How much does power consumption go up with each degree of heating/cooling?
  • Is there any correlation between hours of study and test performance?

Each of these questions seeks to understand the correlation (if any) between two measures. Scatterplots are great for seeing these relationships and also for locating outliers.

Consider the following scatterplot that looks at the relationship between the measures: the sum of Sales (on the X axis) and the sum...