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

Example - regional scorecard


We'll consider another example dashboard which demonstrates slightly different objectives. Let's say everyone in the organization has agreed upon a key performance indicator of Profit Ratio KPI. Furthermore, there is consensus that the cut-off between an acceptable and poor profit ratio is 15.00% but management would like to have the option of adjusting the value dynamically to see if other targets might be better.

Consider the following dashboard:

This dashboard allows your audience to very quickly evaluate the performance of each region over the last 6 months. Executive management could very quickly pull this dashboard up on their mobile device and take appropriate action as needed.

The dashboard provides interactivity with the KPI target parameter. Additional means of drilling down into other dashboards or views could be provided if desired. If this view were published on Tableau Server, it is not unreasonable to think that regional managers might subscribe to...