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

Chapter 8. Deeper Analysis - Trends, Clustering, Distributions, and Forecasting

Sometimes, quick data visualization needs a slightly deeper analysis. For example, a simple scatterplot can reveal outliers and correlation of values. But often you want to understand the distribution. A simple time series helps you see the rise and fall of a measure over time. But many times you want to see the trend or make predictions of future values.

Tableau enables you to quickly enhance your data visualizations with statistical analysis. Built-in features such as trending, clustering, distributions, and forecasting, allow you to quickly add value to your visual analysis. Additionally, Tableau integrates with R, an extensive statistical platform that opens up endless options for statistical analysis of your data. This chapter will cover the built-in statistical models and analysis.

This chapter will cover the following topics:

  • Trending
  • Clustering
  • Distributions
  • Forecasting

We'll take a look at these concepts in...