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
Deeper Analysis - Trends, Clustering, Distributions, and Forecasting

Visualizing dates and times

Often in your analysis, you will want to understand when something happened. You'll ask questions like:

  • When did we gain the newest customers?
  • What times of day have the highest call volume?
  • What kinds of seasonal trends do we see in sales and profit?

Fortunately, Tableau makes this kind of visual discovery and analysis easy.

The built-in date hierarchy

When you are connected to a flat file, relational, or extracted data source, Tableau provides a robust built-in date hierarchy for any date field.


Cubes/OLAP connections do not allow for Tableau hierarchies. You will want to ensure that all the date hierarchies and date values that you need are defined in the cube.

To see this in action, continue with the Chapter 03  workbook, navigate to the Built-in Date Hierarchy sheet, and create a view similar to the one shown here by dragging and dropping SUM(Sales) to Rows and YEAR(Order Date) to Columns:

Note that even though the Order Date field is a date, Tableau defaulted...