Book Image

Tableau Cookbook - Recipes for Data Visualization

By : Shweta Sankhe-Savale
Book Image

Tableau Cookbook - Recipes for Data Visualization

By: Shweta Sankhe-Savale

Overview of this book

Data is everywhere and everything is data! Visualization of data allows us to bring out the underlying trends and patterns inherent in the data and gain insights that enable faster and smarter decision making. Tableau is one of the fastest growing and industry leading Business Intelligence platforms that empowers business users to easily visualize their data and discover insights at the speed of thought. Tableau is a self-service BI platform designed to make data visualization and analysis as intuitive as possible. Creating visualizations with simple drag-and-drop, you can be up and running on Tableau in no time. Starting from the fundamentals such as getting familiarized with Tableau Desktop, connecting to common data sources and building standard charts; you will walk through the nitty gritty of Tableau such as creating dynamic analytics with parameters, blended data sources, and advanced calculations. You will also learn to group members into higher levels, sort the data in a specific order & filter out the unnecessary information. You will then create calculations in Tableau & understand the flexibility & power they have and go on to building story-boards and share your insights with others. Whether you are just getting started or whether you need a quick reference on a “how-to” question, This book is the perfect companion for you
Table of Contents (18 chapters)
Tableau Cookbook – Recipes for Data Visualization
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Creating bins to bucket our data


When we get fields such as sales, profit, discount, and many more in either the Rows or Columns shelf, it creates an axis. However, at times, it is important to organize these continuous measures into discrete groups rather than just showing the individual values for each and every data point. For example, let's say we have a field that holds the age of people ranging from 10 to 90. Rather than showing each and every age in the view, we can bin the individual ages into age groups such as 10 to 25, 26 to 40 and so on. This helps us get an idea of the distribution of the population. The range of this distribution is called a Class Interval. Further, in order to visualize this distribution of data, we use a graphical representation called Histogram which was first introduced by Karl Pearson.

Thus, in other words, binning is a process of dividing the entire range of quantitative values into a series of small intervals and then counting how many values fall into...