Book Image

The Tableau Workshop

By : Sumit Gupta, Sylvester Pinto, Shweta Sankhe-Savale, JC Gillet, Kenneth Michael Cherven
Book Image

The Tableau Workshop

By: Sumit Gupta, Sylvester Pinto, Shweta Sankhe-Savale, JC Gillet, Kenneth Michael Cherven

Overview of this book

Learning Tableau has never been easier, thanks to this practical introduction to storytelling with data. The Tableau Workshop breaks down the analytical process into five steps: data preparation, data exploration, data analysis, interactivity, and distribution of dashboards. Each stage is addressed with a clear walkthrough of the key tools and techniques you'll need, as well as engaging real-world examples, meaningful data, and practical exercises to give you valuable hands-on experience. As you work through the book, you'll learn Tableau step by step, studying how to clean, shape, and combine data, as well as how to choose the most suitable charts for any given scenario. You'll load data from various sources and formats, perform data engineering to create new data that delivers deeper insights, and create interactive dashboards that engage end-users. All concepts are introduced with clear, simple explanations and demonstrated through realistic example scenarios. You'll simulate real-world data science projects with use cases such as traffic violations, urban populations, coffee store sales, and air travel delays. By the end of this Tableau book, you'll have the skills and knowledge to confidently present analytical results and make data-driven decisions.
Table of Contents (12 chapters)
Preface

Introduction

Often, the data sources required for Tableau visualizations are stored in separate tables or files. A very common example is that of an online order on an e-commerce website. The order information and the customer information are stored separately within the website database. However, when suggestions are provided based on previous purchases, the website might combine the information to show a unified view. This is a very simple example of a data join, which is one of the most common scenarios that can be fulfilled using data preparation techniques. In addition to data joining, there is often a need to perform data manipulation activities such as grouping and adding calculations on the data being used. In this chapter, you will learn about using all such techniques to pull the data into Tableau for effective analysis and visualization.