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

Chapter 9. Making Data Work for You

Up to this point, most of the examples we've looked at in this book assume that data is well structured and fairly clean. Data in the real world isn't so pretty at times. Maybe it's messy or it doesn't have a good structure. It may be missing values or have duplicate values. It might be at the wrong level of detail.

How can you deal with this messy data? Tableau offers quite a bit of flexibility for addressing data issues within the tool. We'll take a look at some of the features and techniques that will enable you to overcome data structure obstacles. Having a good understanding of what data structures work well with Tableau is the key to understanding how you will be able to resolve certain issues.

In this chapter, we'll focus on some principles for structuring data to work well with Tableau, as well as some specific examples of how to address common data issues. This chapter will cover the following topics:

  • Structuring data for Tableau
  • Techniques for dealing...