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

Summary


This chapter covered foundational concepts of how Tableau works with data. Although you will not usually be concerned with the queries Tableau generates to query underlying data engines, having a solid foundational understanding of Tableau's paradigm will greatly aid you as you to analyze data.

We looked at multiple examples of different connections to different data sources, considered the benefits and potential drawbacks of using data extracts, considered how to manage metadata, dived into details on joins and blends, and finally considered options for filtering data.

Working with data is fundamental to everything you do in Tableau. Having an understanding of connecting to various data sources, working with extracts, customizing metadata, and the difference between joins and blends will be the key as you begin deeper analysis and more complex visualizations, such as those covered in the next chapter.