Book Image

Mastering Tableau 2019.1 - Second Edition

By : Marleen Meier, David Baldwin
Book Image

Mastering Tableau 2019.1 - Second Edition

By: Marleen Meier, David Baldwin

Overview of this book

Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you’ll be able to handle and prepare data easily. You’ll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you’ll learn how to perform data densification to make displaying granular data easier. Next, you’ll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you’ll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you’ll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB. By the end of this book, you’ll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain.
Table of Contents (20 chapters)
Free Chapter
1
Section 1: Tableau Concepts, Basics
9
Section 2: Advanced Calculations, Mapping, Visualizations
16
Section 3: Connecting Tableau to R, Python, and Matlab

Summary

We started this chapter with an introduction to Tableau Prep. We looked at the GUI and how we can connect data to it. After that, we did a lot of exercises regarding data preparation. This part can be divided in four parts: data cleaning, unions and joins, aggregation, and last but not least, pivoting. To round up this chapter on Tableau Prep, we looked at exporting data as the final topic. Here, we saw that the new dataset can be saved as a file, a data extract, or can be pushed directly to the Tableau Server.

Just like Tableau Desktop, Tableau Prep is very much self-explanatory and highly visual. Colors, symbols, and highlights make it easy to get used to this Extract, transform, and load tool. In the next chapter, we will focus on joins again, but this time, in Tableau Desktop itself. Along with this, we'll examine both data blending and data structures.

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