Book Image

Learning Tableau 2022 - Fifth Edition

By : Joshua N. Milligan
Book Image

Learning Tableau 2022 - Fifth Edition

By: Joshua N. Milligan

Overview of this book

Learning Tableau 2022 helps you get started with Tableau and data visualization, but it does more than just cover the basic principles. It helps you understand how to analyze and communicate data visually, and articulate data stories using advanced features. This new edition is updated with Tableau’s latest features, such as dashboard extensions, Explain Data, and integration with CRM Analytics (Einstein Analytics), which will help you harness the full potential of artificial intelligence (AI) and predictive modeling in Tableau. After an exploration of the core principles, this book will teach you how to use table and level of detail calculations to extend and alter default visualizations, build interactive dashboards, and master the art of telling stories with data. You’ll learn about visual statistical analytics and create different types of static and animated visualizations and dashboards for rich user experiences. We then move on to interlinking different data sources with Tableau’s Data Model capabilities, along with maps and geospatial visualization. You will further use Tableau Prep Builder’s ability to efficiently clean and structure data. By the end of this book, you will be proficient in implementing the powerful features of Tableau 2022 to improve the business intelligence insights you can extract from your data.
Table of Contents (20 chapters)
18
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19
Index

Practical examples of calculations and parameters

Let’s turn our attention to some practical examples of row-level and aggregate calculations. The goal is to learn and understand some of what is possible with calculations. You will be able to build on these examples as you embark on your analysis and visualization journey.

A great place to find help and suggestions for calculations is the official Tableau forums at https://community.tableau.com/s/explore-forums.

Fixing data issues

Often, data is not entirely clean. That is, it has problems that need to be corrected before meaningful analysis can be accomplished. For example, dates may be incorrectly formatted, or fields may contain a mix of numeric values and character codes that need to be separated into multiple fields. Calculated fields can often be used to fix these kinds of issues.

We’ll consider using Tableau Prep—a tool designed to shape and cleanse data—in Chapter...