Book Image

Data Modeling with Tableau

By : Kirk Munroe
Book Image

Data Modeling with Tableau

By: Kirk Munroe

Overview of this book

Tableau is unlike most other BI platforms that have a single data modeling tool and enterprise data model (for example, LookML from Google’s Looker). That doesn’t mean Tableau doesn’t have enterprise data governance; it is both robust and highly flexible. This book will help you effectively use Tableau governance models to build a data-driven organization. Data Modeling with Tableau is an extensive guide, complete with step-by-step explanations of essential concepts, practical examples, and hands-on exercises. As you progress through the chapters, you’ll learn the role that Tableau Prep Builder and Tableau Desktop each play in data modeling. You’ll also explore the components of Tableau Server and Tableau Cloud that make data modeling more robust, secure, and performant. Moreover, by extending data models for Ask and Explain Data, you’ll gain the knowledge required to extend analytics to more people in their organizations, leading to better data-driven decisions. Finally, this book will guide you through the entire Tableau stack and the techniques required to build the right level of governance into Tableau data models for the correct use cases. By the end of this Tableau book, you’ll have a firm understanding of how to leverage data modeling in Tableau to benefit your organization.
Table of Contents (22 chapters)
1
Part 1: Data Modeling on the Tableau Platform
4
Part 2: Tableau Prep Builder for Data Modeling
9
Part 3: Tableau Desktop for Data Modeling
14
Part 4: Data Modeling with Tableau Server and Online

Summary

In this chapter, we learned about adding additional fields to our data model through the relationship feature in Tableau. Relationships give us flexibility by allowing us to create relationships at the logical layer of databases. With relationships, we leave the mapping of joining data at the physical layer for Tableau to create dynamically, depending on the field we use in our analyses.

We looked at how relationships are different than joins and various use cases for relationships where joins would result in multiple data models. We also looked at how performance options are available to optimize relationship query performance.

In the final section, we looked at adding additional rows to our data model by using manual and wildcard unions.

The next chapter will focus on creating joins in Tableau Desktop at the physical database layer. We will also explore geospatial joins and custom SQL.