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 explored data access and data security on the Tableau platform. We began by adding users and groups to Tableau Server or Cloud.

We spent time creating and using Tableau projects to manage data models and content access and capabilities. We learned that locked projects are the best practice for managing access to data models across an organization.

Then, we looked at managing access to the data inside models using RLS. We saw how RLS works using manual user filters and adding users by using entitlements tables. Then, we discussed the pros and cons of each approach.

In the final two sections of this chapter, we looked at Tableau virtual connections and native database security to manage secure user access to the data within our data models.

We will look at data modeling considerations for Ask Data and Explain Data in the next chapter. These are machine learning capabilities for casual users that work best when our data models are tailored for each...