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Data Modeling with Tableau

Data Modeling with Tableau

By : Kirk Munroe
4.5 (14)
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Data Modeling with Tableau

Data Modeling with Tableau

4.5 (14)
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)
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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 the output options for Tableau Prep Builder.

The output to a flat file option works well when prototyping and when we are still in development and want to check our progress. It also meets the use case of creating a data model for our own analysis.

The Tableau published data source output is the best option when we are sharing our data model more broadly. It allows other analysts to connect to our data model without needing to recreate the work that went into the data modeling. It also allows us to have organizational definitions for data and standardized calculations, and allows us to decide which fields to make available for analysis.

The output to database table option allows us to leverage the enterprise security and scalability features of enterprise database servers. It also allows access to our model from tools and applications in addition to Tableau.

This was the final step of our Tableau Prep Builder learning, which started...

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Data Modeling with Tableau
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