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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

Adding new rows

As mentioned in Chapter 3, in the Using Tableau Prep Builder to connect to data section, please make a note of the directory name where you have stored these files: Mobile Phone Plans.xlsx and Bad Measures.xlsx.

In this section, we will explore adding new rows when the level of detail (LOD) of the source data is higher than the level we need to analyze. Looking at the data in the Mobile Phone Plans.xlsx file, as shown in Figure 5.1, we can see data that is easy to understand. We have the customer’s name, the plan they have enrolled in, their monthly plan charge, the number of years of their contract, and the start date of their contract. However, while the data is easy to understand by viewing it, it is not easily consumable for analytical purposes. Imagine the difficulty of answering questions such as, “How many of these customers are still active on January 1, 2023?” or “How much money will we be collecting in the third quarter of 2023...

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Data Modeling with Tableau
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