Data Modeling with Tableau: A practical guide to building data models using Tableau Prep and Tableau Desktop - Couverture souple

Munroe, Kirk

 
9781803248028: Data Modeling with Tableau: A practical guide to building data models using Tableau Prep and Tableau Desktop

Synopsis

Save time analyzing volumes of data using best practices to extract, model, and create insights from your data

Key Features

  • Master best practices in data modeling with Tableau Prep Builder and Tableau Desktop
  • Apply Tableau Server and Cloud to create and extend data models
  • Build organizational data models based on data and content governance best practices

Book Description

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 very flexible. This book will help you build a data-driven organization with the proper use of Tableau governance models.

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 will 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 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 get into the entire Tableau stack and get the techniques required to build the right level of governance into Tableau data models for the right 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.

What you will learn

  • Showcase Tableau published data sources and embedded connections
  • Apply Ask Data in data cataloging and natural language query
  • Exhibit features of Tableau Prep Builder with hands-on exercises
  • Model data with Tableau Desktop through examples
  • Formulate a governed data strategy using Tableau Server and Cloud
  • Optimize data models for Ask and Explain Data

Who this book is for

This book is for data analysts and business analysts who are looking to expand their data skills, offering a broad foundation to build better data models in Tableau for easier analysis and better query performance.

It will also benefit individuals responsible for making trusted and secure data available to their organization through Tableau, such as data stewards and others who work to take enterprise data and make it more accessible to business analysts.

Table of Contents

  1. Introducing Data Modeling in Tableau
  2. Licensing Considerations and Types of Data Models
  3. Data Preparation with Tableau Prep Builder
  4. Data Modeling Functions with Tableau Prep Builder
  5. Advanced Modeling Functions in Tableau Prep Builder
  6. Data Output from Tableau Prep Builder
  7. Connecting to Data in Tableau Desktop
  8. Building Data Models Using Relationships
  9. Building Data Models at the Physical Level
  10. Sharing and Extending Tableau Data Models
  11. Securing Data
  12. Data Modeling Considerations for Ask Data and Explain Data
  13. Data Management with Tableau Prep Conductor
  14. Scheduling Extract Refreshes
  15. Data Modeling Strategies by Audience and Use Case

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

Kirk Munroe is a Tableau Certified Desktop Professional, Tableau Certified Data Analyst, Tableau Certified Partner Architect, and Tableau Certified Partner Consultant, with over 20 years of work experience in business analytics.

He is the co-founder of Paint with Data, a Tableau partner and visual analytics coaching consulting firm. Kirk works with clients to improve their analytics skills from data modeling to storytelling and presenting. Kirk has worked at analytics software companies, including Salesforce/Tableau, IBM/Cognos, and Kinaxis in senior roles in product management, marketing, sales enablement, and customer success.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.