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Data Engineering with dbt

You're reading from  Data Engineering with dbt

Product type Book
Published in Jun 2023
Publisher Packt
ISBN-13 9781803246284
Pages 578 pages
Edition 1st Edition
Languages
Author (1):
Roberto Zagni Roberto Zagni
Profile icon Roberto Zagni

Table of Contents (21) Chapters

Preface 1. Part 1: The Foundations of Data Engineering
2. Chapter 1: The Basics of SQL to Transform Data 3. Chapter 2: Setting Up Your dbt Cloud Development Environment 4. Chapter 3: Data Modeling for Data Engineering 5. Chapter 4: Analytics Engineering as the New Core of Data Engineering 6. Chapter 5: Transforming Data with dbt 7. Part 2: Agile Data Engineering with dbt
8. Chapter 6: Writing Maintainable Code 9. Chapter 7: Working with Dimensional Data 10. Chapter 8: Delivering Consistency in Your Data 11. Chapter 9: Delivering Reliability in Your Data 12. Chapter 10: Agile Development 13. Chapter 11: Team Collaboration 14. Part 3: Hands-On Best Practices for Simple, Future-Proof Data Platforms
15. Chapter 12: Deployment, Execution, and Documentation Automation 16. Chapter 13: Moving Beyond the Basics 17. Chapter 14: Enhancing Software Quality 18. Chapter 15: Patterns for Frequent Use Cases 19. Index 20. Other Books You May Enjoy

Conceptual, logical, and physical data models

Data models can be designed with slightly different notations, but no matter how you design them, a model that describes everything in your data project would be as complex as your database and become too big to be useful as a communication tool.

Furthermore, when working on a data engineering project, you have discussions with different people, and these discussions focus on different levels of detail with respect to the data, business, and technical aspects of the project.

It is common to refer to the following three types of data models, which differ in the level of detail:

  • Conceptual data model: This is the most abstract model, defining what will be in the domain of the project, providing the general scope
  • Logical data model: This model provides much greater detail, defining what the data will look like
  • Physical data model: This is the most detailed model, describing exactly how the data will be stored in the database...
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