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Data Engineering with dbt

You're reading from   Data Engineering with dbt A practical guide to building a cloud-based, pragmatic, and dependable data platform with SQL

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781803246284
Length 578 pages
Edition 1st Edition
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Author (1):
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Roberto Zagni Roberto Zagni
Author Profile Icon Roberto Zagni
Roberto Zagni
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Table of Contents (21) Chapters Close

Preface 1. Part 1: The Foundations of Data Engineering
2. Chapter 1: The Basics of SQL to Transform Data FREE CHAPTER 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

Master Data management

When we refer to Master Data, we are talking about the descriptive data that is at the core of an organization and the processes to ensure that we can understand when different units are referring to the same instance of a concept.

To many extents, Master Data in the data platform realm overlaps with the dimensions that describe the organization concepts, such as customer, product, employee, and so on.

The rare times when we have a Master Data dimension, it adds the semantic of containing the “golden records” selected to represent the instances of the business concept (that is, the entity) represented by the dimension.

As an example, the product MD dimension (MDD_PRODUCT for us in the REF layer) contains the golden records of the products, starting from the codes used as the PK of the entity and continuing with the values of the columns.

Quite often, we will have only a list of MD codes, eventually with names, and mapping tables that...

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