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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

Concepts

Author (1):

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

Why subscribe?

20. Other Books You May Enjoy

Enhancing Software Quality

In this chapter, you will discover and apply more advanced patterns that provide high-quality results in real-life projects, and you will experiment with how to evolve your code with confidence through refactoring.

Through the selection of small use cases around our sample project, you will learn how to save the history of changes of your entities in a very efficient way, how to detect deleted rows from a source, and how to use window functions to leverage the data stored in HIST tables to analyze data evolution over time.

In the last section of this chapter, you will create and apply a macro to properly handle the orphans keys in your facts using self-completing dimensions to produce better quality facts and dimensions for your data marts.

In this chapter, you will learn about the following topics:

Refactoring and evolving models
Implementing real-world code and business rules
Publishing dependable datasets

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Authors (1)

Roberto Zagni

Roberto Zagni is a senior leader with extensive hands-on experience in data architecture, software development and agile methodologies. Roberto is an Electronic Engineer by training with a special interest in bringing software engineering best practices to cloud data platforms and growing great teams that enjoy what they do. He has been helping companies to better use their data, and now to transition to cloud based Data Automation with an agile mindset and proper SW engineering tools and processes, aka DataOps. Roberto also coaches data teams hands-on about practical data architecture and the use of patterns, testing, version control and agile collaboration. Since 2019 his go to tools are dbt, dbt Cloud and Snowflake or BigQuery.

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