Book Image

Data Engineering with dbt

By : Roberto Zagni
3 (1)
Book Image

Data Engineering with dbt

3 (1)
By: Roberto Zagni

Overview of this book

dbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps. This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You’ll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you’ll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work. By the end of this dbt book, you’ll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that’ll enable you to build reports with the BI tool of your choice.
Table of Contents (21 chapters)
1
Part 1: The Foundations of Data Engineering
7
Part 2: Agile Data Engineering with dbt
14
Part 3: Hands-On Best Practices for Simple, Future-Proof Data Platforms

Technical requirements

This chapter builds on the previous ones, so we expect a basic understanding of SQL, data modeling, and the data life cycle.

To follow the examples, we expect you to have an account at dbt Cloud, connected with Snowflake and GitHub, as explained step-by-step in the first two chapters.

The code samples of this chapter are available on GitHub at https://github.com/PacktPublishing/Data-engineering-with-dbt/tree/main/Chapter_05.