Data Engineering with dbt
1h 16mIntermediate2024-01-02
Authors
Mark Freeman
Course details
Data Build Tool (dbt) has quickly become an essential tool in many data stacks ranging from startups to big tech for managing data transformations. In this course, data engineer Mark Freeman helps you get started with setting up, running, and managing a dbt project via the open-source offering dbt Core. Learn how to install dbt Core, configure an environment for dbt, create and manage a dbt project, and deploy a dbt project in production. If you’re a data professional tasked with implementing dbt within your organization, recently joined a team utilizing dbt and need to upskill, or just want to learn about dbt to increase your competitiveness within the data job market, check out this course.
Skills covered
Data Build Tool (dbt)Data ModelingData EngineeringData ScienceOpen SourceOne-Off
Concepts
0. Introduction
- 01 - Build your first dbt project
- 02 - Introducing the dbt project
- 03 - The project in GitHub Codespaces
1. Prepare Your Coding Environment
- 04 - Install the dbt Core via pip
- 05 - Install the dbt connector to DuckDB
- 06 - Install DuckDB via pip
- 07 - Update your requirements.txt file within your project
2. Prepare Your Database Environment
- 08 - Create your database file
- 09 - Import CSV data into your new database
3. Create a dbt Project
- 10 - Start your project with dbt init
4. Prepare Your dbt Environment
- 11 - Understand the dbt project.yml file
- 12 - Create your profiles YAML file
- 13 - Connect your profiles and project YAML files
5. Your First dbt Model
- 14 - Create your first dbt model file
- 15 - Using the dbt CLI commands
6. Introduction to dbt Ref Function
- 16 - Create your dbt model utilizing ref
- 17 - Run your dbt models with the ref syntax
- 18 - View your dbt project data lineage
7. Implementing Medallion Architecture with dbt
- 19 - Planning your medallion architecture project
- 20 - Medallion architecture - Bronze data
- 21 - Medallion architecture - Silver data
- 22 - Medallion architecture - Gold data
8. Materialization of dbt Models
- 23 - Materialization in your dbt project
- 24 - Implement materialization in your dbt project.yml file
9. Documentation as Code via dbt
- 25 - Further documentation via schema.yml file
- 26 - The docs blocks.md file
10. Implementing Tests within Your dbt Project
- 27 - Creating custom singular tests
- 28 - Implementing tests within the schema.yml file
11. Deploying Your dbt Project
- 29 - Utilizing multiple dbt profiles
- 30 - Deploying with GitHub workflows
Conclusion
- 31 - Next steps