Data Engineering with dbt
Offered By: LinkedIn Learning
Course Description
Overview
Learn how to get started with setting up, running, and managing a dbt project.
Syllabus
Introduction
- Build your first dbt project
- Introducing the dbt project
- The project in GitHub Codespaces
- Install the dbt Core via pip
- Install the dbt connector to DuckDB
- Install DuckDB via pip
- Update your requirements.txt file within your project
- Create your database file
- Import CSV data into your new database
- Start your project with dbt init
- Understand the dbt_project.yml file
- Create your profiles YAML file
- Connect your profiles and project YAML files
- Create your first dbt model file
- Using the dbt CLI commands
- Create your dbt model utilizing ref
- Run your dbt models with the ref syntax
- View your dbt project data lineage
- Planning your medallion architecture project
- Medallion architecture: Bronze data
- Medallion architecture: Silver data
- Medallion architecture: Gold data
- Materialization in your dbt project
- Implement materialization in your dbt_project.yml file
- Further documentation via schema.yml file
- The docs_blocks.md file
- Creating custom singular tests
- Implementing tests within the schema.yml file
- Utilizing multiple dbt profiles
- Deploying with GitHub workflows
- Next steps
Taught by
Mark Freeman
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