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dbt Fundamentals
Learn the Fundamentals of dbt including modeling, testing, documentation, and deployment.
Welcome to dbt Fundamentals
Welcome!
Frequently Asked Questions + Change Log
Who is an analytics engineer?
Learning Objectives
Traditional Data Teams
ETL and ELT
Analytics Engineer
data build tool
Review
Set up dbt Cloud
Learning Objectives
dbt, databases, and version control
Loading training data into your warehouse
Set up GitHub repository and connect to dbt Cloud
Connect to your warehouse and repository
dbt Cloud IDE Overview
Review
Models
Learning Objectives
What are models?
Building your first model
What is modularity?
Modularity and the ref functions
Quick history of data modeling
Naming conventions
Reorganize your project
Practice
Exemplar
Review
Tests
Learning Objectives
Why testing?
What is testing?
Schema tests
Data tests
Practice
Exemplar
Review
Documentation
Learning Objectives
Why is documentation important?
What is documentation?
Writing documentation and doc blocks
Generate and view Documentation
Practice
Review
Sources
Learning Objectives
What are sources?
Configure and select from sources
Testing and documenting sources
Source freshness
Practice
Exemplar
Review
Deployment
Learning Objectives
What is deployment?
Scheduling a dbt job in dbt Cloud
Review a scheduled dbt Cloud job
Review
Jinja Primer
Learning Objectives
What is Jinja?
Jinja Basics
Jinja Applications
Practice
Exemplar
Review
Macros
Learning Objectives
What are macros?
cents_to_dollars macro
limit_data_in_dev macro
DRY code vs. readability
Practice
Exemplar
Review
Packages
Learning Objectives
What are packages?
Installing packages
Packages with macros
Packages with models
Practice
Exemplar
Review
Materializations
Learning Objectives
What are materializations?
Tables, views, and ephemeral models
Incremental models
What are snapshots?
Implementing snapshots
Practice
Review
Analyses and Seeds
Learning Objectives
What are analyses?
What are seeds?
Implementing analyses
Implementing seeds
Practice
Exemplar
Review
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