dbt Fundamentals

Learn the Fundamentals of dbt including modeling, testing, documentation, and deployment.

Welcome to dbt Fundamentals

Welcome! Frequently Asked Questions

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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