README.md

DBT

.
├───analyses/             # SQL files used for auditing queries
├───macros/               # SQL files for reusable functions
├───models/               # SQL files used to generate tables
├───seeds/                # CSV files used to populate initial data
├───snapshots/            # SQL files for handling type-2 data
├───tests/                # SQL files for automated tests
├───example.profiles.yml  # Example YAML file used to configure a connection with Snowflake
├───dbt_project.yml       # YAML file used to configure DBT
└───packages.yml          # YAML file used to specify DBT extensions

DBT is a tool that extends SQL with features like code templating and order of execution. In this project, we leverage DBT to create reproducible database structures in Snowflake.

First Time Setup

# Install the DBT CLI tool
$ python -m venv venv
$ venv/Scripts/pip install dbt-snowflake
$ source venv/Scripts/activate

# Configure your connection to Snowflake
$ cp example.profiles.yml profiles.yml
$ vi profiles.yml

# Test that the configuration works
$ dbt debug

# Install DBT extensions
$ dbt deps

Usage

Create a set of models for individual use in Snowflake

$ dbt run

Create a set of models for group use in Snowflake

Note: Requires Snowflake admin permissions.

$ dbt run -t prod

Other Resources

• DBT Init Documentation
• DBT Quickstart Documentation
• DBT Best Practices