Data sourced from https://github.com/fivethirtyeight/data/tree/master/nfl-elo

DBT Installation - see https://docs.getdbt.com/docs/core/installation for additional details

• 1 - Create a new python virtual environment python -m venv venv
• 2 - pip install -r requirements.txt Note: this will include the Redshift and Snowflake connectors only.

To run this project

• 1 - Activate virtual environment - source venv/bin/activate
• 2 - cd dbt_analytics
• 3 - set USER and PASS environment variables for target system
• 4 - Edit profiles.yml with connection information and user credentials
• 5 - dbt seed --profiles-dir . to create the initial source tables
• 6 - dbt run --profiles-dir .

To create a new project

• 1 - dbt init and follow the prompts to create a new profile or extend existing profile

To generate project documentation

• 1 - dbt docs generate
• 2 - dbt docs serve to host html with with documentation details.

Suggestions for addition:

• 1 - Generate a primary key for the nfl_elo dataset using season + team1 + team2
• 2 - Create an incremental model that shows the change in ELO for each team for each game - ex assume new records are added
• 3 - Add pre-hook + post-hook for groups of models