Welcome to my dbt project!

Using the starter project

• dbt is a tool for how to build with data rather than enforcing what to build

Try running the following commands:

• dbt run
• dbt test

dbt Learning Notes

Model naming conventions

• Sources(src) - the raw data that has already been loaded to a WH
• Staging(stg) - 1:1 with source tables. Clean and standardized tables(views)
• Intermediate(int) - models between staging and final models. Always build on staging models
• Facts(fct) - Skinny, long tables of things that are occurring or have occured (events, clicks, votes etc)
• Dimensions(dim) - things that exist, do not change as much for example email for a customer

Recommended project structure (Example)

dbt-learn
├── analysis
├── dbt_modules
├── logs
├── macros
├── models
    └── marts
        └── core
            └── dim_customers.sql
        └── finance
        └── hr
        └── marketing
        └── businessunit_or_domain_etc  
    └── staging
        └── jaffle_Shop
            ├── stg_customers.sql
            └── stg_orders.sql 
├── snapshots
├── target
├── tests
├── .gitignore
├── dbt_project.yml
└── README.md

Ref Macro

• Use {{ ref('REPLACE_WITH_YOUR_MODEL_NAME') )} to refer to other defined models and resume within current one.

Documentation in DBT

• DBT provides a DAG which is automatically generated to show flow of data from source to final models
• You can add own test descriptions directly in the project. Documenting can happen as you build your models. You can use MarkDown
• To run the document generation in dbt: dbt docs generate

Resources:

• Learn more about dbt in the docs
• Check out Discourse for commonly asked questions and answers
• Join the chat on Slack for live discussions and support
• Find dbt events near you
• Check out the blog for the latest news on dbt's development and best practices