class: subtitle # Working session 1 .dense-text[ 1. Make sure you have your dbt Cloud project set up. * Accept the dbt Cloud invite. * Find your project and input your Snowflake credentials. * Initialize your project. 2. Run the `customers.sql` model. 3. Refactor this code to break out the staging models into `stg_customers.sql` and `stg_orders.sql`. * Create a staging subdirectory under models for these staging models. 4. Change the materialization strategy of your project in `dbt_project.yml` so that all models are materialized as tables by default, but the models in the staging folder will be materialized as views. ] ??? Notes for what to walk students through * Give them a brief tour of the IDE: the file tree, file editor, the "Preview Data" and "Compile SQL" buttons, the results tab, and command line. * When creating the staging models explain that best practice is to create one staging model per raw data table and to do some minimal cleanup and re-naming. * For each model created, run the command: `dbt run` and look at the logs to talk through what is happening.