Hey @Mike thank you for the video. One thing I did not see anyone covered is how DBT layers translate to DW objects. For example, it was quite surprising to me that "raw" layer is a separate DB. I just joined a new org and they did the same. I think this is a bit unusual approach, so would be great to see it covered.
@kahanDataSolutins, will The Playbook for dbt include the DBT cloud knowledge as well.. like how to schedule and how to run the jobs in different environments and how to set up those environment variables in the cloud and all please, Jinja and macro coding etc.
Hi, thanks for your content. I have a question: I have already configured my 3 data stores: raw, analytics (development) and analytics-prod (production). Is it possible to configure certain models to only display in the development environment? I work from dbt Cloud, and I have automatic jobs configured. But currently I get this result: Analytcs-prod (production): marts: customer.sql staging: stg_customer.sql Analyctcs: marts: customer.sql staging: stg_customer.sql I would like to only execute the queries of stangin within the development environment and marts in production.
Can we have multiple profiles in the profiles.yml apart from multiple environmnents. For example, haivng Snowflake and Redshift. If yes, how to connect the same?
Do you know why a pipe symbol | is necessary for the database assignment in your example ~5:54 mark on line 5 (database: |)? If so could you please explain this?
Try adding comma-separated tags (ex. dbt run -s tag: tag_1, tag_2) to run multiple. I haven't tried myself but that would be my first thought. Here are the docs for more info: docs.getdbt.com/reference/resource-configs/tags
