Review dbt project structure

With our base tables populated, we can turn to the dbt project. The analytics/models directory, located alongside our Dagster code in the src/project_dbt directory, contains a small but representative dbt project:

analytics
├── marts
│   ├── daily_metrics.sql
│   └── location_metrics.sql
├── sources
│   └── raw_taxis.yml
└── staging
    ├── staging.yml
    ├── stg_trips.sql
    └── stg_zones.sql

It’s usually simpler to keep your dbt project in the same repository as your Dagster code. This makes it easier for Dagster to parse the metadata files generated by dbt commands, and enables tighter integration between the two tools.

dbt sources

This dbt project includes four models and two sources. The sources correspond to the taxi_zones and taxi_trips tables created in the previous step:

src/project_dbt/analytics/models/sources/raw_taxis.yml

version: 2

sources:
  - name: raw_taxis
    schema: main
    tables:
      - name: zones
      - name: trips

The connection for the dbt project is defined in profiles.yml. Here, we point it to the same DuckDB storage layer used by our Dagster DuckDB resource, /var/tmp/duckdb.db:

src/project_dbt/analytics/profiles.yml

dbt_project:
  target: dev
  outputs:
    dev:
      type: duckdb
      path: '{{ env_var("DUCKDB_DATABASE", "/var/tmp/duckdb.db") }}'

dbt models

In addition to the sources, the project defines several models that capture the business logic. Most models are materialized as tables, one is incremental, and one includes lightweight tests (configured in staging.yml).

Table	Materialization	Tests
daily_metrics	Incremental	No
location_metrics	Table	No
stg_trips	Table	No
stg_zones	Table	Yes

The SQL inside each model isn’t the focus here. Instead, this compact project highlights many of the core dbt patterns you’ll encounter: staging layers, source declarations, different materializations, and basic testing.

Next, we’ll turn these dbt models into Dagster assets so they can be orchestrated, tracked, and monitored as part of your data pipeline.

Next steps

• Continue this example with dbt assets