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docs(ingest/dbt): clarify dbt ingestion docs (datahub-project#11312)
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hsheth2 authored Sep 9, 2024
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24 changes: 13 additions & 11 deletions metadata-ingestion/docs/sources/dbt/README.md
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Expand Up @@ -2,17 +2,19 @@ Ingesting metadata from dbt requires either using the **dbt** module or the **db

### Concept Mapping

| Source Concept | DataHub Concept | Notes |
| --------------- | ------------------------------------------------------------- | ------------------ |
| `"dbt"` | [Data Platform](../../metamodel/entities/dataPlatform.md) | |
| dbt Source | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Source` |
| dbt Seed | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Seed` |
| dbt Model | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Model` |
| dbt Snapshot | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Snapshot` |
| dbt Test | [Assertion](../../metamodel/entities/assertion.md) | |
| dbt Test Result | [Assertion Run Result](../../metamodel/entities/assertion.md) | |
| Source Concept | DataHub Concept | Notes |
| -------------- | ---------------------------------------------------------------------- | ------------------ |
| Source | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Source` |
| Seed | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Seed` |
| Model | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Model` |
| Snapshot | [Dataset](../../metamodel/entities/dataset.md) | Subtype `Snapshot` |
| Test | [Assertion](../../metamodel/entities/assertion.md) | |
| Test Result | [Assertion Run Result](../../metamodel/entities/assertion.md) | |
| Model Runs | [DataProcessInstance](../../metamodel/entities/dataProcessInstance.md) | |

Note:

1. It also generates lineage between the `dbt` nodes (e.g. ephemeral nodes that depend on other dbt sources) as well as lineage between the `dbt` nodes and the underlying (target) platform nodes (e.g. BigQuery Table -> dbt Source, dbt View -> BigQuery View).
2. We also support automated actions (like add a tag, term or owner) based on properties defined in dbt meta.
1. You must **run ingestion for both dbt and your data warehouse** (target platform). They can be run in any order.
2. It generates column lineage between the `dbt` nodes (e.g. when a model/snapshot depends on a dbt source or ephemeral model) as well as lineage between the `dbt` nodes and the underlying target platform nodes (e.g. BigQuery Table -> dbt source, dbt model -> BigQuery table/view).
3. It automatically generates "sibling" relationships between the dbt nodes and the target / data warehouse nodes. These nodes will show up in the UI with both platform logos.
4. We also support automated actions (like add a tag, term or owner) based on properties defined in dbt meta.
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Expand Up @@ -91,7 +91,7 @@ class AwsConnectionConfig(ConfigModel):
aws_role: Optional[Union[str, List[Union[str, AwsAssumeRoleConfig]]]] = Field(
default=None,
description="AWS roles to assume. If using the string format, the role ARN can be specified directly. "
"If using the object format, the role can be specified in the RoleArn field and additional available arguments are documented at https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts.html?highlight=assume_role#STS.Client.assume_role",
"If using the object format, the role can be specified in the RoleArn field and additional available arguments are the same as [boto3's STS.Client.assume_role](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts.html?highlight=assume_role#STS.Client.assume_role).",
)
aws_profile: Optional[str] = Field(
default=None,
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