> ## Documentation Index
> Fetch the complete documentation index at: https://elementary-ele-2784-fix-alerts-configuration-links-docs.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Lineage to Downstream Exposures

Some of your data is used downstream in dashboards, applications, data science pipelines, reverse ETLs, etc.
These downstream data consumers are called *exposures*.

Elementary lineage graph presents downstream exposures of two origins:

1. Elementary Cloud Automated BI integrations
2. Exposures configured in your dbt project. Read about [how to configure exposures](https://docs.getdbt.com/docs/build/exposures) in code.

<Accordion title="Supported exposures YML fields">
  ```yaml
  exposures:
    - name: returns_dashboard
      label: Returned Orders # Pretty name, will be used if provided
      type: dashboard
      url: https://your.bi.tool/dashboards/2
      description: >
        Returned orders over time
      platform: Tableau # Elementary field
      path: Tableau # For the UI folders tree, elementary field

      depends_on:
        - ref('returned_orders')

      owner:
        name: Callum McData
        email: data@jaffleshop.com

      tags: ["finance"]

      meta:
        referenced_columns: # Used for exposure validation test
          - column_name: "order_id"
            data_type: "numeric"
  ```
</Accordion>

### Automated BI lineage

<Snippet file="cloud/cloud-feature-tag.mdx" />

Elementary will automatically and continuously extend the column-level-lineage to the dashboard level of your data visualization tool.

<video autoplay muted loop playsinline className="w-full aspect-video" src="https://res.cloudinary.com/diuctyblm/video/upload/v1710790204/colum-level-lineage-to-bi-better_c00lz0.mp4" />

### Supported BI tools:

<Snippet file="cloud/integrations/cards-groups/bi-cards.mdx" />

### Why is lineage to exposures useful?

* **Incidents impact analysis**: You could explore which exposures are impacted by each data issue.
* **Exposure health**: By selecting an exposure and filtering on upstream nodes, you could see the status of all it’s upstream datasets.
* **Prioritize data issues**: Prioritize the triage and resolution of issues that are impacting your critical downstream assets.
* **Change impact**: Analyze which exposures will be impacted by a planned change.
* **Unused datasets**: Detect datasets that no exposure consumes, that could be removed to save costs.