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Lightdash instantly turns your dbt™️ project into a full-stack BI platform. Analysts write metrics and Lightdash enables self-serve for the entire business.
Paradime integrates natively with Lightdash CLI to enable you to develop Lightdash metrics in your dbt™️ project.

Setup a Lightdash instance

To get started you will need to setup a Lightdash instance. You can choose between Lightdash Cloud or Self-Host.

Develop Lightdash metrics

To get started developing in the Paradime Integrated Terminal open a new terminal tab and login to authenticate with Lightdash depending on your authentication method.

Lightdash CLI

Paradime support Lightdash CLI to help your develop your Lightdash metrics at scale. Autogenerate Lightdash-ready YAML, Lightdash Preview to experiment with your metrics and deploy your new metrics to Lightdash.
To see the full list of CLI options, in the Paradime Terminal use:
lightdash --help

Deploy Lightdash

You can use Paradime Bolt schedules to deploy to Lightdash new changes from your dbt™️ project after a PR is merged using a Paradime CD schedule or after each production run.

1. Add your Lightdash credentials to your Paradime workspace

In Paradime, navigate to account settings > workspaces and add the Lightdash required credentials to enabled the Paradime scheduler to trigger lightdash deploy during a run.
You should set the below credentials as environment variables for your workspace in Paradime.
💡 How can I find the required credentials in Lightdash?
Create a new personal access token, by going to Settings > Personal Access Tokens. This is the token you'll put in for LIGHTDASH_API_KEY.
The UUID for your project. For example, if your URL looks like, then 3538ab33-dc90-45f0-aabb-e50bba3a5f69 is your LIGHTDASH_PROJECT
This is either or (check the URL to your Lightdash project)

2. Setup a paradime schedule with the lightdash deploy command

In your Paradime Bolt schedule, in the commands section add the lightdash deploy step. This will trigger a lightdash deploy after your dbt™️ commands have been executed. This will ensure changes in your dbt™️ project are made available in your lightdash project.
- name: run_with_re_data
schedule: "*/10 * * * *"
environment: production
- dbt seed
- dbt run
- lightdash deploy
owner_email: "[email protected]"
- passed
- failed
- "#data-alerts"
- "@john"
- passed
- failed