Using dbt Cloud

You can enable CI to test every single change prior to deploying the code to production just like in a software development workflow.

Automatically generate project documentation as you run jobs.

Validate that data freshness meets expectations and alert if stale.

Use artifacts to power your automated docs site and source freshness data.

You can use cron syntax to specify when you want to run a job.

You can define a custom target name for any dbt Cloud job to correspond to settings in your dbt project.

Use environment variables to customize the behavior of your dbt project.

Set up notifications in dbt Cloud to receive Email or Slack alerts for job run status.

Embed Status Tiles in your dashboards to provide consumers with contextual information about the quality and freshness of data.

Visually explore runs and identify long-running models with the model timing dashboard.

The dbt metrics layer helps you standardize metrics within your organization.