The adoption of Power BI Deployment Pipelines is advised to set the automation of deployment of Power BI reports to multiple environments. Pipelines also provide a native way to manage the stages of Dev, Test, and Prod. With Deployment Pipelines, a user can promote their content between stages by version control, compare their changes before deploying, and handle parameter rules to customize datasets per environment (like going to different SQL Server connections).
For more sophisticated automation, you should include Power BI Rest APIs in your CI/CD. Through such scripting, you would publish reports, bind datasets, and manage workspaces using any such automation engine as Azure DevOps, GitHub Actions, or PowerShell scripts for automation. This would be of great use for any enterprise whose workflow involves automated testing and approvals before deployment.
For environment-specific configurations, parameters and dynamic data source binding can be used through APIs or XMLA endpoints. Third-party tools, such as the Power BI Sentinel, Tabular Editor, or ALM Toolkit, can also assist in schema comparison, deployment validation, and metadata tracking. Combining these tools can ensure relatively smooth, repeatable deployments with minimal manual efforts.