DP-600 Maintain a Data Analytics Solution Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✓

  Apply deployment rules to change the data source connection of a semantic model.

  Why this is correct

  Deployment rules allow you to automatically update parameters or connection strings as items move between stages. This ensures that the test environment queries the test database while the production environment queries the production database. Without this feature, developers would have to manually update connections, which is a major source of production errors.

• ✗

  Automatically convert a Power BI report into a Paginated report during the deployment.

  Why it's wrong here

  Deployment pipelines are designed to move and configure items, not to change their fundamental type or internal structure. Power BI reports and Paginated reports use different file formats and rendering engines. Converting between these types requires manual redesign and cannot be handled by the deployment automation process provided by Fabric pipelines.

• ✗

  Restore a deleted workspace by reverting to a previous pipeline deployment stage.

  Why it's wrong here

  Pipelines manage the content within workspaces but do not act as a backup and restore mechanism for the workspaces themselves. If a workspace is deleted, it must be recovered through the Microsoft 365 admin center or recreated. Pipelines can redeploy content to a new workspace, but they cannot restore the original workspace object.

• ✓

  Compare the items in the source and target stages to identify differences before deploying.

  Why this is correct

  The comparison tool within deployment pipelines provides a visual representation of which items are new, modified, or identical across stages. This allows engineers to verify exactly what changes will be applied before committing the deployment. It is a critical maintenance step for preventing the accidental deployment of unfinished or unwanted modifications.

• ✗

  Encrypt individual columns in a Lakehouse table using a custom key during the sync.

  Why it's wrong here

  Deployment pipelines do not modify the internal data or schema of Lakehouse tables, such as applying column-level encryption. Security configurations like encryption at rest are handled at the capacity or storage level, not through the deployment pipeline interface. The pipeline's role is focused on the movement and metadata configuration of the workspace items.