Deployment pipelines validate invalid warehouse references as part of deployment

DP-700 By islever Editorial Last updated

Short answer

B A deployment pipeline checks dependencies and reports invalid references during deployment with no extra development effort.

Question

You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1. You plan to deploy Warehouse1 to a new workspace named Workspace2. As part of the deployment process, you need to verify whether Warehouse1 contains invalid references. The solution must minimize development effort. What should you use?
  1. a database project
  2. a deployment pipeline Correct Answer
  3. a Python script
  4. a T-SQL script

Key Takeaways

The deployment process in Fabric deployment pipelines includes validation of dependencies and references, so reusing the pipeline detects invalid references without writing custom scripts.

Deploying Warehouse1 from Workspace1 to Workspace2 through a Fabric deployment pipeline automatically validates the item and surfaces issues such as invalid references during deployment, with no additional development effort.

Common mistake: Writing a Python or T-SQL script to scan for invalid references; both add development effort, while the deployment pipeline reports such validation issues out of the box.

Expert Analysis

Why the Answer Is Correct

Fabric deployment pipelines perform validation during deployment: when an item such as Warehouse1 is deployed from one workspace to another, the pipeline checks the item's dependencies and reports issues, including invalid references, as part of the deployment process. Using the pipeline therefore verifies the references with minimal development effort - essentially configuration only.

Why the Other Options Are Wrong

Option A (a database project) can validate a warehouse schema but requires creating and maintaining the project, which is more development effort than reusing the deployment pipeline. Option C (a Python script) and Option D (a T-SQL script) both require writing and maintaining custom validation logic, directly contradicting the minimize-development-effort requirement.

Community Comment Notes

The community strongly favors B (85). QAZdbarhate12345678 (11 likes) explains that deployment pipelines automatically check for invalid references or missing dependencies during deployment, while dissenting comments propose a database project or a Python script, both of which add development effort.

Official Reference

Community Votes

B
100%

100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 3 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 3

  1. QAZdbarhate12345678 👍 11 Answered B
    Microsoft Fabric's deployment pipelines provide a built-in mechanism to manage and validate the deployment of artifacts like warehouses. When you use a deployment pipeline to move Warehouse1 from one workspace (Workspace1) to another (Workspace2), the pipeline automatically checks for issues such as invalid references or missing dependencies during the deployment process.
  2. Anushareddysri 👍 1 Answered C
    Question is focusing on "As part of the deployment process, you need to verify whether Warehouse1 contains invalid references" for this python script can be written to identify invalid references and can add it as a notebook activity in pipeline. So answer is python script.
  3. hebertorosillo 👍 1 Answered A
    A. a database project for minimal effor

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