Designing and Implementing a Data Science Solution on Azure — Question 72

You use the Azure Machine Learning Python SDK to create a batch inference pipeline.

You must publish the batch inference pipeline so that business groups in your organization can use the pipeline. Each business group must be able to specify a different location for the data that the pipeline submits to the model for scoring.

You need to publish the pipeline.

What should you do?

Answer options

• A. Create multiple endpoints for the published pipeline service and have each business group submit jobs to its own endpoint.
• B. Define a PipelineParameter object for the pipeline and use it to specify the business group-specific input dataset for each pipeline run.
• C. Define a OutputFileDatasetConfig object for the pipeline and use the object to specify the business group-specific input dataset for each pipeline run.
• D. Have each business group run the pipeline on local compute and use a local file for the input data.

Correct answer: B

Explanation

The correct answer is B because using a PipelineParameter object allows you to dynamically specify the input dataset for each run of the pipeline based on the requirements of different business groups. Options A and D are not efficient as they involve creating multiple endpoints or executing locally, which is not scalable. Option C is incorrect because OutputFileDatasetConfig is used for output configuration, not for specifying input datasets.