Microsoft Azure

Designing and Implementing a Data Science Solution on Azure

DP-100

Master data science on Azure with the DP-100 exam focusing on designing and implementing solutions.

138 questions 0 views Free
Start Mock Test Timed · Full-length · Scored

Questions 21–30 of 138

Q21

You are configuring a model training pipeline in Azure. What happens if you set the maximum number of concurrent pipelines to zero?

  • A All pipelines will execute immediately
  • B No pipelines will execute
  • C The system will default to one pipe
  • D Pipelines will queue indefinitely
Explanation Setting concurrency to zero effectively halts all pipeline executions, unlike other options.
Q22

Which Azure service is best suited for building machine learning models?

  • A Azure Machine Learning
  • B Azure Data Factory
  • C Azure Databricks
  • D Azure Logic Apps
Explanation Azure Machine Learning is specifically designed for building, training, and deploying machine learning models, while the others serve different purposes.
Q23

A company needs to deploy a predictive model for real-time user data. What Azure solution should they use?

  • A Azure Batch
  • B Azure Stream Analytics
  • C Azure Blob Storage
  • D Azure Logic Apps
Explanation Azure Stream Analytics enables real-time data processing, which is critical for predictive modeling on live data.
Q24

You are configuring an Azure ML workspace. What happens if you set the default compute target to VM with limited GPUs?

  • A Only CPU processing will be allowed.
  • B All models will fail to run.
  • C GPU models will run slower.
  • D Training will only use CPU.
Explanation Setting the compute target to a limited GPU VM means models that utilize GPUs will still run but potentially with reduced performance.
Q25

Which Azure service is primarily used for building, training, and deploying machine learning models?

  • A Azure Machine Learning
  • B Azure Data Factory
  • C Azure Databricks
  • D Azure Synapse Analytics
Explanation Azure Machine Learning is specifically designed for machine learning workflows, while the others serve different data processing purposes.
Q26

A company needs to implement version control for their machine learning models. What service should they choose?

  • A Azure DevOps
  • B Azure Blob Storage
  • C Azure Data Lake Storage
  • D Azure Cognitive Services
Explanation Azure DevOps provides tools for version control while the others do not focus on model versioning.
Q27

What happens when you try to deploy a model with mismatched schema in Azure Machine Learning?

  • A Deployment succeeds with warnings
  • B Deployment fails
  • C Model runs but gives errors
  • D Schema automatically adjusts
Explanation Deployment fails due to the mismatch in expected input schema.
Q28

Which Azure service would you use for real-time data processing?

  • A Azure Stream Analytics
  • B Azure Blob Storage
  • C Azure Data Lake Storage
  • D Azure SQL Database
Explanation Azure Stream Analytics is optimized for real-time data processing, while the others are focused on storage solutions or batch processing.
Q29

A company needs to automate model deployment in Azure. Which service should they use?

  • A Azure DevOps
  • B Azure Machine Learning
  • C Azure Functions
  • D Azure Virtual Machines
Explanation Azure Machine Learning provides built-in capabilities for automating model deployment, while Azure DevOps focuses on workflow management and CI/CD practices.
Q30

What happens when you don't set an expiration for a dataset in Azure Data Lake Storage?

  • A Data is deleted automatically
  • B Data remains indefinitely
  • C Data becomes read-only
  • D Data triggers alerts
Explanation If no expiration is set, the data stays in Azure Data Lake Storage indefinitely until explicitly deleted by the user.