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 51–60 of 138

Q51

You are configuring a machine learning model for deployment. What should you prioritize?

  • A Model Complexity
  • B Model Explainability
  • C Model Training Time
  • D Model Size
Explanation Model explainability is essential for trust and transparency, more so than other factors here.
Q52

Which Azure service is best suited for real-time streaming analytics?

  • A Azure Functions
  • B Azure Cosmos DB
  • C Azure Stream Analytics
  • D Azure Firestore
Explanation Azure Stream Analytics specializes in real-time data processing, while the others serve different purposes such as serverless computing or database services.
Q53

A company needs to manage their data science project lifecycle effectively. What should they use?

  • A Azure Notebooks
  • B Azure DevOps
  • C Azure Machine Learning Workspaces
  • D Azure Data Lake Storage
Explanation Azure DevOps provides tools for managing the entire project lifecycle, whereas the others focus on specific aspects like code or storage.
Q54

You are configuring an Azure Machine Learning model for deployment. What happens when you select 'Real-time endpoint'?

  • A Batch processing deployed
  • B Scalable endpoint for predictions
  • C Data is automatically cleaned
  • D Model will run only on-premises
Explanation Selecting 'Real-time endpoint' creates a scalable REST endpoint for instant predictions, not batch processing or other options.
Q55

Which Azure service is best for real-time event processing?

  • A Azure Stream Analytics
  • B Azure Blob Storage
  • C Azure SQL Database
  • D Azure Virtual Machine
Explanation Azure Stream Analytics specifically handles real-time data streams, while other options are not designed for real-time processing.
Q56

A company needs to implement a secure REST API for their data science models. Which Azure service should they use?

  • A Azure API Management
  • B Azure Data Lake Storage
  • C Azure Functions
  • D Azure DevOps
Explanation Azure API Management allows for secure APIs, while the other options do not focus on API management functionalities.
Q57

What happens when you set the 'warm-up' time for an Azure Machine Learning model deployment?

  • A Model loads faster initially
  • B Requests get throttled
  • C Model is not ready for requests
  • D Increased cost from idle time
Explanation Setting 'warm-up' time delays readiness for requests, ensuring the model is fully prepared before handling them.
Q58

Which Azure service is best for real-time analytics on streaming data?

  • A Azure Stream Analytics
  • B Azure Blob Storage
  • C Azure SQL Database
  • D Azure Data Lake Storage
Explanation Azure Stream Analytics provides real-time insights, while others are not optimized for streaming data.
Q59

A company needs to scale its machine learning model on-demand. Which Azure service should they use?

  • A Azure Functions
  • B Azure Machine Learning
  • C Azure Batch
  • D Azure App Service
Explanation Azure Machine Learning supports model deployment and scaling, whereas others do not specialize in ML models.
Q60

What happens when you configure a model with high bias in Azure ML?

  • A Model underfits training data
  • B Model overfits training data
  • C Model performs excellently
  • D Model ignores all input features
Explanation High bias leads to underfitting, while other options describe different types of model behavior.