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 101–110 of 138

Q101

A company needs to deploy a machine learning model with 99% uptime. Which Azure feature should be prioritized for this requirement?

  • A Scale Sets
  • B Availability Zones
  • C Azure Activations
  • D Azure Functions
Explanation Availability Zones provide high availability; Scale Sets can help but don't guarantee redundancy.
Q102

What happens when you use AutoML with insufficient historical data?

  • A Model fails to train
  • B Training time is extended
  • C Model accuracy decreases
  • D More hyperparameters are generated
Explanation Insufficient data often leads to poor model generalization; the other options are incorrect outcomes.
Q103

Which service is best for predictive analytics in Azure?

  • A Azure Machine Learning
  • B Azure Functions
  • C Azure Data Lake
  • D Azure Cosmos DB
Explanation Azure Machine Learning is specifically designed for predictive analytics, while the others serve different purposes.
Q104

A company needs a chatbot for customer service. Which Azure service should they use?

  • A Azure Bot Service
  • B Azure Logic Apps
  • C Azure Web Apps
  • D Azure Functions
Explanation Azure Bot Service is purpose-built for creating chatbots, whereas the other options do not focus on chatbot functionalities.
Q105

What happens when using 'Data Drift' feature in Azure Machine Learning?

  • A Improves model accuracy automatically
  • B Tracks changes in data over time
  • C Trains multiple models simultaneously
  • D Eliminates the need for retraining
Explanation The 'Data Drift' feature monitors and identifies shifts in the data distribution, which is essential for maintaining model performance.
Q106

Which service is used for building predictive models in Azure?

  • A Azure Machine Learning
  • B Azure DevOps
  • C Azure Blob Storage
  • D Azure SQL Database
Explanation Azure Machine Learning is specifically designed for predictive modeling, while the others serve different purposes.
Q107

A company needs to automate preprocessing of data before training. Which Azure feature should they use?

  • A Data Lake
  • B Data Factory
  • C Cosmos DB
  • D Stream Analytics
Explanation Azure Data Factory is best suited for data processing automation, while the others do not primarily focus on this.
Q108

You are configuring a model in the Azure ML pipeline. What happens when you set a split ratio of 0.8?

  • A 80% for training data
  • B 20% for validation data
  • C Unchanged data split
  • D Random data distribution
Explanation A split ratio of 0.8 means 80% allocation for training, with the remainder for other uses.
Q109

Which Azure service is best for deploying Jupyter notebooks?

  • A Azure Machine Learning
  • B Azure Functions
  • C Azure Blob Storage
  • D Azure SQL Database
Explanation Azure Machine Learning is specifically designed for data science workflows, including Jupyter notebook deployment.
Q110

A company needs to analyze large streams of event data in real time. Which Azure service should they use?

  • A Azure Data Lake Storage
  • B Azure Stream Analytics
  • C Azure SQL Database
  • D Azure Data Factory
Explanation Azure Stream Analytics provides real-time analytics capabilities specifically for stream processing of event data.