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 11–20 of 138

Q11

A company needs to securely share datasets with external partners. What is the best approach?

  • A Use Azure File Share with authentication
  • B Implement Azure Data Share
  • C Install a VPN for data transfer
  • D Send datasets via email
Explanation Azure Data Share is specifically designed for securely sharing datasets with external entities.
Q12

What happens when you configure an Azure Machine Learning model for batch inference?

  • A Runs immediately on all new data
  • B Waits for manual triggering
  • C Processes in real-time
  • D Only uses data from a single source
Explanation Batch inference models require manual or scheduled triggering to process data.
Q13

Which service is best for version controlling machine learning models?

  • A Azure Machine Learning
  • B Azure DevOps
  • C Azure Blob Storage
  • D Azure Functions
Explanation Azure Machine Learning offers built-in versioning for models, while others do not support model management specifically.
Q14

A company needs to analyze real-time streaming data. Which Azure service should they use?

  • A Azure Logic Apps
  • B Azure Data Factory
  • C Azure Stream Analytics
  • D Azure Batch
Explanation Azure Stream Analytics is designed specifically for real-time analytics, while the others are meant for different scenarios.
Q15

You are configuring an Azure Machine Learning pipeline. What happens when you add a data preparation step after the training step?

  • A Training gets skipped.
  • B Data is prepared twice.
  • C Pipeline executes out of order.
  • D Data preparation runs before training.
Explanation Data preparation must precede the model training; incorrectly placing them will lead to unintended results.
Q16

Which Azure service helps identify anomalies in time-series data?

  • A Azure Anomaly Detector
  • B Azure Monitor
  • C Azure ML Designer
  • D Azure Stream Analytics
Explanation Azure Anomaly Detector is specifically designed for anomaly detection, while the others serve different functions.
Q17

A company needs to design a machine learning solution that scales seamlessly with data volume. Which Azure service should they consider?

  • A Azure Batch
  • B Azure Data Lake Storage
  • C Azure Databricks
  • D Azure Functions
Explanation Azure Databricks supports big data processing and auto-scaling, making it ideal for scalable machine learning solutions.
Q18

What happens when you enable 'AutoML' in Azure Machine Learning for a dataset?

  • A It automatically selects the best features.
  • B It chooses the best algorithm and hyperparameters.
  • C It creates production-ready pipelines.
  • D It generates interpretability reports.
Explanation AutoML optimizes model training by selecting the best algorithm and hyperparameters based on dataset characteristics.
Q19

Which Azure service is best for large-scale data processing?

  • A Azure Databricks
  • B Azure SQL Database
  • C Azure Blob Storage
  • D Azure Functions
Explanation Azure Databricks is optimized for big data analytics, while others serve different purposes.
Q20

A company needs to predict customer churn using historical data stored in Azure. What is the best approach?

  • A Use Azure Machine Learning AutoML
  • B Implement Azure Logic Apps
  • C Utilize Azure HDInsight
  • D Deploy Azure Synapse Analytics
Explanation Azure Machine Learning AutoML simplifies model training for predictive analysis, unlike the other options.