Describe How the NetApp DataOps Toolkit Works CERTIFIED-AI-EXPERT Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   In an AI pipeline, the DataOps toolkit can be used to:

   • AMonitor model accuracy during training
   • BAutomate the creation of dataset versions for each training run
   • CDeploy the trained model to production
   • DVisualize training loss curves
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2. 7application · medium

   A software team is building a custom AI data management application and wants to integrate the NetApp DataOps toolkit. They need to embed data operations directly into their application code. Which toolkit component should they use?

   • ANetApp ONTAP CLI
   • BDataOps SDK
   • CDataOps API
   • DNetApp BlueXP console
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4. 8foundation · easy

   Which of the following is an example of orchestrating data operations using the DataOps toolkit?

   • AConfiguring the toolkit to automatically retrain models
   • BUsing the toolkit's built-in Kubernetes operator to manage pods
   • CUsing the toolkit to monitor GPU utilization
   • DCalling the DataOps API from a CI/CD pipeline to create a dataset before model training
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5. 9foundation · easy

   What is the primary benefit of using the DataOps toolkit's clone operation for dataset management?

   • AIt encrypts the dataset for secure sharing
   • BIt automatically cleans up unused datasets
   • CIt migrates data to the cloud
   • DIt reduces storage consumption by using space-efficient snapshots
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6. 10foundation · easy

   What is the role of the DataOps SDK in the NetApp DataOps toolkit?

   • AIt allows developers to interact with the DataOps API using Python
   • BIt is a standalone application for monitoring data pipelines
   • CIt provides a graphical interface for managing datasets
   • DIt is a command-line tool for managing NetApp storage
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