Describe the Uses of BlueXP Software Tools to Build AI Solutions CERTIFIED-AI-EXPERT Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which BlueXP feature is designed to improve performance for AI workloads by keeping frequently accessed data on high-speed storage?

   • ACaching
   • BEncryption
   • CSnapshotting
   • DDeduplication
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A company is expanding its AI operations from a single cloud region to multiple regions to reduce latency for global users. They use BlueXP to manage storage. What should they configure to ensure data is available in all regions while maintaining a single management interface?

   • ADeploy BlueXP connectors in each region and manage them from a single BlueXP account.
   • BCreate separate BlueXP accounts for each region.
   • CUse BlueXP backup to replicate data to all regions.
   • DUse BlueXP tiering to move data to a single object store.
   Reveal Solution Discussion Select an answer first
4. 8application · medium

   A data science team uses a distributed training pipeline that reads datasets from a NetApp ONTAP NFS share. They want to use BlueXP to streamline data preparation and reduce the time spent copying data to compute instances. Which BlueXP feature should they integrate with their AI pipeline to provide low-latency access to training data?

   • ABlueXP Cost Optimizer to identify unused data and reduce storage spend.
   • BBlueXP Compliance to scan datasets for regulatory compliance before training.
   • CBlueXP Backup to create frequent snapshots of the training data.
   • DBlueXP Cloud Cache to create a high-performance cache close to the compute resources.
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   In an AI workload, what is the primary benefit of using BlueXP's data tiering feature?

   • AIt replicates data to multiple regions to improve availability.
   • BIt encrypts data at rest to meet compliance requirements.
   • CIt increases the speed of model training by providing more GPU resources.
   • DIt reduces storage costs by moving less frequently accessed data to lower-cost storage tiers.
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   How does BlueXP integrate with AI frameworks and pipelines to streamline data preparation?

   • ABy replacing the AI framework's data loading functions with proprietary ones.
   • BBy providing APIs and connectors that allow AI pipelines to access and manage data stored on NetApp systems.
   • CBy providing a built-in model registry for versioning trained models.
   • DBy compiling AI models into a format that runs directly on storage hardware.
   Reveal Solution Discussion Select an answer first