A company runs AI training jobs that have variable data access patterns. Some datasets are accessed heavily for a few weeks and then become cold. They use BlueXP and want to minimize storage costs while ensuring that data is available for retraining at any time. Which approach should they take?

Use automated tiering with policies that move data to lower-cost tiers after a defined period of inactivity.

Replicate all data to multiple regions to ensure availability.

Keep all data on high-performance storage to ensure immediate availability for retraining.

Delete data that is not accessed for a month to reduce costs.

A financial services company is using BlueXP to manage AI training data that includes sensitive customer information. They must ensure that data is encrypted both at rest and in transit, and that only authorized AI engineers can access the datasets. Which BlueXP capability should they enable to meet these requirements?

Use BlueXP tiering to move all sensitive data to a public cloud object store.

Configure BlueXP to replicate data to a secondary site in another country.

Enable BlueXP backup to create multiple copies of the data for disaster recovery.

Enable encryption and configure role-based access controls (RBAC) for the BlueXP environment.

A government agency uses BlueXP to manage AI datasets that are subject to strict data residency requirements. They must ensure that data does not leave a specific geographic region. Which BlueXP configuration should they implement to meet this requirement?

Configure role-based access controls to limit who can access the data.

Use BlueXP replication to copy data to a secondary region for disaster recovery.

Enable encryption on all data to prevent unauthorized access.

Restrict BlueXP storage resources to a region that complies with the residency requirement.

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Domain 3Objective 5

Describe the Uses of BlueXP Software Tools to Build AI Solutions CERTIFIED-AI-EXPERT Practice Questions (Page 6)

Part of the AI Software Architectures domain, which accounts for 18% of the CERTIFIED-AI-EXPERT exam. NetApp does not publish an official question count, but from its 90-minute exam (~35–60 total, ~6–11 in this domain), expect 1–2 from this objective — we provide 28 practice questions to prepare you well beyond it. (estimate)

28questions here

6free pages

6concepts

18%of the exam

Questions 26–28

26expert · hard
A company runs AI training jobs that have variable data access patterns. Some datasets are accessed heavily for a few weeks and then become cold. They use BlueXP and want to minimize storage costs while ensuring that data is available for retraining at any time. Which approach should they take?
Select an answer first
27application · medium
A financial services company is using BlueXP to manage AI training data that includes sensitive customer information. They must ensure that data is encrypted both at rest and in transit, and that only authorized AI engineers can access the datasets. Which BlueXP capability should they enable to meet these requirements?
Select an answer first
28application · medium
A government agency uses BlueXP to manage AI datasets that are subject to strict data residency requirements. They must ensure that data does not leave a specific geographic region. Which BlueXP configuration should they implement to meet this requirement?
Select an answer first

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Describe the Uses of BlueXP Software Tools to Build AI Solutions CERTIFIED-AI-EXPERT Practice Questions (Page 6)

Questions 26–28

A company runs AI training jobs that have variable data access patterns. Some datasets are accessed heavily for a few weeks and then become cold. They use BlueXP and want to minimize storage costs while ensuring that data is available for retraining at any time. Which approach should they take?

A government agency uses BlueXP to manage AI datasets that are subject to strict data residency requirements. They must ensure that data does not leave a specific geographic region. Which BlueXP configuration should they implement to meet this requirement?

Keep studying — AI Software Architectures