A data team uses the NetApp DataOps toolkit to manage datasets for a natural language processing project. They need to create a new dataset that is a read-only copy of an existing dataset for validation purposes. Which toolkit feature should they use?

Use the DataOps API to export the dataset

Create a snapshot of the dataset

Copy the dataset to a new location

A data science team uses the NetApp DataOps toolkit to manage datasets for multiple concurrent experiments. They need to minimize storage consumption while ensuring that each experiment can modify its dataset without affecting others. They also need to be able to revert to a previous dataset version if an experiment fails. Which combination of practices best meets these needs?

Use clones for each experiment and snapshots for version control

Use snapshots for each experiment and clones for version control

Use a single shared dataset and rely on version control software

Use full copies for each experiment and delete them after completion

A data science team uses the NetApp DataOps toolkit to manage datasets for a training pipeline. They need to create a writable snapshot of a dataset so that a new experiment can modify data without affecting the original. Which toolkit capability should they use?

Mount the dataset as a network filesystem

Clone the dataset using the DataOps SDK

Create a read-only snapshot of the dataset

Restore the dataset from a backup

Which of the following is a common configuration step after installing the NetApp DataOps toolkit?

Deploying a dedicated database for metadata storage

Configuring a load balancer for the toolkit's web interface

Enabling GPU acceleration for data processing

Setting up credentials for the NetApp storage system

Which two components are main parts of the NetApp DataOps toolkit?

DataOps Connector and DataOps Agent

DataOps Dashboard and DataOps Monitor

NetAppCertified AI Expert

Domain 3Objective 3

Describe How the NetApp DataOps Toolkit Works 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 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

7concepts

18%of the exam

Questions 26–30

26application · medium
A data team uses the NetApp DataOps toolkit to manage datasets for a natural language processing project. They need to create a new dataset that is a read-only copy of an existing dataset for validation purposes. Which toolkit feature should they use?
Select an answer first
27expert · hard
A data science team uses the NetApp DataOps toolkit to manage datasets for multiple concurrent experiments. They need to minimize storage consumption while ensuring that each experiment can modify its dataset without affecting others. They also need to be able to revert to a previous dataset version if an experiment fails. Which combination of practices best meets these needs?
Select an answer first
28application · medium
A data science team uses the NetApp DataOps toolkit to manage datasets for a training pipeline. They need to create a writable snapshot of a dataset so that a new experiment can modify data without affecting the original. Which toolkit capability should they use?
Select an answer first
29foundation · easy
Which of the following is a common configuration step after installing the NetApp DataOps toolkit?
Select an answer first
30foundation · easy
Which two components are main parts of the NetApp DataOps toolkit?
Select an answer first

Finished these 5 questions?

Review the revealed explanations, or continue through the curriculum.

No more pagesBack to CERTIFIED-AI-EXPERT

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by NetApp. “CERTIFIED-AI-EXPERT” is a trademark of its owner, used for identification only.