Network Appliance NS0-901

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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. A financial services company is required by regulators to be able to trace any version of their deployed fraud detection model back to the exact dataset and source code commit used to train it.
The current MLOps workflow is as follows:
Code_Repository: Git (commit hash: a1b2c3d4)
Dataset_Location: /vol/prod_data/fraud_dataset_v3
Storage_System: NetApp ONTAP 9
Model_Output: /vol/models/fraud_model_v3.2
Which NetApp technology should be used to create an immutable, point-in-time, and space- efficient copy of the dataset that can be linked to the specific code commit and model version?

A) NetApp SnapMirror
B) NetApp FlexClone
C) NetApp FabricPool
D) NetApp Snapshots

2. An AI operations team is troubleshooting why their RAG-based chatbot is providing outdated information. They have confirmed that the vector database embedding process is functioning correctly, but suspect an issue with the initial data synchronization that moves the knowledge base from an on- premises ONTAP file share to a cloud staging bucket.
They inspect the relevant BlueXP copy and sync job and find the following details:
Service: BlueXP copy and sync
Relationship_Name: KB_Sync_to_Vector_Staging
Source: nfs://ontap-cluster-1/vol_kb/docs
Destination: s3://vector-staging-bucket-89a3/latest/
Last_Sync_Status: FAILED
Last_Sync_Time: 2025-07-11T02:00:15Z
Error_Message: "Authentication error:
Unable to access source.
Check export policy on 'vol_kb'."
Based on this information, what is the most direct solution to fix the data pipeline?

A) Modify the NFS export policy on the 'vol_kb' volume on the on-premises ONTAP cluster to grant access to the BlueXP Connector.
B) Fine-tune the LLM with the latest data instead of using the RAG system.
C) Check the IAM permissions for the role associated with the S3 bucket.
D) Re-run the vector database embedding job.

3. Which of the following best describes the difference between data lakes, data warehouses, and lakehouses?

A) Data lakes store structured data, data warehouses store unstructured data, and lakehouses store only real-time data.
B) Data lakes store raw, unstructured data, data warehouses store structured data, and lakehouses combine the features of both.
C) Data lakes store metadata, data warehouses store transaction data, and lakehouses store archival data.
D) Data lakes store data in cloud storage, data warehouses store it in traditional databases, and lakehouses store it in external drives.

4. A team has deployed a Retrieval-Augmented Generation (RAG) system to answer customer queries. Recently, users have complained that the answers provided by the chatbot are outdated and do not reflect the latest product updates. An architect investigates and finds the following status log from the RAG pipeline's data ingestion monitor.
Timestamp: 2025-07-11T14:00:00Z
System: RAG Pipeline Monitor
Status: WARNING
Message: Vector DB freshness check failed.
Source data appears stale.
Vector_DB_Last_Update: 2025-06-10T08:00:00Z
Knowledge_Base_Last_Modified: 2025-07-11T13:15:00Z
Data_Sync_Service: BlueXP copy and sync
Sync_Job_Status: Succeeded
Based on the log, what is the most likely cause of the outdated answers?

A) The process that converts staged documents into vectors and updates the vector database is not running.
B) The BlueXP copy and sync service is failing to copy data to the staging area.
C) The knowledge base itself has not been updated with the latest product information.
D) The LLM needs to be fine-tuned with the new product information.

5. A national research laboratory is investing in a turnkey AI infrastructure solution. Their primary goal is to eliminate the complexity and risk of designing and integrating the compute, network, and storage components themselves. The solution must be pre-validated by the vendors to deliver predictable, linear performance as they scale from one to multiple compute nodes. Which two options represent this type of pre-validated, converged infrastructure solution for AI? (Choose two)

A) A single NetApp FAS system connected directly to a single server.
B) A public cloud provider's general-purpose virtual machine instances.
C) A Cisco and NetApp FlexPod for AI solution.
D) A custom-built server rack with components sourced from various different vendors.
E) NetApp AIPod, which integrates NVIDIA DGX servers with NetApp storage and networking.

Solutions: