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SnowPro® Specialty: Gen AI Certification
Exam Latest Version: 6.1 Practice Exam
Newest 2026.
Q1. What is the primary purpose of Snowflake Cortex AI?
A) A data warehousing solution for structured data only
B) A suite of fully managed Large Language Model (LLM)
functions and AI services for building Gen AI applications
C) A machine learning library for custom model training
D) A data visualization tool for AI insights
Answer: B
Rationale: Snowflake Cortex AI is a fully managed, serverless
suite of LLM functions and AI services designed to help
developers build Gen AI applications directly within Snowflake
using their data. It operates on the principle of bringing
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intelligence to the data rather than moving data to the
intelligence .
Q2. Which Snowflake service allows you to run containerized
applications, including open-source models, within the
Snowflake environment?
A) Snowflake Streams
B) Snowpark Container Services
C) Snowflake Tasks
D) Snowflake Dynamic Tables
Answer: B
Rationale: Snowpark Container Services (SPCS) enables you to
run containerized applications, including custom machine learning
models and open-source LLMs, directly within the Snowflake
ecosystem. This provides secure, governed access to Snowflake
data .
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Q3. According to Snowflake documentation, what are the key
architectural principles of the Snowflake AI Data Cloud?
(Select all that apply)
A) Separation of storage and compute
B) Elastic scalability
C) Single, monolithic architecture
D) Data governance and security
Answer: A, B, D
Rationale: The Snowflake AI Data Cloud is built on three core
architectural principles: separation of storage and compute
(allowing independent scaling), elastic scalability (handling
varying workloads), and strong data governance/security
features. It is not monolithic; it is a distributed, multi-cluster
platform .
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Q4. A company wants to build a Gen AI application that uses
both structured (sales data) and unstructured (customer
support transcripts) data. What is the recommended Snowflake
architecture for this use case?
A) Load all data into a single, large table
B) Process unstructured data outside Snowflake and bring only
the results back
C) Use Snowflake’s native support for both structured data
(tables) and unstructured data (stages) with Cortex AI functions
for processing
D) Convert all unstructured data to structured format before
loading
Answer: C
Rationale: Snowflake natively supports structured data (in tables)
and unstructured data (in stages). Cortex AI functions
(e.g., PARSE_DOCUMENT, COMPLETE) can directly process
SnowPro® Specialty: Gen AI Certification
Exam Latest Version: 6.1 Practice Exam
Newest 2026.
Q1. What is the primary purpose of Snowflake Cortex AI?
A) A data warehousing solution for structured data only
B) A suite of fully managed Large Language Model (LLM)
functions and AI services for building Gen AI applications
C) A machine learning library for custom model training
D) A data visualization tool for AI insights
Answer: B
Rationale: Snowflake Cortex AI is a fully managed, serverless
suite of LLM functions and AI services designed to help
developers build Gen AI applications directly within Snowflake
using their data. It operates on the principle of bringing
,Page 2 of 145
intelligence to the data rather than moving data to the
intelligence .
Q2. Which Snowflake service allows you to run containerized
applications, including open-source models, within the
Snowflake environment?
A) Snowflake Streams
B) Snowpark Container Services
C) Snowflake Tasks
D) Snowflake Dynamic Tables
Answer: B
Rationale: Snowpark Container Services (SPCS) enables you to
run containerized applications, including custom machine learning
models and open-source LLMs, directly within the Snowflake
ecosystem. This provides secure, governed access to Snowflake
data .
,Page 3 of 145
Q3. According to Snowflake documentation, what are the key
architectural principles of the Snowflake AI Data Cloud?
(Select all that apply)
A) Separation of storage and compute
B) Elastic scalability
C) Single, monolithic architecture
D) Data governance and security
Answer: A, B, D
Rationale: The Snowflake AI Data Cloud is built on three core
architectural principles: separation of storage and compute
(allowing independent scaling), elastic scalability (handling
varying workloads), and strong data governance/security
features. It is not monolithic; it is a distributed, multi-cluster
platform .
, Page 4 of 145
Q4. A company wants to build a Gen AI application that uses
both structured (sales data) and unstructured (customer
support transcripts) data. What is the recommended Snowflake
architecture for this use case?
A) Load all data into a single, large table
B) Process unstructured data outside Snowflake and bring only
the results back
C) Use Snowflake’s native support for both structured data
(tables) and unstructured data (stages) with Cortex AI functions
for processing
D) Convert all unstructured data to structured format before
loading
Answer: C
Rationale: Snowflake natively supports structured data (in tables)
and unstructured data (in stages). Cortex AI functions
(e.g., PARSE_DOCUMENT, COMPLETE) can directly process
