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Snowflake SOL-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	Snowflake Certified SnowPro Associate - Platform Certification
Exam Number:	SOL-C01
Passing Score:	750
Exam Duration:	85 minutes
Exam Format:	Multiple Select, Multiple Choice, Interactive
Certificate Validity Period:	2 years
Real Exam Qty:	65
Related Certifications:	SnowPro Core Certification
Exam Price:	$100 USD
Available Languages:	Chinese, English, Japanese
Sample Questions:	Snowflake SOL-C01 Sample Questions
Exam Way:	Unproctored online exam delivered through Pearson VUE. Once purchased, you have 24 hours to launch and complete the exam. Must be completed within 85 minutes from starting with no exceptions.
Pre Condition:	No prerequisites. Target audience: individuals with 3+ months of knowledge using Snowflake.
Official Syllabus URL:	https://learn.snowflake.com/en/pages/snowpro-platform-announcementFAQs

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Snowflake SOL-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Interacting with Snowflake and the Architecture: This domain covers Snowflake's elastic architecture, key user interfaces like Snowsight and Notebooks, and the object hierarchy including databases, schemas, tables, and views with practical navigation and code execution skills.
Topic 2	Data Protection and Data Sharing: This domain addresses continuous data protection through Time Travel and cloning, plus data collaboration capabilities via Snowflake Marketplace and private Data Exchange sharing.
Topic 3	Data Loading and Virtual Warehouses: This domain covers loading structured, semi-structured, and unstructured data using stages and various methods, virtual warehouse configurations and scaling strategies, and Snowflake Cortex LLM functions for AI-powered operations.
Topic 4	Identity and Data Access Management: This domain focuses on Role-Based Access Control (RBAC) including role hierarchies and privileges, along with basic database administration tasks like creating objects, transferring ownership, and executing fundamental SQL commands.

Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q116-Q121):

NEW QUESTION # 116
Which SQL command is used to create a new database in Snowflake?

A. USE DATABASE database_name;
B. USE DB database_name;
C. CREATE DB database_name;
D. CREATE DATABASE database_name;

Answer: D

Explanation:
The correct SQL command for creating a new database in Snowflake isCREATE DATABASE database_name;. This initializes a new logical container for schemas and objects. USE DATABASE switches the active database context but does not create one. Snowflake does not support the shorthand CREATE DB or USE DB syntax. Therefore, CREATE DATABASE is the correct and only valid command for creating a database.

NEW QUESTION # 117
How does Snowflake process queries?

A. By optimizing data in cloud storage
B. Using MPP compute clusters
C. Through third-party connectors
D. With shared-disk architecture

Answer: B

Explanation:
Snowflake processes queries usingMassively Parallel Processing (MPP)compute clusters, deployed as virtual warehouses. Each warehouse consists of multiple compute nodes working in parallel to execute queries efficiently. When a query is submitted, Snowflake distributes tasks across nodes, processes data subsets concurrently, and aggregates results. This architecture enables high performance, scalability, and the ability to handle complex analytical workloads. While Snowflake does incorporate elements of shared-disk storage, query execution itself depends on MPP compute clusters. Options such as third-party connectors or storage optimization do not represent the core query processing mechanism.

NEW QUESTION # 118
You are tasked with creating a development environment from a production database in Snowflake. The production database,
'PROD DB', is very large and you need to minimize the storage costs and time required for the cloning operation. The development environment should be isolated and allow developers to make changes without affecting production data. Which of the following approaches is the most efficient and cost- effective?

A. Export the data from 'PROD to cloud storage, create a new database 'DEV DBS, and import the data.Then grant access to developers.
B. Create a zero-copy clone of 'PROD DB' using 'CREATE DATABASE DEV DB CLONE PROD DB;'
C. Create a full backup of restore it to a new database 'DEV_DB', and then grant access to developers.
D. Create a full clone of 'PROD_Dff using 'CREATE DATABASE DEV_DB CLONE PROD_DB;'
E. Create a zero-copy clone of 'PROD_DB' using 'CREATE DATABASE DEV_DB CLONE PROD_DB BEFORE (TIMESTAMP '2023-01-01 and then grant access to developers.

Answer: B

Explanation:
Snowflake cloning is a zero-copy operation. Using 'CREATE DATABASE DEV_DB CLONE PROD_DB',' creates a metadata copy instantly. The storage is only consumed when changes are made to the cloned database 'DEV DBA. This is the most efficient and cost-effective method. A, D, and E involve full data duplication which is slower and more expensive. C is also zero copy cloning but refers to a specific timestamp, which wasn't a requirement of the question.

NEW QUESTION # 119
What is the primary purpose of the CLASSIFY_TEXT function in Cortex?

A. Classifying text into predefined categories
B. Extracting data from documents
C. Translating text to different languages
D. Generating text completions based on a given prompt

Answer: A

Explanation:
TheCLASSIFY_TEXTfunction performscategory assignmentfor free-form text. Users provide a list of predefined labels, and the function predicts the most appropriate category using a Snowflake-optimized LLM.
It is ideal for automatically tagging customer feedback, routing support tickets, labeling product reviews, classifying email content, and segmenting operational logs.
The function outputs both the predicted label and an associated confidence score, enabling downstream filtering, dashboarding, and automated processing.
Other options belong to different Cortex functions:
* TRANSLATEhandles multilingual translation.
* COMPLETEgenerates natural language completions.
* PARSE_DOCUMENTextracts structured information from documents.
Thus, CLASSIFY_TEXT is task-specific and optimized specifically for classification workloads.

NEW QUESTION # 120
What is a key benefit of using Streamlit for data visualization in Snowflake notebooks?

A. Real-time interactivity and dynamic visualizations
B. Manual data storage
C. Simplified code execution
D. Fixed-size compute clusters

Answer: A

Explanation:
Streamlit inside Snowflake Notebooks enables users to buildinteractive, real-time visualizations and data applicationsdirectly within Snowsight. Because Streamlit is event-driven, users can create UI components such as sliders, dropdowns, date pickers, buttons, and filters that dynamically update charts, tables, and computed outputs.
Data remains inside Snowflake, processed through Python with Snowpark, eliminating data movement to external systems. This allows rapid prototyping of dashboards, analytical workflows, and AI-driven apps.
Streamlit also supports layout customization, reactive components, and seamless integration with Snowflake compute for scalable analytics.
Incorrect options:
* Streamlit doesnotmanage data storage.
* Streamlit does not simplify code execution; it enhances visualization and interactivity.
* Warehouse clusters are not fixed-size-Snowflake warehouses can scale.
Thus, its primary benefit is enablingrich interactive analytics directly within Snowflake.

NEW QUESTION # 121
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