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Exam SOL-C01 PDF | SOL-C01 Valid Exam Testking

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Snowflake SOL-C01 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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 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.

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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q125-Q130):

NEW QUESTION # 125
You have a Snowflake database named 'SALES DB' containing schemas 'RAW' and
'TRANSFORMED'. The 'RAW' schema holds raw data ingested from various sources, and the
'TRANSFORMED' schema contains cleansed and transformed data ready for reporting. You need to grant the 'DATA ANALYST' role the ability to read all tables in the 'TRANSFORMED' schema but prevent them from modifying any objects. What is the MOST efficient and secure way to achieve this?

A. GRANT SELECT ON ALL TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
B. GRANT SELECT ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
C. GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST; GRANT USAGE ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST; GRANT SELECT ON FUTURE TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;
D. GRANT ALL PRIVILEGES ON SCHEMA SALES DB.TRANSFORMED TO ROLE DATA
ANALYST;
E. GRANT USAGE ON DATABASE SALES DB TO ROLE DATA ANALYST; GRANT SELECT ON FUTURE TABLES IN SCHEMA SALES DB.TRANSFORMED TO ROLE DATA ANALYST;

Answer: C

Explanation:
The most efficient and secure approach is to grant USAGE on the DATABASE and SCHEMA, and SELECT on FUTURE TABLES (C). USAGE privilege on the database allows the role to access objects within the database. USAGE on the schema allows access to the schema.
Granting SELECT on FUTURE TABLES ensures that any new tables created in the TRANSFORMED schema will automatically inherit the SELECT privilege for the DATA ANALYST role. Option A only grants SELECT on existing tables, not future ones. Option D grants ALL PRIVILEGES, which is too permissive. Option E is insufficient as it doesn't grant required privileges on Database and Schema. Option B is partially correct but misses granting usage on SCHEMA.

NEW QUESTION # 126
What is a key benefit of using Streamlit for data visualization in Snowflake notebooks?

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

Answer: C

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 # 127
What are characteristics of schemas in Snowflake? (Select TWO).

A. A schema is contained in a database.
B. Each schema is available to a single role.
C. Schemas contain virtual warehouses.
D. A schema is an immutable object.
E. Schemas are used to organize database objects.

Answer: A,E

Explanation:
Schemas in Snowflake serve asorganizational containersfor database objects such as tables, views, sequences, stages, file formats, and functions. They existwithin a database, forming Snowflake's logical hierarchy:
account # database # schema # object.
Schemas are not limited to a single role; access depends on granted privileges. Schemas are not immutable- administrators can rename, alter, or drop them. Schemas do not contain virtual warehouses; warehouses exist independently at the account level.
Thus, the correct characteristics are that schemas organize objects and are contained within a database.

NEW QUESTION # 128
Which of the following are date and time data types in Snowflake? (Choose any 3 options)

A. DATETIME
B. DATE
C. Python
D. TIMESTAMP
E. TIMEDATE
F. JavaScript

Answer: A,B,D

Explanation:
Snowflake supports several native data types for managing temporal information:
DATE - Stores dates only (year, month, day) without any time component.
TIMESTAMP - Represents date and time values, including several variants:
* TIMESTAMP_NTZ (no time zone)
* TIMESTAMP_LTZ (local time zone)
* TIMESTAMP_TZ (explicit time zone)
DATETIME - An alias for TIMESTAMP_NTZ, storing both date and time.
These data types enable powerful time-based analytics and comparisons.
#TIMEDATE is not a valid data type.
#Python and JavaScript are programming languages, not Snowflake data types.

NEW QUESTION # 129
Consider the following Snowflake warehouse definition: 'CREATE OR REPLACE WAREHOUSE MY WAREHOUSE WITH WAREHOUSE SIZE = 'MEDIUM' WAREHOUSE TYPE = 'STANDARD' AUTO SUSPEND = 300 AUTO RESUME = TRUE MIN CLUSTER_COUNT = 1 MAX CLUSTER_COUNT = 3 SCALING_POLICY = 'ECONOMY;' Which of the following statements are TRUE regarding this warehouse? (Select all that apply)

A. The warehouse will automatically suspend after 5 minutes of inactivity.
B. The warehouse will always have at least one active cluster.
C. The 'WAREHOUSE_TYPE = 'STANDARD" setting is invalid and will cause an error.
D. The warehouse is optimized for minimizing costs rather than maximizing performance when scaling.
E. The warehouse can scale up to a maximum of three clusters to handle concurrent queries.

Answer: A,B,D,E

Explanation:
The warehouse will auto-suspend after 300 seconds (5 minutes) of inactivity (A). = 1 ` ensures at least one active cluster (B). = 3' allows scaling to three clusters (C). 'SCALING_POLICY =
'ECONOMY" prioritizes cost savings over immediate performance during scaling (D).
'WAREHOUSE_TYPE = 'STANDARD'` is a valid setting, it defines the warehouse as using the standard model for resource management.

NEW QUESTION # 130
......

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