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Snowflake Cloud Data Platform is a powerful tool that has revolutionized data warehousing and analytics. It has become the leading data cloud platform for data storage, integration, and analysis. Snowflake offers a highly scalable, highly available, and highly secure cloud data warehouse that allows businesses to rapidly generate insights from their data.

Snowflake COF-C02 certification exam is a challenging and rigorous process that requires a deep understanding of Snowflake's data warehousing and analytics technologies. COF-C02 exam is designed to test the candidate's ability to work with large volumes of data and to optimize performance for complex queries. Candidates who pass the exam are recognized as experts in Snowflake's technology and are highly sought after by employers who use Snowflake's platform for data warehousing and analytics.

Snowflake COF-C02 (SnowPro Core Certification) Certification Exam is designed to test an individual's knowledge and proficiency with the Snowflake data platform. Snowflake is a cloud-based data warehousing and analytics platform that allows organizations to store, manage, and analyze large amounts of data in the cloud. The SnowPro Core Certification Exam is an essential step for data professionals who want to demonstrate their expertise in Snowflake and advance their careers.

Snowflake SnowPro Core Certification Exam Sample Questions (Q397-Q402):

NEW QUESTION # 397
Which database objects can be shared with Secure Data Sharing? (Select TWO).

A. Views
B. External tables
C. Materialized views
D. External stages
E. Dynamic tables

Answer: A,E

Explanation:
* Secure Data Sharing allows sharing the following objects:
* Views (A): Logical objects that allow controlled data sharing without exposing the underlying tables.
* Dynamic tables (E): Can be shared to provide real-time data access while maintaining security.
Other Notes:
* Materialized views (B): Cannot be directly shared.
* External stages (C): Cannot be shared through Secure Data Sharing.
* External tables (D): Data remains outside Snowflake and cannot be shared directly.
References:
* Snowflake Documentation: Secure Data Sharing
* Objects Supported for Sharing

NEW QUESTION # 398
Which command sets the Virtual Warehouse for a session?

A. SET WAREHOUSE = <<warehouse name>>;
B. USE VIRTUAL_WAREHOUSE <<warehouse name>>;
C. USE WAREHOUSE <<warehouse name>>;
D. COPY WAREHOUSE FROM <<config file>>;

Answer: C

NEW QUESTION # 399
What is the MINIMUM permission needed to access a file URL from an external stage?

A. USAGE
B. READ
C. MODIFY
D. SELECT

Answer: B

NEW QUESTION # 400
Which command should be used to load data incrementally based on column values that are specified in the source table or subquery?

A. MERGE
B. COPY INTO
C. INSERT INTO
D. GET

Answer: A

Explanation:
The MERGE command in Snowflake is used for incremental loading based on column values in a source table or subquery. It enables the insertion, updating, or deletion of records in a target table depending on whether matching rows are found, making it ideal for loading data that changes incrementally, such as daily updates or modifications.

NEW QUESTION # 401
A Snowflake user is trying to load a 125 GB file using SnowSQL. The file continues to load for almost an entire day. What will happen at the 2< hour mark?

A. The file will continue to load until all contents arc loaded.
B. The file loading could be aborted without any portion of the file being committed.
C. The tile will slop loading and all data up to that point will be committed.
D. The file's number of allowable hours to load can be programmatically controlled to load easily into Snowflake

Answer: B

Explanation:
When attempting to load large files, such as a 125 GB file, into Snowflake using SnowSQL, the process might encounter limitations related to the maximum execution time for queries or data loading operations. If the loading process exceeds this time limit (typically around 24 hours), it could be aborted without committing any part of the file to the database. This behavior is designed to prevent indefinite resource consumption and to maintain system stability, emphasizing the need for optimizing data load operations, possibly through file segmentation or parallel loading strategies.References: Snowflake Documentation on Data Loading Considerations

NEW QUESTION # 402
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