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Pass Guaranteed Quiz 2025 COF-C02: Newest New SnowPro Core Certification Exam Braindumps Questions

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Three Easy-to-Use and Compatible Real4dumps Snowflake COF-C02 Exam Questions

Real4dumps insists on providing you with the best and high quality exam dumps, aiming to ensure you 100% pass in the actual test. Being qualified with Snowflake certification will bring you benefits beyond your expectation. Our COF-C02 practice training material will help you to enhance your specialized knowledge and pass your actual test with ease. COF-C02 Questions are all checked and verified by our professional experts. Besides, the COF-C02 answers are all accurate which ensure the high hit rate.

Snowflake SnowPro Core Certification Exam Sample Questions (Q551-Q556):

NEW QUESTION # 551
Which SQL commands, when committed, will consume a stream and advance the stream offset? (Choose two.)

A. UPDATE TABLE FROM STREAM
B. BEGIN COMMIT
C. SELECT FROM STREAM
D. INSERT INTO TABLE SELECT FROM STREAM
E. ALTER TABLE AS SELECT FROM STREAM

Answer: A,D

Explanation:
The SQL commands that consume a stream and advance the stream offset are those that result in changes to the data, such as UPDATE and INSERT operations. Specifically, 'UPDATE TABLE FROM STREAM' and 'INSERT INTO TABLE SELECT FROM STREAM' will consume the stream and move the offset forward, reflecting the changes made to the data.

NEW QUESTION # 552
When publishing a Snowflake Data Marketplace listing into a remote region what should be taken into consideration? (Choose two.)

A. There is no need to have a Snowflake account in the target region, a share will be created for each user.
B. Shares attached to listings in remote regions can be viewed from any account in an organization.
C. The user must have the ORGADMIN role available in at least one account to link accounts for replication.
D. The listing is replicated into all selected regions automatically, the data is not.
E. For a standard listing the user can wait until the first customer requests the data before replicating it to the target region.

Answer: A,C

NEW QUESTION # 553
How can staged files be removed during data loading once the files have loaded successfully?

A. Use the DROP command
B. Use the FORCE = TRUE parameter
C. Use the LOAD UNCERTAIN FILES copy option.
D. Use the purge copy option.

Answer: D

Explanation:
To remove staged files during data loading after they have been successfully loaded, thePURGEcopy option is used in Snowflake.
* PURGE Option: This option automatically deletes files from the stage after they have been successfully copied into the target table.
* Usage:
FROM @my_stage
FILE_FORMAT = (type = 'csv')
PURGE = TRUE;
References:
* Snowflake Documentation on COPY INTO

NEW QUESTION # 554
At what level is the MIN_DATA_RETENSION_TIME_IN_DAYS parameter set?

A. Table
B. Database
C. Schema
D. Account

Answer: D

Explanation:
The MIN_DATA_RETENTION_TIME_IN_DAYS parameter is set at the Account level in Snowflake. This parameter specifies the minimum number of days Snowflake retains the historical data for time travel, which allows users to access and query data as it existed at previous points in time.
Here's how to understand and adjust this parameter:
Purpose of MIN_DATA_RETENTION_TIME_IN_DAYS: This parameter is crucial for managing data lifecycle and compliance requirements within Snowflake. It determines the minimum time frame for which you can perform operations like restoring deleted objects or accessing historical versions of data.
Setting the Parameter: Only account administrators can set or modify this parameter. It is done at the account level, impacting all databases and schemas within the account. The setting can be adjusted based on the organization's data retention policy.
Adjusting the Parameter:
To view the current setting, use:
SHOW PARAMETERS LIKE 'MIN_DATA_RETENTION_TIME_IN_DAYS';
To change the setting, an account administrator can execute:
ALTER ACCOUNT SET MIN_DATA_RETENTION_TIME_IN_DAYS = <number_of_days>;

NEW QUESTION # 555
Which data formats are supported by Snowflake when unloading semi-structured data? (Select TWO).

A. Plain text file containing XML elements
B. Binary file in Avro
C. Comma-separated JSON
D. Newline Delimited JSON
E. Binary file in Parquet

Answer: D,E

Explanation:
Snowflake supports a variety of file formats for unloading semi-structured data, among which Parquet and Newline Delimited JSON (NDJSON) are two widely used formats.
* B. Binary file in Parquet: Parquet is a columnar storage file format optimized for large-scale data processing and analysis. It is especially suited for complex nested data structures.
* D. Newline Delimited JSON (NDJSON): This format represents JSON records separated by newline
* characters, facilitating the storage and processing of multiple, separate JSON objects in a single file.
These formats are chosen for their efficiency and compatibility with data analytics tools and ecosystems, enabling seamless integration and processing of exported data.
References:
* Snowflake Documentation: Data Unloading

NEW QUESTION # 556
......

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