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Snowflake SnowPro-Core Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	SnowPro Core Certification Exam
Exam Number:	COF-C02
Certificate Validity Period:	2 years
Exam Duration:	115 minutes
Passing Score:	750/1000
Exam Format:	Multiple Select, Multiple Choice
Available Languages:	Japanese, English
Exam Price:	USD 175
Related Certifications:	SnowPro Advanced: Data Engineer SnowPro Advanced: Architect SnowPro Advanced: Administrator
Real Exam Qty:	100
Recommended Training:	Snowflake Training Courses
Exam Registration:	Snowflake Certification Portal
Sample Questions:	Snowflake SnowPro-Core Sample Questions
Exam Way:	Online proctored or onsite testing center
Pre Condition:	No formal prerequisites required; basic knowledge of SQL and cloud concepts recommended.
Official Syllabus URL:	https://www.snowflake.com/certifications/snowpro-core/

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SnowPro-Core is a certification exam that measures a professional's ability to work with Snowflake's cloud-based data warehousing platform. SnowPro-Core exam is designed to test the candidate's proficiency in various areas, including data loading, querying data, performance optimization, and security. Passing the SnowPro-Core Exam demonstrates that the candidate has a deep understanding of Snowflake's architecture and can perform tasks such as data modeling, data integration, and data migration.

Snowflake SnowPro Core Certification Exam Sample Questions (Q594-Q599):

NEW QUESTION # 594
Which semi-structured file format is a compressed, efficient, columnar data representation?

A. JSON
B. Parquet
C. TSV
D. Avro

Answer: B

Explanation:
Parquet is a columnar storage file format that is optimized for efficiency in both storage and processing. It supports compression and encoding schemes that significantly reduce the storage space needed and speed up data retrieval operations, making it ideal for handling large volumes of data. Unlike JSON or TSV, which are row-oriented and typically uncompressed, Parquet is designed specifically for use with big data frameworks, offering advantages in terms of performance and cost when storing and querying semi-structured data.References: Apache Parquet Documentation

NEW QUESTION # 595
Which of the following indicates that it may be appropriate to use a clustering key for a table? (Select TWO).

A. The table has a small number of micro-partitions
B. The clustering depth for the table is large
C. The table contains a column that has very low cardinality
D. DML statements that are being issued against the table are blocked
E. Queries on the table are running slower than expected

Answer: B,C

NEW QUESTION # 596
How can a Snowflake user optimize query performance in Snowflake? (Select TWO).

A. Index a table.
B. Create a view.
C. Enable the search optimization service.
D. Cluster a table.
E. Enable Time Travel.

Answer: C,D

NEW QUESTION # 597
A sales table FCT_SALES has 100 million records.
The following Query was executed
SELECT COUNT (1) FROM FCT__SALES;
How did Snowflake fulfill this query?

A. Query against the result set cache
B. Query against a virtual warehouse cache
C. Query against the most-recently created micro-partition
D. Query against the metadata excite

Answer: D

NEW QUESTION # 598
If 3 size Small virtual warehouse is made up of two servers, how many servers make up a Large warehouse?

A. 0
B. 1
C. 2
D. 3

Answer: B

Explanation:
Explanation
Size specifies the amount of compute resources available per cluster in a warehouse. Snowflake supports the following warehouse sizes:

https://docs.snowflake.com/en/user-guide/warehouses-overview.html

NEW QUESTION # 599
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