Most Recent Snowflake SnowPro-Core Exam Questions & Answers

Prepare for the Snowflake SnowPro Core Certification Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Snowflake SnowPro-Core exam and achieve success.

The questions for SnowPro-Core were last updated on Nov 18, 2024.

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Question No. 1

What COPY INTO SQL command should be used to unload data into multiple files?

ASINGLE=TRUE

BMULTIPLE=TRUE

CMULTIPLE=FALSE

DSINGLE=FALSE

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Correct Answer: D

The COPY INTO SQL command with the optionSINGLE=FALSEis used to unload data into multiple files. This option allows the data to be split into multiple files during the unload process.Reference:SnowPro Core Certification COPY INTO SQL command unload multiple files

Question No. 2

What is the maximum total Continuous Data Protection (CDP) charges incurred for a temporary table?

A30 days

B7 days

C48 hours

D24 hours

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Correct Answer: D

For a temporary table, the maximum total Continuous Data Protection (CDP) charges incurred are for the duration of the session in which the table was created, which does not exceed 24 hours2.

Reference = [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation2

Question No. 3

Which statement describes pruning?

AThe filtering or disregarding of micro-partitions that are not needed to return a query.

BThe return of micro-partitions values that overlap with each other to reduce a query's runtime.

CA service that is handled by the Snowflake Cloud Services layer to optimize caching.

DThe ability to allow the result of a query to be accessed as if it were a table.

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Correct Answer: A

Pruning in Snowflake refers to the process of filtering or disregarding micro-partitions that are not needed to satisfy the conditions of a query.This optimization technique helps reduce the amount of data scanned, thereby improving query performance

Question No. 4

Which system_defined Snowflake role has permission to rename an account and specify whether the original URL can be used to access the renamed account?

AACCOUNTADMIN

BSECURITYADMIN

CSYSADMIN

DORGADMIN

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Correct Answer: A

The ACCOUNTADMIN role in Snowflake has the highest level of privileges, including the ability to manage accounts, users, roles, and all objects within the account. This role is specifically granted the permission to rename an account and specify whether the original URL can be used to access the renamed account. The ACCOUNTADMIN role encompasses broad administrative capabilities, ensuring that users assigned this role can perform critical account management tasks. Reference: Snowflake Documentation on Roles and Permissions

Question No. 5

What are value types that a VARIANT column can store? (Select TWO)

ASTRUCT

BOBJECT

CBINARY

DARRAY

ECLOB

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Correct Answer: B, D

A VARIANT column in Snowflake can store semi-structured data types. This includes:

B . OBJECT: An object is a collection of key-value pairs in JSON, and a VARIANT column can store this type of data structure.

D . ARRAY: An array is an ordered list of zero or more values, which can be of any variant-supported data type, including objects or other arrays.

The VARIANT data type is specifically designed to handle semi-structured data like JSON, Avro, ORC, Parquet, or XML, allowing for the storage of nested and complex data structures.

Snowflake Documentation on Semi-Structured Data Types

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