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Snowflake COF-C02 Practice Test - Questions Answers, Page 48

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Question 471

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What is the only supported character set for loading and unloading data from all supported file formats?

UTF-8
UTF-8
UTF-16
UTF-16
ISO-8859-1
ISO-8859-1
WINDOWS-1253
WINDOWS-1253
Suggested answer: A

Explanation:

UTF-8 is the only supported character set for loading and unloading data from all supported file formats in Snowflake. UTF-8 is a widely used encoding that supports a large range of characters from various languages, making it suitable for internationalization and ensuring data compatibility across different systems and platforms.

References:

Snowflake Documentation: Data Loading and Unloading

asked 23/09/2024
Sujit Singh
34 questions

Question 472

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Which statement accurately describes Snowflake's architecture?

It uses a local data repository for all compute nodes in the platform.
It uses a local data repository for all compute nodes in the platform.
It is a blend of shared-disk and shared-everything database architectures.
It is a blend of shared-disk and shared-everything database architectures.
It is a hybrid of traditional shared-disk and shared-nothing database architectures.
It is a hybrid of traditional shared-disk and shared-nothing database architectures.
It reorganizes loaded data into internal optimized, compressed, and row-based format.
It reorganizes loaded data into internal optimized, compressed, and row-based format.
Suggested answer: C

Explanation:

Snowflake's architecture is unique in that it combines elements of both traditional shared-disk and shared-nothing database architectures. This hybrid approach allows Snowflake to offer the scalability and performance benefits of a shared-nothing architecture (with compute and storage separated) while maintaining the simplicity and flexibility of a shared-disk architecture in managing data across all nodes in the system. This results in an architecture that provides on-demand scalability, both vertically and horizontally, without sacrificing performance or data cohesion.

References:

Snowflake Documentation: Snowflake Architecture

asked 23/09/2024
Arun Samuel
41 questions

Question 473

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Which use case does the search optimization service support?

Disjuncts (OR) in join predicates
Disjuncts (OR) in join predicates
LIKE/ILIKE/RLIKE join predicates
LIKE/ILIKE/RLIKE join predicates
Join predicates on VARIANT columns
Join predicates on VARIANT columns
Conjunctions (AND) of multiple equality predicates
Conjunctions (AND) of multiple equality predicates
Suggested answer: D

Explanation:

The search optimization service in Snowflake supports use cases involving conjunctions (AND) of multiple equality predicates. This service enhances the performance of queries that include multiple equality conditions by utilizing search indexes to quickly filter data without scanning entire tables or partitions. It's particularly beneficial for improving the response times of complex queries that rely on specific data matching across multiple conditions.

References:

Snowflake Documentation: Search Optimization Service

asked 23/09/2024
Aleksei Chernikov
47 questions

Question 474

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What are characteristics of transient tables in Snowflake? (Select TWO).

Transient tables have a Fail-safe period of 7 days.
Transient tables have a Fail-safe period of 7 days.
Transient tables can be cloned to permanent tables.
Transient tables can be cloned to permanent tables.
Transient tables persist until they are explicitly dropped.
Transient tables persist until they are explicitly dropped.
Transient tables can be altered to make them permanent tables.
Transient tables can be altered to make them permanent tables.
Transient tables have Time Travel retention periods of 0 or 1 day.
Transient tables have Time Travel retention periods of 0 or 1 day.
Suggested answer: B, C

Explanation:

Transient tables in Snowflake are designed for temporary or intermediate workloads with the following characteristics:

B . Transient tables can be cloned to permanent tables: This feature allows users to create copies of transient tables for permanent use, providing flexibility in managing data lifecycles.

C . Transient tables persist until they are explicitly dropped: Unlike temporary tables that exist for the duration of a session, transient tables remain in the database until explicitly removed by a user, offering more durability for short-term data storage needs.

References:

Snowflake Documentation: Transient Tables

asked 23/09/2024
Paulina Radziszewska
36 questions

Question 475

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What will happen if a Snowflake user increases the size of a suspended virtual warehouse?

The provisioning of new compute resources for the warehouse will begin immediately.
The provisioning of new compute resources for the warehouse will begin immediately.
The warehouse will remain suspended but new resources will be added to the query acceleration service.
The warehouse will remain suspended but new resources will be added to the query acceleration service.
The provisioning of additional compute resources will be in effect when the warehouse is next resumed.
The provisioning of additional compute resources will be in effect when the warehouse is next resumed.
The warehouse will resume immediately and start to share the compute load with other running virtual warehouses.
The warehouse will resume immediately and start to share the compute load with other running virtual warehouses.
Suggested answer: C

Explanation:

When a Snowflake user increases the size of a suspended virtual warehouse, the changes to compute resources are queued but do not take immediate effect. The provisioning of additional compute resources occurs only when the warehouse is resumed. This ensures that resources are allocated efficiently, aligning with Snowflake's commitment to cost-effective and on-demand scalability.

References:

Snowflake Documentation: Virtual Warehouses

asked 23/09/2024
Welton Harris
38 questions

Question 476

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How can a user get the MOST detailed information about individual table storage details in Snowflake?

SHOW TABLES command
SHOW TABLES command
SHOW EXTERNAL TABLES command
SHOW EXTERNAL TABLES command
TABLES view
TABLES view
TABLE STORAGE METRICS view
TABLE STORAGE METRICS view
Suggested answer: D

Explanation:

To obtain the most detailed information about individual table storage details in Snowflake, the TABLE STORAGE METRICS view is the recommended option. This view provides comprehensive metrics on storage usage, including data size, time travel size, fail-safe size, and other relevant storage metrics for each table. This level of detail is invaluable for monitoring, managing, and optimizing storage costs and performance.

References:

Snowflake Documentation: Information Schema

asked 23/09/2024
Felix Bourdier
47 questions

Question 477

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A developer is granted ownership of a table that has a masking policy. The developer's role is not able to see the masked data. Will the developer be able to modify the table to read the masked data?

Yes, because a table owner has full control and can unset masking policies.
Yes, because a table owner has full control and can unset masking policies.
Yes, because masking policies only apply to cloned tables.
Yes, because masking policies only apply to cloned tables.
No, because masking policies must always reference specific access roles.
No, because masking policies must always reference specific access roles.
No, because ownership of a table does not include the ability to change masking policies
No, because ownership of a table does not include the ability to change masking policies
Suggested answer: D

Explanation:

Even if a developer is granted ownership of a table with a masking policy, they will not be able to modify the table to read the masked data if their role does not have the necessary permissions. Ownership of a table does not automatically confer the ability to alter masking policies, which are designed to protect sensitive data.Masking policies are applied at the schema level and require specific privileges to modify12.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Masking Policies

asked 23/09/2024
Rene Claassen
38 questions

Question 478

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Which of the following describes how clustering keys work in Snowflake?

Clustering keys update the micro-partitions in place with a full sort, and impact the DML operations.
Clustering keys update the micro-partitions in place with a full sort, and impact the DML operations.
Clustering keys sort the designated columns over time, without blocking DML operations
Clustering keys sort the designated columns over time, without blocking DML operations
Clustering keys create a distributed, parallel data structure of pointers to a table's rows and columns
Clustering keys create a distributed, parallel data structure of pointers to a table's rows and columns
Clustering keys establish a hashed key on each node of a virtual warehouse to optimize joins at run-time
Clustering keys establish a hashed key on each node of a virtual warehouse to optimize joins at run-time
Suggested answer: B

Explanation:

Clustering keys in Snowflake work by sorting the designated columns over time. This process is done in the background and does not block data manipulation language (DML) operations, allowing for normal database operations to continue without interruption.The purpose of clustering keys is to organize the data within micro-partitions to optimize query performance1.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Clustering1

asked 23/09/2024
Ricardo Monsalve
38 questions

Question 479

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What is a machine learning and data science partner within the Snowflake Partner Ecosystem?

Informatica
Informatica
Power Bl
Power Bl
Adobe
Adobe
Data Robot
Data Robot
Suggested answer: D

Explanation:

Data Robot is recognized as a machine learning and data science partner within the Snowflake Partner Ecosystem. It provides an enterprise AI platform that enables users to build and deploy accurate predictive models quickly.As a partner, Data Robot integrates with Snowflake to enhance data science capabilities2.

References:

[COF-C02] SnowPro Core Certification Exam Study Guide

Snowflake Documentation on Machine Learning & Data Science Partners

https://docs.snowflake.com/en/user-guide/ecosystem-analytics.html

asked 23/09/2024
Oleksandr Kondratchuk
33 questions

Question 480

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Which of the following is a valid source for an external stage when the Snowflake account is located on Microsoft Azure?

An FTP server with TLS encryption
An FTP server with TLS encryption
An HTTPS server with WebDAV
An HTTPS server with WebDAV
A Google Cloud storage bucket
A Google Cloud storage bucket
A Windows server file share on Azure
A Windows server file share on Azure
Suggested answer: D

Explanation:

In Snowflake, when the account is located on Microsoft Azure, a valid source for an external stage can be an Azure container or a folder path within an Azure container. This includes Azure Blob storage which is accessible via theazure://endpoint. A Windows server file share on Azure, if configured properly, can be a valid source for staging data files for Snowflake.Options A, B, and C are not supported as direct sources for an external stage in Snowflake on Azure12.References:[COF-C02] SnowPro Core Certification Exam Study Guide

asked 23/09/2024
mariam alsallal
40 questions
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