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Snowflake COF-C02 Exam Syllabus Topics:

SectionWeightObjectives
Data Protection & Data Sharing10%- Secure data sharing
  • 1. Direct sharing, data exchanges, reader accounts
  • 2. Sharing security and access control
- Data recovery & retention
  • 1. Time Travel, Fail-safe, cloning capabilities
  • 2. Data retention policies and backup
Account Access & Security20%- Data protection & governance
  • 1. Encryption at rest and in transit
  • 2. Data masking and row-level security
- Authentication & authorization
  • 1. Users, roles, privileges and access control
  • 2. Network policies and security settings
Snowflake Architecture & Cloud Concepts25%- Cloud data platform fundamentals
  • 1. Service layers and separation of storage/compute
  • 2. Data storage structure and formats
  • 3. Virtual warehouses and resource management
- Account structure and hierarchy
  • 1. Object ownership and naming conventions
  • 2. Organization, account, database, schema levels
Data Pipelines & Automation10%- Integration & connectivity
  • 1. Connectors and ETL/ELT patterns
  • 2. External functions and API integration
- Workflow & automation
  • 1. Change data capture and processing
  • 2. Streams, tasks, and pipes
Performance Concepts & Optimization15%- Warehouse sizing & tuning
  • 1. Scaling, clustering, and concurrency management
  • 2. Query profiling and optimization techniques
- Data optimization features
  • 1. Caching and result reuse
  • 2. Clustering keys, search optimization, materialized views
Data Loading & Transformation20%- Data ingestion methods
  • 1. File formats and data type handling
  • 2. Bulk loading, continuous loading, external stages
- Data transformation & querying
  • 1. Working with structured, semi-structured, unstructured data
  • 2. DDL/DML operations and SQL functions

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Snowflake SnowPro Core Certification Exam Sample Questions (Q916-Q921):

NEW QUESTION # 916
What information is stored in the ACCESS_HlSTORY view?

Answer: B

Explanation:
Details around the privileges that have been granted for all objects in an account. The ACCESS_HISTORY view in Snowflake provides a comprehensive log of access control changes, including grants and revocations of privileges on all securable objects within the account. This information is crucial for auditing and monitoring the security posture of your Snowflake environment.
Here's how to understand and use the ACCESS_HISTORY view:
Purpose of ACCESS_HISTORY View: It is designed to track changes in access controls, such as when a user or role is granted or revoked privileges on various Snowflake objects. This includes tables, schemas, databases, and more.
Querying ACCESS_HISTORY: To access this view, you can use the following SQL query pattern:
SELECT * FROM SNOWFLAKE.ACCOUNT_USAGE.ACCESS_HISTORY WHERE EVENT_TYPE = 'GRANT' OR EVENT_TYPE = 'REVOKE'; Interpreting the Results: The results from the ACCESS_HISTORY view include the object type, the specific privilege granted or revoked, the grantee (who received or lost the privilege), and the timestamp of the event. This data is invaluable for audits and compliance checks.


NEW QUESTION # 917
What MINIMUM privilege is required on the external stage for any role in the GET REST API to access unstructured data files using a file URL?

Answer: B

Explanation:
The minimum privilege required on an external stage for any role to access unstructured data files using a file URL in the GET REST API is READ. This allows the role to retrieve or download data files from the stage.


NEW QUESTION # 918
When using the ALLOW_CLIยฃNT_MFA_CACHING parameter, how long is a cached Multi-Factor Authentication (MFA) token valid for?

Answer: C


NEW QUESTION # 919
Which typos of charts does Snowsight support? (Select TWO).

Answer: A,E

Explanation:
Snowsight, Snowflake's user interface for executing and analyzing queries, supports various types of visualizations to help users understand their data better. Among the supported types, area charts and bar charts are two common options. Area charts are useful for representing quantities through the use of filled areas on the graph, often useful for showing volume changes over time. Bar charts, on the other hand, are versatile for comparing different groups or categories of data. Both chart types are integral to data analysis, enabling users to visualize trends, patterns, and differences in their data effectively.References: Snowflake Documentation on Snowsight Visualizations


NEW QUESTION # 920
Which Snowflake feature supports the use of natural language queries to analyze unstructured data?

Answer: C

Explanation:
The correct answer is C. Snowflake Cortex .
Snowflake Cortex provides AI and large language model capabilities inside Snowflake. It includes features that support natural language interaction, text analysis, document processing, search, summarization, classification, and other AI-powered workflows.
Why C is correct:
Snowflake Cortex is the Snowflake AI feature family used for natural language and unstructured data use cases. Cortex capabilities can be used to analyze text and other unstructured data using natural language functions and AI services.
Why the other options are incorrect:
A). Snowsight is Snowflake's web interface. It can expose AI-assisted features, but the underlying AI capability is Snowflake Cortex.
B). Snowflake ML supports machine learning workflows but is not the primary feature family for natural language querying of unstructured data.
D). Snowflake Horizon Catalog is focused on governance, discovery, and catalog capabilities, not natural language analysis of unstructured data.
Official Snowflake documentation reference:
Snowflake documentation describes Snowflake Cortex as the set of intelligent, AI-powered features that use large language models and ML to analyze data, including unstructured text data.
Reference: Snowflake Documentation - Snowflake Cortex; Snowflake Documentation - Cortex AI functions; SnowPro Core Study Guide - Snowflake Architecture.


NEW QUESTION # 921
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