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| Section | Weight | Objectives |
|---|---|---|
| Data Collaboration & Protection | 10% | - Data Clean Rooms, Collaboration Features - Data Protection, Retention, Time Travel, Fail-safe - Secure Data Sharing, Listings, Marketplace |
| Snowflake Architecture & Core Concepts | 31% | - Cloud Services Layer, Compute Layer, Storage Layer - Virtual Warehouses, Clustering, Caching - Databases, Schemas, Objects, Data Types - Snowsight Interface, Core Platform Features |
| Account Management & Data Governance | 20% | - Access Control: RBAC, DAC, Roles, Privileges - Governance: Resource Monitors, Data Masking, Row/Column Security - Security: Network Policies, MFA, Encryption - Trust Center, Data Lineage, Compliance |
| Performance Optimization, Querying & Transformation | 21% | - Query Processing, Profiling, Optimization - SQL Transformations, Semi-structured/Unstructured Data - Cortex AI, Notebooks, Apache Iceberg Tables - Materialized Views, Streams, Tasks, Pipelines |
| Data Loading, Unloading & Connectivity | 18% | - Stages, File Formats, COPY INTO, Snowpipe - External Integrations, Connectors, SnowSQL - Bulk Load, Streaming, Dynamic Tables - Unloading Data, Export Options |
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NEW QUESTION # 286
When should a user consider disabling auto-suspend for a virtual warehouse? (Select TWO).
Answer: D,E
Explanation:
Disabling auto-suspend for a virtual warehouse is recommended when there is a steady workload, which ensures that compute resources are always available.Additionally, it is advisable to disable auto-suspend when immediate availability of compute resources is critical, eliminating any startup delay
NEW QUESTION # 287
Which Snowflake feature supports the use of natural language queries to analyze unstructured data?
Answer: B
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 # 288
How does Snowflake utilize clustering information to improve query performance?
Answer: A
Explanation:
Snowflake utilizes clustering information to enhance query performance by pruning unnecessary micro- partitions.
Clustering Metadata: Snowflake stores clustering information for each micro-partition, which includes data range and distribution.
Pruning Micro-partitions: When a query is executed, Snowflake uses this clustering metadata to identify and eliminate micro-partitions that do not match the query criteria, thereby reducing the amount of data scanned and improving query performance.
Snowflake Documentation on Clustering
Snowflake Documentation on Micro-partition Pruning
NEW QUESTION # 289
What happens when a network policy includes values that appear in both the allowed and blocked IP address list?
Answer: D
Explanation:
In Snowflake, when setting up a network policy that specifies both allowed and blocked IP address lists, if an IP address appears in both lists, access from that IP address will be denied. The reason is that Snowflake prioritizes security, and the presence of an IP address in the blocked list indicates it should not be allowed regardless of its presence in the allowed list. This ensures that access controls remain stringent and that any potentially unsafe IP addresses are not inadvertently permitted access.
References:
Snowflake Documentation: Network Policies
NEW QUESTION # 290
What AUTHENTICATION_METHODS value should be selected for the Single Sign-On, or SSO, login option to appear when creating a Snowflake authentication policy?
Answer: D
Explanation:
The correct answer is C. SAML .
In Snowflake, Single Sign-On is commonly implemented using federated authentication through a SAML 2.0 identity provider. When creating an authentication policy, including SAML in the allowed AUTHENTICATION_METHODS enables SSO-based login options.
Why C is correct:
SAML represents SAML-based federated authentication. This is the authentication method associated with SSO login in Snowflake.
Example concept:
CREATE AUTHENTICATION POLICY sso_policy
AUTHENTICATION_METHODS = ( ' SAML ' );
Why the other options are incorrect:
A). PASSWORD allows username and password authentication, not SSO.
B). KEYPAIR allows key-pair authentication, commonly used for service accounts and applications.
D). OAUTH allows OAuth-based authentication, but the SSO login option in this context is associated with SAML.
Official Snowflake documentation reference:
Snowflake documentation describes authentication policies as controlling allowed authentication methods, including password, SAML, OAuth, and key-pair authentication. SAML is used for federated SSO authentication.
Reference: Snowflake Documentation - Authentication policies; Snowflake Documentation - Federated authentication and SSO; SnowPro Core Study Guide - Security and Access Control.
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NEW QUESTION # 291
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