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| Section | Weight | Objectives |
|---|---|---|
| Account Management & Data Governance | 20% | - Trust Center, Data Lineage, Compliance - Access Control: RBAC, DAC, Roles, Privileges - Security: Network Policies, MFA, Encryption - Governance: Resource Monitors, Data Masking, Row/Column Security |
| Data Collaboration & Protection | 10% | - Data Protection, Retention, Time Travel, Fail-safe - Secure Data Sharing, Listings, Marketplace - Data Clean Rooms, Collaboration Features |
| Performance Optimization, Querying & Transformation | 21% | - SQL Transformations, Semi-structured/Unstructured Data - Materialized Views, Streams, Tasks, Pipelines - Query Processing, Profiling, Optimization - Cortex AI, Notebooks, Apache Iceberg Tables |
| Snowflake Architecture & Core Concepts | 31% | - Virtual Warehouses, Clustering, Caching - Databases, Schemas, Objects, Data Types - Cloud Services Layer, Compute Layer, Storage Layer - Snowsight Interface, Core Platform Features |
| Data Loading, Unloading & Connectivity | 18% | - External Integrations, Connectors, SnowSQL - Bulk Load, Streaming, Dynamic Tables - Unloading Data, Export Options - Stages, File Formats, COPY INTO, Snowpipe |
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NEW QUESTION # 158
Which command is used to unload data from a Snowflake table into a file in a stage?
Answer: C
Explanation:
The COPY INTO command is used in Snowflake to unload data from a table into a file in a stage. This command allows for the export of data from Snowflake tables into flat files, which can then be used for further analysis, processing, or storage in external systems.
References:
Snowflake Documentation on Unloading Data
Snowflake SnowPro Core: Copy Into Command to Unload Rows to Files in Named Stage
NEW QUESTION # 159
Which Snowflake layer is associated with virtual warehouses?
Answer: B
Explanation:
The layer of Snowflake's architecture associated with virtual warehouses is the Query Processing layer. Virtual warehouses in Snowflake are dedicated compute clusters that execute SQL queries against the stored data. This layer is responsible for the entire query execution process, including parsing, optimization, and the actual computation. It operates independently of the storage layer, enabling Snowflake to scale compute and storage resources separately for efficiency and cost-effectiveness.
References:
Snowflake Documentation: Snowflake Architecture
NEW QUESTION # 160
How should a user enable Search Optimization Service?
Answer: D
Explanation:
Search Optimization Service is enabled on a table using ALTER TABLE ... ADD SEARCH OPTIMIZATION.
Example:
ALTER TABLE sales ADD SEARCH OPTIMIZATION;
It is not enabled on a warehouse.
Reference: Snowflake Documentation - Enabling Search Optimization Service; ALTER TABLE ... ADD SEARCH OPTIMIZATION.
NEW QUESTION # 161
How can a 5 GB table be downloaded into a single file MOST efficiently?
Answer: B
Explanation:
To download a 5 GB table into a single file most efficiently in Snowflake, you should set the SINGLE parameter to TRUE. This parameter ensures that the COPY INTO command outputs the result into a single file, regardless of the file size. This approach is more efficient than relying on the default MAX_FILE_SIZE setting, which would split the output into multiple files.
Snowflake Documentation: COPY INTO < location >
NEW QUESTION # 162
Which security models are used in Snowflake to manage access control? (Select TWO).
Answer: B,C
Explanation:
Snowflake uses both Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) to manage access control. DAC allows object owners to grant access privileges to other users. RBAC assigns permissions to roles, and roles are then granted to users, making it easier to manage permissions based on user roles within the organization.
References:
Snowflake Documentation: Access Control in Snowflake
NEW QUESTION # 163
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