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| Section | Weight | Objectives |
|---|---|---|
| Snowflake Architecture & Core Concepts | 31% | - Virtual Warehouses, Clustering, Caching - Databases, Schemas, Objects, Data Types - Snowsight Interface, Core Platform Features - Cloud Services Layer, Compute Layer, Storage Layer |
| Performance Optimization, Querying & Transformation | 21% | - Materialized Views, Streams, Tasks, Pipelines - SQL Transformations, Semi-structured/Unstructured Data - Cortex AI, Notebooks, Apache Iceberg Tables - Query Processing, Profiling, Optimization |
| Account Management & Data Governance | 20% | - Security: Network Policies, MFA, Encryption - Access Control: RBAC, DAC, Roles, Privileges - Trust Center, Data Lineage, Compliance - Governance: Resource Monitors, Data Masking, Row/Column Security |
| Data Collaboration & Protection | 10% | - Secure Data Sharing, Listings, Marketplace - Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features |
| Data Loading, Unloading & Connectivity | 18% | - Stages, File Formats, COPY INTO, Snowpipe - Unloading Data, Export Options - External Integrations, Connectors, SnowSQL - Bulk Load, Streaming, Dynamic Tables |
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NEW QUESTION # 624
Which queries can execute eligible portions in parallel by using the Query Acceleration Service? (Choose two.)
Answer: A,E
Explanation:
The Query Acceleration Service uses serverless compute resources to execute eligible portions of a query plan in parallel with the virtual warehouse. Snowflake identifies two primary eligible patterns:
large scans containing an aggregation or highly selective filter, and large scans that insert or copy many new rows. These patterns correspond directly to options B and E. Query acceleration is most useful for outlier queries with substantial scan work, unpredictable data volumes, or selective processing that can be divided across additional compute resources. Small scans generally do not contain enough parallelizable work to benefit. Complex joins on small tables are also not the primary eligibility pattern. Eligibility is determined at the query-plan level, so enabling the service does not guarantee that every submitted query will use it.
NEW QUESTION # 625
Which Snowsight feature can be used to perform data manipulations and transformations using a programming language?
Answer: A
Explanation:
Python worksheets in Snowsight enable users to perform data manipulations and transformations using the Python programming language directly within the Snowflake environment. This feature integrates the power of Python with Snowflake ' s data warehousing capabilities, allowing for sophisticated data analysis and manipulation.
Introduction to Python Worksheets:
Python worksheets provide an interactive environment to write and execute Python code.
They are designed to facilitate data science and data engineering tasks.
Functionality:
Users can run Python scripts to manipulate data stored in Snowflake.
It allows for leveraging Python ' s extensive libraries for data analysis, machine learning, and more.
Integration with Snowflake:
Python worksheets run on Snowflake ' s compute infrastructure, ensuring scalability and performance.
They can access and manipulate Snowflake tables directly, making them a powerful tool for data transformation.
Snowflake Documentation: Snowsight Python Worksheets
NEW QUESTION # 626
Who can grant object privileges in a regular schema?
Answer: D
Explanation:
In a regular schema within Snowflake, the object owner has the privilege to grant object privileges. The object owner is typically the role that created the object or to whom the ownership of the object has been transferred78.
References = [ COF-C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 627
What are characteristic of Snowsight worksheet? (Select TWO.)
Answer: A,C
Explanation:
Characteristics of Snowsight worksheets in Snowflake include:
A). Worksheets can be grouped under folders, and a folder of folders: This organizational feature allows users to efficiently manage and categorize their worksheets within Snowsight, Snowflake ' s web-based UI, enhancing the user experience by keeping related worksheets together.
E). Users can import worksheets and share them with other users: Snowsight supports the sharing of worksheets among users, fostering collaboration by allowing users to share queries, analyses, and findings.
This feature is crucial for collaborative data exploration and analysis workflows.
References:
Snowflake Documentation: Snowsight (UI for Snowflake)
NEW QUESTION # 628
What does SnowCD help Snowflake users to do?
Answer: B
Explanation:
SnowCD is a connectivity diagnostic tool that helps users troubleshoot network connections to Snowflake.It performs a series of checks to evaluate the network connection and provides suggestions for resolving any issues4.
NEW QUESTION # 629
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