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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Loading, Unloading & Connectivity | 18% | - Bulk Load, Streaming, Dynamic Tables - Unloading Data, Export Options - External Integrations, Connectors, SnowSQL - Stages, File Formats, COPY INTO, Snowpipe |
| Topic 2: Performance Optimization, Querying & Transformation | 21% | - Cortex AI, Notebooks, Apache Iceberg Tables - Materialized Views, Streams, Tasks, Pipelines - Query Processing, Profiling, Optimization - SQL Transformations, Semi-structured/Unstructured Data |
| Topic 3: Snowflake Architecture & Core Concepts | 31% | - Cloud Services Layer, Compute Layer, Storage Layer - Snowsight Interface, Core Platform Features - Virtual Warehouses, Clustering, Caching - Databases, Schemas, Objects, Data Types |
| Topic 4: Data Collaboration & Protection | 10% | - Data Protection, Retention, Time Travel, Fail-safe - Secure Data Sharing, Listings, Marketplace - Data Clean Rooms, Collaboration Features |
| Topic 5: 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 |
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NEW QUESTION # 1122
Which key access control concept does Snowflake descibe as a defined level of access to an object?
Answer: D
Explanation:
In Snowflake, the term " privilege " refers to a defined level of access to an object. Privileges are specific actions that roles can perform on securable objects in Snowflake, such as tables, views, warehouses, databases, and schemas. These privileges are granted to roles and can be further granted to users through their roles, forming the basis of Snowflake's access control framework.
References: Snowflake Documentation on Access Control Privileges
NEW QUESTION # 1123
Which data type can be used for floating-point numbers without losing precision?
Answer: B
Explanation:
In Snowflake, the DOUBLE data type is used for floating-point numbers and can represent a wide range of values without losing precision. This data type is ideal for storing numerical values that require decimal precision.
Define the Column: When creating a table, specify the column with the DOUBLE data type to store floating-point numbers.
CREATE TABLE example_table (
id INTEGER,
value DOUBLE
);
Insert Data: Insert floating-point numbers into the DOUBLE column.
INSERT INTO example_table (id, value) VALUES (1, 123.456);
References:
Snowflake Documentation: Data Types
Snowflake Documentation: Numeric Data Types
NEW QUESTION # 1124
How should the SPLIT_TO_TABLE( < string > , < delimiter > ) function be called?
Answer: C
Explanation:
SPLIT_TO_TABLE() is a table function that splits a string into multiple rows based on a delimiter. To use it correctly in SQL, you must wrap it in a TABLE() clause.
Correct Syntax:
SELECT * FROM TABLE(SPLIT_TO_TABLE( ' a.b.c ' , ' . ' ));
Reference:
Snowflake Docs: SPLIT_TO_TABLE
NEW QUESTION # 1125
Which formats does Snowflake store unstructured data in? (Choose two.)
Answer: C,D
Explanation:
Snowflake supports storing unstructured data and provides native support for semi-structured file formats such as JSON, Avro, Parquet, ORC, and XML1. GeoJSON, being a type of JSON, and XML are among the formats that can be stored in Snowflake. References: [ COF-C03 ] SnowPro Core Certification Exam Study Guide
NEW QUESTION # 1126
A virtual warehouse is created using the following command:
Create warehouse my_WH with
warehouse_size = MEDIUM
min_cluster_count = 1
max_cluster_count = 1
auto_suspend = 60
auto_resume = true;
The image below is a graphical representation of the warehouse utilization across two days.
What action should be taken to address this situation?
Answer: C
Explanation:
The graphical representation of warehouse utilization indicates periods of significant queuing, suggesting that the current single cluster cannot efficiently handle all incoming queries.Configuring the warehouse to a multi-cluster warehouse will distribute the load among multiple clusters, reducing queuing times and improving overall performance1.
References = Snowflake Documentation on Multi-cluster Warehouses1
NEW QUESTION # 1127
......
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