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Snowflake COF-C02 Exam Syllabus Topics:

SectionWeightObjectives
Performance Optimization20-25%- Query Performance
  • 1. Query Profiling
  • 2. Result Set Caching
  • 3. Query History
- Data Optimization
  • 1. Materialized Views
  • 2. Search Optimization Service
  • 3. Clustering Keys
- Warehouse Optimization
  • 1. Auto-Suspend/Auto-Resume
  • 2. Warehouse Sizing
  • 3. Multi-cluster Configuration
Cloud Architecture and Data Loading20-25%- Data Loading Techniques
  • 1. Bulk Loading (COPY INTO)
  • 2. Continuous Loading
  • 3. Data Loading Best Practices
- Snowflake Architecture Overview
  • 1. Snowflake Editions
  • 2. Virtual Warehouses
  • 3. Layers (Storage, Compute, Services)
  • 4. Multi-cluster Warehouses
Account Access and Security20-25%- Network Security
  • 1. Network Policies
  • 2. Private Connectivity
- Authorization
  • 1. Object Privileges
  • 2. Grant/Revoke Commands
  • 3. Role Hierarchy
- Authentication
  • 1. User/Role Management
  • 2. Multi-Factor Authentication
  • 3. SSO Integration
Data Handling and Transformation15-20%- Data Transformation
  • 1. Snowflake SQL Functions
  • 2. Time Travel Features
  • 3. Data Pipelines
- Semi-Structured Data
  • 1. Flattening Data
  • 2. VARIANT Data Type
  • 3. JSON/Avro/Parquet Handling
Billing and Account Management10-15%- Account Operations
  • 1. Database/Schema Management
  • 2. Object Naming Conventions
  • 3. Account Parameters
- Credit Usage
  • 1. Resource Monitors
  • 2. Credit Monitoring

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Snowflake SnowPro Core Certification Exam Sample Questions (Q985-Q990):

NEW QUESTION # 985
Which command is used to upload data files from a local directory or folder on a client machine to an internal stage, for a specified table?

Answer: D

Explanation:
To upload data files from a local directory or folder on a client machine to an internal stage in Snowflake, the PUT command is used. The PUT command takes files from the local file system and uploads them to an internal Snowflake stage (or a specified stage) for the purpose of preparing the data to be loaded into Snowflake tables.
Syntax Example:
PUT file://<local_file_path> @<stage_name>;
This command is crucial for data ingestion workflows in Snowflake, especially when preparing to load data using the COPY INTO command.
Reference: Snowflake Documentation on Using the PUT Command: https://docs.snowflake.com/en/sql- reference/sql/put.html


NEW QUESTION # 986
Which REST API can be used with unstructured data?

Answer: A

Explanation:
The REST API used with unstructured data in Snowflake is GET /api/files/, which retrieves (downloads) a data file from an internal or external stage4.


NEW QUESTION # 987
What information does the Query Profile provide?

Answer: B


NEW QUESTION # 988
What is a characteristic of materialized views in Snowflake?

Answer: D

Explanation:
One of the characteristics of materialized views in Snowflake is that they allow multiple tables to be joined in the underlying query. This enables the pre-computation of complex queries involving joins, which can significantly improve the performance of subsequent queries that access the materialized view4. References: [COF-C02] SnowPro Core Certification Exam Study Guide


NEW QUESTION # 989
Which data formats are supported by Snowflake when unloading semi-structured data? (Select TWO).

Answer: B,D

Explanation:
Snowflake supports a variety of file formats for unloading semi-structured data, among which Parquet and Newline Delimited JSON (NDJSON) are two widely used formats.
B . Binary file in Parquet: Parquet is a columnar storage file format optimized for large-scale data processing and analysis. It is especially suited for complex nested data structures.
D . Newline Delimited JSON (NDJSON): This format represents JSON records separated by newline characters, facilitating the storage and processing of multiple, separate JSON objects in a single file.
These formats are chosen for their efficiency and compatibility with data analytics tools and ecosystems, enabling seamless integration and processing of exported data.
Reference:
Snowflake Documentation: Data Unloading


NEW QUESTION # 990
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