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Snowflake COF-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Data Pipelines & Automation	10%	- Integration & connectivity 1. Connectors and ETL/ELT patterns 2. External functions and API integration - Workflow & automation 1. Streams, tasks, and pipes 2. Change data capture and processing
Performance Concepts & Optimization	15%	- Data optimization features 1. Clustering keys, search optimization, materialized views 2. Caching and result reuse - Warehouse sizing & tuning 1. Query profiling and optimization techniques 2. Scaling, clustering, and concurrency management
Snowflake Architecture & Cloud Concepts	25%	- Account structure and hierarchy 1. Object ownership and naming conventions 2. Organization, account, database, schema levels - Cloud data platform fundamentals 1. Service layers and separation of storage/compute 2. Data storage structure and formats 3. Virtual warehouses and resource management
Data Loading & Transformation	20%	- Data ingestion methods 1. Bulk loading, continuous loading, external stages 2. File formats and data type handling - Data transformation & querying 1. DDL/DML operations and SQL functions 2. Working with structured, semi-structured, unstructured data
Data Protection & Data Sharing	10%	- Secure data sharing 1. Direct sharing, data exchanges, reader accounts 2. Sharing security and access control - Data recovery & retention 1. Time Travel, Fail-safe, cloning capabilities 2. Data retention policies and backup
Account Access & Security	20%	- Authentication & authorization 1. Network policies and security settings 2. Users, roles, privileges and access control - Data protection & governance 1. Data masking and row-level security 2. Encryption at rest and in transit

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Snowflake SnowPro Core Certification Exam Sample Questions (Q1026-Q1031):

NEW QUESTION # 1026
A user unloaded a Snowflake table called mytable to an internal stage called mystage.
Which command can be used to view the list of files that has been uploaded to the staged?

A. list @%raytable;
B. list @mystage;
C. list @ %m.ystage;
D. list @mytable;

Answer: B

Explanation:
The command list @mystage; is used to view the list of files that have been uploaded to an internal stage in Snowflake. The list command displays the metadata for all files in the specified stage, which in this case is mystage. This command is particularly useful for verifying that files have been successfully unloaded from a Snowflake table to the stage and for managing the files within the stage.
References:
Snowflake Documentation on Stages
SnowPro® Core Certification Study Guide

NEW QUESTION # 1027
What is the recommended way to change the existing file format type in my format from CSV to JSON?

A. REPLACE FILE FORMAT my format TYPE-JSON;
B. ALTER FILE FORMAT my format SWAP TYPE WITH JSON;
C. CREATE OR REPLACE FILE FORMAT my format TYPE-JSON;
D. ALTER FILE FORMAT my_format SET TYPE=JSON;

Answer: D

Explanation:
To change the existing file format type from CSV to JSON, the recommended way is to use the ALTER FILE FORMAT command with the SET TYPE=JSON clause. This alters the file format specification to use JSON instead of CSV. References: Based on my internal knowledge as of 2021.

NEW QUESTION # 1028
What is a fundamental characteristic of Snowflake micro-partitions?

A. They can be read directly as files.
B. They serve as an index for Snowflake tables.
C. They are sized based on Time Travel requirements.
D. Once established they cannot be changed.

Answer: C

NEW QUESTION # 1029
Which of the following describes a Snowflake stored procedure?

A. They can only access tables from a single database.
B. They can be created to run with a caller's rights or an owner's rights.
C. They can contain only a single SQL statement.
D. They can be created as secure and hide the underlying metadata from the user.

Answer: D

Explanation:
Reference: https://docs.snowflake.com/en/sql-reference/stored-procedures-overview.html

NEW QUESTION # 1030
Which Snowflake table supports unstructured data?

A. Transient
B. Temporary
C. Permanent
D. Directory

Answer: C

Explanation:
While Snowflake primarily deals with structured and semi-structured data, it also has the capability to handle unstructured data. Unstructured data can be stored in Snowflake using variants of SQL data types in tables, which can be permanent tables. These permanent tables, while traditionally used for structured or semi-structured data (like JSON, Avro, or Parquet), can also accommodate unstructured data in the form of binary formats or strings, offering flexibility in data storage and analysis. However, the management and querying of unstructured data in Snowflake may require additional considerations compared to structured data.
Reference: Snowflake Documentation on Data Types

NEW QUESTION # 1031
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