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Snowflake COF-C02 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Snowflake Architecture & Cloud Concepts25%- Account structure and hierarchy
  • 1. Object ownership and naming conventions
  • 2. Organization, account, database, schema levels
- Cloud data platform fundamentals
  • 1. Virtual warehouses and resource management
  • 2. Service layers and separation of storage/compute
  • 3. Data storage structure and formats
Topic 2: Account Access & Security20%- Data protection & governance
  • 1. Encryption at rest and in transit
  • 2. Data masking and row-level security
- Authentication & authorization
  • 1. Users, roles, privileges and access control
  • 2. Network policies and security settings
Topic 3: Data Protection & Data Sharing10%- Secure data sharing
  • 1. Direct sharing, data exchanges, reader accounts
  • 2. Sharing security and access control
- Data recovery & retention
  • 1. Data retention policies and backup
  • 2. Time Travel, Fail-safe, cloning capabilities
Topic 4: Data Pipelines & Automation10%- Integration & connectivity
  • 1. Connectors and ETL/ELT patterns
  • 2. External functions and API integration
- Workflow & automation
  • 1. Change data capture and processing
  • 2. Streams, tasks, and pipes
Topic 5: Performance Concepts & Optimization15%- 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
Topic 6: Data Loading & Transformation20%- Data ingestion methods
  • 1. Bulk loading, continuous loading, external stages
  • 2. File formats and data type handling
- Data transformation & querying
  • 1. Working with structured, semi-structured, unstructured data
  • 2. DDL/DML operations and SQL functions

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Snowflake SnowPro Core Certification Exam Sample Questions (Q966-Q971):

NEW QUESTION # 966
Which SQL command can be used to see the CREATE definition of a masking policy?

Answer: A

Explanation:
The SQL command GET_DDL can be used to retrieve the CREATE definition of a masking policy in Snowflake. This command generates the DDL statement required to recreate the masking policy


NEW QUESTION # 967
Which role is responsible for managing the billing and credit data within Snowflake?

Answer: B

Explanation:
The ORGADMIN role in Snowflake is responsible for managing organization-level administrative functions, which include managing billing and credit data. This role has the highest level of administrative privileges and can oversee multiple Snowflake accounts within an organization.
Snowflake Documentation: Account and Organization Roles


NEW QUESTION # 968
Which statement about billing applies to Snowflake credits?

Answer: C

Explanation:
Snowflake credits are the unit of measure for the compute resources used in Snowflake. The number of credits consumed depends on the size of the virtual warehouse and the time it is running. Larger warehouses consume more credits per hour than smaller ones, and credits are billed for the time the warehouse is active, regardless of the actual usage within that time.
References: [COF-C02] SnowPro Core Certification Exam Study Guide


NEW QUESTION # 969
Which table function should be used to view details on a Directed Acyclic Graphic (DAG) run that is presently scheduled or is executing?

Answer: A

Explanation:
TheCURRENT_TASK_GRAPHStable function is designed to provide information on Directed Acyclic Graphs (DAGs) that are currently scheduled or executing within Snowflake. This function offers insights into the structure and status of task chains, enabling users to monitor and troubleshoot task executions. DAGs in Snowflake represent sequences of tasks with dependencies, and understanding their current state is crucial for managing complex workflows.
References: Snowflake Documentation on Task Management


NEW QUESTION # 970
What can a Snowtlake user do to reduce queuing on a multi-cluster virtual warehouse?

Answer: A

Explanation:
* In a multi-cluster virtual warehouse, Snowflake allows you to scale-out by adding more clusters to handle concurrent queries.
* Increasing the MAX_CLUSTER_COUNT ensures more clusters are dynamically provisioned during high-concurrency periods, reducing queuing.
Why Other Options Are Incorrect:
* A. Increase warehouse size: Increases compute power for individual queries but does not address concurrency issues.
* B. Use economy scaling policy: Economy scaling is unrelated to reducing query queuing.
* D. Convert to Snowpark-optimized warehouse: Snowpark warehouses are designed for ML and Python-based workloads, not for query concurrency.
References:
* Multi-Cluster Warehouses


NEW QUESTION # 971
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