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Snowflake COF-C03 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Loading and Unloading- External and internal stages
- Bulk data loading using stages and COPY INTO
Topic 2: Data Sharing and Protection- Data replication and failover concepts
- Secure data sharing
Topic 3: Performance and Optimization- Warehouse sizing and scaling
- Query optimization basics
Topic 4: Data Transformation and Processing- SQL operations in Snowflake
- Streams and tasks for data pipelines
Topic 5: Security and Access Control- Authentication and user management
- Role-based access control (RBAC)
Topic 6: Snowflake Architecture and Platform Concepts- Virtual warehouses and compute model
- Storage and data organization
- Snowflake architecture fundamentals

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Snowflake SnowPro® Core Certification 2026 Exam (COF-C03) Sample Questions (Q1150-Q1155):

NEW QUESTION # 1150
What actions will prevent leveraging of the ResultSet cache? (Choose two.)

Answer: A,C

Explanation:
The ResultSet cache is leveraged to quickly return results for repeated queries. Actions that prevent leveraging this cache include stopping the virtual warehouse that the query is running against (B) and executing the RESULTS_SCAN() table function (D).Stopping the warehouse clears the local disk cache, including the ResultSet cache1. The RESULTS_SCAN() function is used to retrieve the result of a previously executed query, which bypasses the need for the ResultSet cache.


NEW QUESTION # 1151
Which table function should be used to view details on a Directed Acyclic Graphic (DAG) run that is presently scheduled or is executing?

Answer: C

Explanation:
The CURRENT_TASK_GRAPHS table 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 # 1152
Why would a Snowflake user load JSON data into a VARIANT column instead of a string column?

Answer: B

Explanation:
A VARIANT column in Snowflake is specifically designed to store semi-structured data, such as JSON, and allows for the creation of a data hierarchy. Unlike string columns, VARIANT columns can natively handle JSON data structures, enabling complex querying and manipulation of hierarchical data using functions designed for semi-structured data.
Snowflake Documentation: VARIANT Data


NEW QUESTION # 1153
When unloading data, which file format preserves the data values for floating-point number columns?

Answer: C

Explanation:
When unloading data, the Parquet file format is known for its efficiency in preserving the data values for floating-point number columns. Parquet is a columnar storage file format that offers high compression ratios and efficient data encoding schemes. It is especially effective for floating-point data, as it maintains high precision and supports efficient querying and analysis.
References:
Snowflake Documentation: Using the Parquet File Format for Unloading Data


NEW QUESTION # 1154
Refer to the exhibit.

What do these Query Profile metrics indicate about the query micro-partition pruning?

Answer: A


NEW QUESTION # 1155
......

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