COF-C03 Exam Dumps - SnowPro Core Certification 2026 Exam

 Snowflake supports three types of internal stages: Named, User, and Table stages. These stages are used for staging data files to be loaded into Snowflake tables. Schema, Stream, and Database stages are not supported as internal stages inSnowflake. References: Snowflake Documentation1.

To easily transfer data from a production account to a non-production account in Snowflake within the same cloud provider region, creating a data share is the most efficient approach. Data sharing allows for live, read-only access to selected data objects from the production account to the non-production account without the need to duplicate or move the actual data. This method facilitates seamless access to the data for development, testing, or analytics purposes in the non-production environment.

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.

Snowflake ' s unique architecture is described as a multi-cluster, shared data architecture that leverages massively parallel processing (MPP). This architecture separates compute and storage resources, enabling Snowflake to scale them independently. It does not use a single cluster or rely solely on symmetric multiprocessing (SMP); rather, it uses a combination of shared-nothing architecture for compute clusters (virtual warehouses) and a centralized storage layer for data, optimizing for both performance and scalability.

The Search Optimization Service in Snowflake is designed to improve the performance of specific types of queries, particularly those involving extensive sets of WHERE conditions. By maintaining a search index on tables, this service can accelerate lookup and analytical queries, making it a valuable feature for optimizing query performance and reducing execution times for complex searches.

A Pre-signed URL provides access to files stored in Snowflake without requiring authorization at the time of access. This feature allows users to generate a URL with a limited validity period that grants temporary access to a file in a secure manner. It ' s particularly useful for sharing data with external parties or applications without the need for them to authenticate directly with Snowflake.

To unload data from a table into one or more files in a named stage, theCOPY INTO < location > command should be used. This command exports the result of a query, such as selecting all rows from a table, into files stored in the specified stage. TheCOPY INTOcommand is versatile, supporting various file formats and compression options for efficient data unloading.

The default value for auto-suspending a Virtual Warehouse in the Snowflake Web Interface (UI) is 10 minutes. This setting helps manage compute costs by automatically suspending warehouses that are not in use, ensuring that compute resources are efficiently allocated and not wasted on idle warehouses.