Free Practice Questions for Snowflake SOL-C01 Exam

The Snowflake Data Cloud allows organizations toseamlessly share, access, and collaborate on dataacross departments and external partners, without copying or moving data. Through secure data sharing, listings, and data clean rooms, Snowflake eliminates data silos and dramatically improves data collaboration.

It does not eliminate the need for governance—Snowflake enhances governance via RBAC, masking policies, and centralized controls. It does not provide access to underlying cloud infrastructure; Snowflake abstracts that. It is not an on-premises solution; Snowflake is fully cloud-native.

Thus, the primary benefit is unifying and securely sharing data across the ecosystem.

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SHOW FILE FORMATS listsfile format objectsthat exist in the currently selected schema (or optionally, a specific database or schema). These objects define how Snowflake interprets staged files during data loading.

It doesnotlist supported built-in formats (CSV, Parquet, etc.).

It doesnotshow example usage information and doesnotlist files—LIST @stage handles that.

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SHOW GRANTS is used to list privileges, including roles assigned to a user.

SHOW GRANTS TO USER reveals all the roles that user inherits.

SHOW ROLES lists roles, SHOW USERS lists users, SHOW DATABASES lists databases—not SHOW GRANTS.

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TheCLASSIFY_TEXTfunction performscategory assignmentfor free-form text. Users provide a list of predefined labels, and the function predicts the most appropriate category using a Snowflake-optimized LLM. It is ideal for automatically tagging customer feedback, routing support tickets, labeling product reviews, classifying email content, and segmenting operational logs.

The function outputs both the predicted label and an associated confidence score, enabling downstream filtering, dashboarding, and automated processing.

Other options belong to different Cortex functions:

TRANSLATEhandles multilingual translation.

COMPLETEgenerates natural language completions.

PARSE_DOCUMENTextracts structured information from documents.

Thus, CLASSIFY_TEXT is task-specific and optimized specifically for classification workloads.

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Snowflake Notebooks support multiple cell types for development and documentation.Pythoncells allow users to perform data transformations, analysis, and Snowpark operations.SQLcells enable executing Snowflake SQL queries directly against tables and views.Markdowncells support formatted documentation within notebooks—useful for narrative explanations and commentary. The option “Markup” is not a supported cell type in Snowflake Notebooks. These three supported types allow users to blend analytics, code execution, and documentation in a unified environment.

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The Cloud Services Layer is the coordination and control layer of Snowflake’s architecture. One of its primary responsibilities is managing security, metadata, authentication, and system-wide services. This layer handles user authentication, role-based access control, metadata services (such as table structures, micro-partition metadata, statistics), query parsing, optimization, execution coordination, and transaction management.

It does not store customer data; storage is handled by the Database Storage Layer using micro-partitions. It does not manage virtual warehouses directly; warehouses are part of the Compute Layer. While Snowsight is a UI that interacts with the Cloud Services Layer, the interface itself is not part of the architectural layer.

The Cloud Services Layer essentially acts as the “brain” of Snowflake, ensuring the platform is consistent, secure, optimized, and able to scale operations intelligently across compute clusters and cloud-native storage environments.

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Snowsight includes a modern, fully capableSQL editordesigned for rich query development, execution, and analysis. The editor offers features such as syntax highlighting, intelligent auto-complete, contextual error display, and result-set visualization. Users can organize work with worksheets, folders, tagging, and versioning-like behavior.

Snowsight is built for both simple and complex SQL workloads. It supports multi-statement execution, script-like workflows, stored procedure development, materialized views, and advanced analytics queries.

Unsupported options include:

Manual data storage configuration: Snowflake abstracts storage management completely.

Pre-built queries only: Snowsight allows fully custom SQL.

Limited to simple queries: It supports enterprise workloads, BI query chains, and operational SQL.

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TheAccountis the top-level Snowflake container encompassing:

• All databases

• All schemas

• All compute resources (warehouses)

• All roles, users, and governance structures

All other objects exist within the Account context.

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Snowsight provides adrag-and-dropinterface for uploading data from a local machine into an internal stage. This is done via: Data → Add Data → Load Files into a Stage. Users can upload multiple files and choose the destination stage. This convenient UI eliminates the need for command-line tools such as SnowSQL. Snowsight supports both local file uploads and cloud storage references, not just cloud sources.

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