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Snowflake SnowPro Associate: Platform Certification SOL-C01 Exam Questions in PDF

Free Snowflake SOL-C01 Dumps Questions (page: 4)

SOL-C01 PDF — 214 Questions

What is the purpose of the SHOW GRANTS SQL command in Snowflake?

  1. To list all roles in the account
  2. To list all roles granted to a user
  3. To list all users in the account
  4. To list all databases in the account

Answer(s): B

Explanation:

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

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

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



What is the purpose of the COPY INTO SQL command?

  1. To copy data into a virtual warehouse
  2. To copy data from one table into another
  3. To load data from a stage into a table
  4. To duplicate all files on a stage

Answer(s): C

Explanation:

COPY INTO <table> loads data from staged files (internal or external stages) into a Snowflake table.

It supports pattern matching, file formats, error-handling modes, and parallel loading.

It does not move files, does not load to a warehouse (warehouses only supply compute), and table- to-table copying uses INSERT INTO...SELECT.



Snowflake stores semi-structured data in a column of which data type?

  1. TEXT
  2. VARCHAR
  3. STRING
  4. VARIANT

Answer(s): D

Explanation:

TheVARIANTdata type stores semi-structured data (JSON, Parquet, XML, Avro, ORC).

VARIANT allows schema-on-read and supports nested structures.

TEXT/VARCHAR/STRING store plain text only and cannot efficiently query nested structures. STRING is not a Snowflake-native type--VARCHAR is used instead.



What SQL command will return a list of all files in a stage?

  1. PUT
  2. LIST
  3. GET
  4. COPY INTO

Answer(s): B

Explanation:

LIST @stage_name displays all files present in a stage (internal or external).

PUT uploads local files to an internal stage.

GET downloads files from an internal stage.

COPY INTO loads or unloads data but does not list files.



Which Snowflake Cortex LLM function allows a user to specify which model will be used?

  1. COMPLETE
  2. SENTIMENT
  3. SUMMARIZE
  4. TRANSLATE

Answer(s): A

Explanation:

TheCOMPLETEfunction is the only Cortex LLM function where the user can explicitly specify the model name (e.g., Mistral, Snowflake Arctic, Meta Llama models).

SUMMARIZE, SENTIMENT, and TRANSLATE are task-specific functions that use built-in, preselected models anddo not allowmodel selection.



What is the Snowsight object browser used for?

  1. To manage virtual warehouses
  2. To create Snowsight worksheets
  3. To modify security settings for objects
  4. To view and filter database objects

Answer(s): D

Explanation:

The Snowsight object browser is Snowflake's built-in visual interface for exploring and navigating all database objects within an account. It provides a hierarchical view across databases, schemas, and contained objects such as tables, views, stages, pipes, file formats, procedures, and functions. The key purpose of the object browser is to make it easy for users to view and filter database objects without needing SQL commands. Users can search objects by name, apply filters, preview table metadata, and inspect properties such as storage usage or row counts.

The object browser does not manage warehouses; warehouse management is done under the "Warehouses" section. It also does not create worksheets; worksheets are created in the "Worksheets" section. Additionally, the object browser does not modify security settings-- permissions and grants are controlled through SQL (GRANT, REVOKE, SHOW GRANTS) or through the Access Control interfaces.

In summary, the object browser is a discovery and navigation layer, allowing users to efficiently find, inspect, and explore Snowflake objects.



What information can be accessed using the Snowsight Monitoring tab?

  1. Virtual warehouse usage metrics
  2. Query execution history
  3. Database Time Travel snapshots
  4. Database schema changes history

Answer(s): A

Explanation:

The Snowsight Monitoring tab provides a centralized view of virtual warehouse usage metrics, enabling administrators and developers to evaluate how compute resources are being consumed. This includes critical insights such as credit usage, query load, concurrency levels, average queue times, execution durations, and auto-scaling activity (for multi-cluster warehouses). These metrics help determine whether a warehouse is correctly sized, whether concurrency issues are occurring, or whether workloads require scaling up or adding clusters.

Query history is available in a different section--"Activity Query History"--not under Monitoring. Time Travel snapshots are not visualized within Monitoring; Time Travel is controlled via retention parameters and accessed with SQL (AT/BEFORE clauses). Schema change history is also not part of Monitoring and instead is discoverable through ACCOUNT_USAGE or specific metadata views.

The Monitoring tab exists specifically to help evaluate warehouse performance and resource consumption, enabling optimization of compute spending and better workload management.



Where do tables reside in Snowflake?

  1. Stages
  2. Virtual warehouses
  3. Schemas
  4. File formats

Answer(s): C

Explanation:

In Snowflake's logical hierarchy, tables reside within schemas, and schemas reside within databases. This structured arrangement allows clear organization, access management, and separation of workloads or business domains. A schema functions as a container that holds tables, views, functions, sequences, stages, and file formats.
When users reference a table, they typically qualify it using the full three-part name: database.schema.table.

Stages are used to store or reference files, not to hold structured database tables. Virtual warehouses provide compute power for executing queries and performing DML operations but do not store data. File formats define how staged files should be interpreted (CSV, JSON, Parquet, etc.) and are unrelated to where tables physically reside.

Snowflake separates compute and storage, so while compute happens in virtual warehouses, all persistent data--including tables--is managed in Snowflake's centralized storage layer, organized through schemas and databases. This organization ensures consistency, ease of management, and predictable access control.



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