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Accurate SOL-C01 Answers, Reliable SOL-C01 Exam Online

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Accurate SOL-C01 Answers, Reliable SOL-C01 Exam Online

Posted at 14 hour before      View：23 | Replies：0        Print      Only Author   [Copy Link] 1#
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Snowflake SOL-C01 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Identity and Data Access Management: This domain focuses on Role-Based Access Control (RBAC) including role hierarchies and privileges, along with basic database administration tasks like creating objects, transferring ownership, and executing fundamental SQL commands.
Topic 2
  • Interacting with Snowflake and the Architecture: This domain covers Snowflake's elastic architecture, key user interfaces like Snowsight and Notebooks, and the object hierarchy including databases, schemas, tables, and views with practical navigation and code execution skills.
Topic 3
  • Data Protection and Data Sharing: This domain addresses continuous data protection through Time Travel and cloning, plus data collaboration capabilities via Snowflake Marketplace and private Data Exchange sharing.
Topic 4
  • Data Loading and Virtual Warehouses: This domain covers loading structured, semi-structured, and unstructured data using stages and various methods, virtual warehouse configurations and scaling strategies, and Snowflake Cortex LLM functions for AI-powered operations.

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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q80-Q85):NEW QUESTION # 80
A data warehouse has a role hierarchy where 'ANALYST' reports to 'DATA SCIENTIST' and
'DATA SCIENTIST' reports to 'DATA ENGINEER'. The 'ANALYST' role needs to create and use user-defined functions (UDFs) within a specific schema 'ANALYTICS. However, you want to restrict the ability of `ANALYST' to grant UDF usage privileges to other roles. You also want to ensure that if a new user is granted the 'ANALYST' role in the future, they automatically have the necessary privileges to create UDFs.
Which sequence of actions would best fulfill these requirements?
  • A. GRANT CREATE FUNCTION ON FUTURE FUNCTIONS IN SCHEMAANALYTICS TO ROLE ANALYST; GRANT USAGE ON SCHEMAANALYTICS TO ROLE ANALYST;
  • B. GRANT CREATE FUNCTION ON FUTURE FUNCTIONS IN SCHEMAANALYTICS TO ROLE ANALYST; GRANT USAGE ON SCHEMAANALYTICS TO ROLE ANALYST;
  • C. GRANT CREATE FUNCTION ON SCHEMAANALYTICS TO ROLE ANALYST, GRANT USAGE ON SCHEMAANALYTICS TO ROLE ANALYST; GRANT USAGE ON SCHEMAANALYTICS TO ROLE DATA SCIENTIST;
  • D. GRANT CREATE FUNCTION ON SCHEMAANALYTICS TO ROLE ANALYST, GRANT USAGE ON SCHEMAANALYTICS TO ROLE ANALYST;
  • E. GRANT CREATE FUNCTION ON FUTURE FUNCTIONS IN SCHEMAANALYTICS TO ROLE ANALYST; GRANT USAGE ON SCHEMAANALYTICS TO ROLE ANALYST; GRANT USAGE ON SCHEMAANALYTICS TO ROLE DATA SCIENTIST;
Answer: B
Explanation:
Option E is the most appropriate. It grants 'CREATE FUNCTION' on 'FUTURE FUNCTIONS' in the 'ANALYTICS' schema, meaning any new UDFs created will automatically grant the privilege.
This ensures future users with the 'ANALYST role can create UDFs. Granting USAGE' on the schema is necessary for the 'ANALYST' role to be able to access and interact with the schema, including creating UDFs. The use of 'FUTURE FUNCTIONS' grants is crucial for fulfilling the requirement of automatically granting privileges to new users. The USAGE on SCHEMA is necessary for analyst to use the database and to interact with the schema, so they can create UDFs. Option A is incorrect as it gives GRANT CREATE FUNCTION on schema, but not FUTURE functions inside that schema. Similarly Options B and D are also incorrect for this reason. Options B and D also unnecessarily grant USAGE on the schema to the DATA SCIENTIST. The data scientist already inherits privileges as part of hierarchy.

NEW QUESTION # 81
A junior data analyst accidentally deleted a critical table using Snowsight. After restoring the table from Time Travel, they want to prevent this from happening again. What is the MOST appropriate preventative measure they should take using Snowsight, considering they still need access to query other tables?
  • A. Revoke the DELETE privilege ONLY on the specific critical table.
  • B. Configure multi-factor authentication for the analyst's Snowflake account.
  • C. Grant the analyst the MONITOR privilege on the database.
  • D. Revoke the ACCOUNTADMIN role from the analyst.
  • E. Revoke the DELETE privilege on all tables for the analyst.
Answer: A
Explanation:
Revoking the DELETE privilege ONLY on the specific critical table prevents accidental deletion of that table while still allowing the analyst to delete data from other tables where they have the appropriate permissions. Revoking DELETE on all tables or removing ACCOUNTADMIN is too restrictive, as the analyst needs to query and potentially modify other tables. Multi-factor authentication enhances security but doesn't directly prevent accidental deletions. MONITOR privilege is for observing, not preventing actions.

NEW QUESTION # 82
A security architect is designing a role hierarchy in Snowflake for a data analytics team. They need to grant specific privileges to different user groups. 'DATA ENGINEER' role should have the ability to create and manage databases. 'DATA ANALYST' role should be able to query data from those databases. 'REPORT USER' role needs read-only access to specific views. The architect wants to ensure minimum privilege and enforce role separation. Which of the following sequences of SQL commands would correctly establish this role hierarchy and grant necessary privileges?

  • A. Option B
  • B. Option E
  • C. Option C
  • D. Option D
  • E. Option A
Answer: B
Explanation:
Option E is the most complete answer. It creates the roles, grants necessary database creation privileges to DATA_ENGINEER, allows DATA ANALYST to use and query the database, and REPORT USER to use the database and select from the specified view. The role grants establish the hierarchy. Options A and B have incorrect grant statements for select on all tables in the database and lack the creation of Roles at the begining. Option D does not grant the roles to each other, leaving the hierarchy incomplete, and incorrectly attempts to grant select on future tables directly to a view.

NEW QUESTION # 83
A Snowflake Notebook is being used to train a machine learning model. The notebook contains multiple cells: one to load data, one to perform feature engineering, and one to train the model using Snowpark ML. After running the feature engineering cell, the notebook session unexpectedly terminates. No error messages are displayed, and the notebook kernel restarts automatically. The data being processed is approximately 50 GB. What are the TWO most likely causes of this issue and their corresponding remedies?
  • A. The feature engineering process resulted in an excessively large intermediate dataset that exceeded available memory. Optimize the feature engineering code to reduce memory consumption or partition the data.
  • B. The Snowpark ML library encountered an incompatibility issue with the current Snowflake version.
    Upgrade or downgrade the Snowpark ML version to match the compatible Snowflake version.
  • C. The notebook is configured to automatically save checkpoints. This feature is causing overhead and instability when dealing with large datasets. Disable auto- saving in the notebook settings.
  • D. The Snowflake warehouse being used for the notebook session is undersized, leading to memory exhaustion and session termination. Scale up the warehouse to a larger size (e.g., from X-Small to Small or Medium).
  • E. The notebook session timed out due to inactivity. Increase the SESSION_IDLE_TIMEOUT setting for the Snowflake user or account.
Answer: A,D
Explanation:
Warehouse size (B) is crucial for processing large datasets. An undersized warehouse will quickly run out of memory, leading to session termination. Memory exhaustion (D) from feature engineering is also a common cause. Optimizing the code and partitioning data can help. While session timeouts (A) are possible, the immediate termination after running the cell suggests a memory issue. Snowpark ML incompatibility (C) is less likely if the basic loading and processing work. Auto-saving (E) contributes to overhead but is unlikely to be the primary cause of immediate termination.

NEW QUESTION # 84
What is the Snowsight Query Profile used for?
  • A. To execute SQL queries
  • B. To manage data loading processes
  • C. To create new database objects
  • D. To visualize and analyze query performance
Answer: D
Explanation:
The Snowsight Query Profile is a powerful diagnostic tool that provides a visual breakdown of how Snowflake executed a query. Its primary purpose is to help users visualize and analyze query performance. It displays execution steps, including scan operations, join strategies, pruning results, aggregation methods, and data movement between processing nodes.
The profile shows metrics such as execution time per step, partition pruning effectiveness, bytes scanned, and operator relationships. This allows developers, analysts, and DBAs to identify bottlenecks-such as unnecessary full-table scans, non-selective filters, or inefficient joins-and tune SQL accordingly.
Query Profile does not execute queries; execution happens in worksheets or programmatic interfaces. It does not create objects or manage data loading; those tasks involve separate SQL commands and UI interfaces.
Overall, Query Profile is essential for performance tuning, helping teams reduce compute costs, optimize warehouse sizing, and improve query efficiency.

NEW QUESTION # 85
......
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