SOL-C01 Test Book - SOL-C01 Test Papers

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Snowflake SOL-C01 Exam Overview:

Certification Vendor:	Snowflake
Exam Name:	Snowflake Certified SnowPro Associate - Platform Certification
Exam Number:	SOL-C01
Passing Score:	750 out of 1000
Real Exam Qty:	65
Exam Duration:	85 minutes
Available Languages:	English, Japanese
Exam Price:	$100 USD
Exam Format:	Multiple-select, Interactive items, Multiple-choice
Certificate Validity Period:	2 years
Related Certifications:	SnowPro Core Certification SnowPro Advanced Certifications SnowPro Specialty Certifications
Recommended Training:	Snowflake Free Hands-On Labs Snowflake Documentation
Exam Registration:	Snowflake Certification Portal Pearson VUE Registration
Sample Questions:	Snowflake SOL-C01 Sample Questions
Exam Way:	Online unproctored exam via Pearson VUE; available 24/7 upon purchase
Pre Condition:	No mandatory prerequisites; recommended 3+ months hands-on experience with Snowflake
Official Syllabus URL:	https://learn.snowflake.com/en/certifications/snowpro-platform/

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Latest Snowflake SOL-C01 Questions in Three Different Formats

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Snowflake SOL-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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.
Topic 3	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 4	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.

Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q156-Q161):

NEW QUESTION # 156
You are using the Snowflake web interface to execute SQL queries. You want to save a specific query for future use. Which of the following methods allows you to effectively save and organize your SQL queries within Snowflake's webUIand how it is best used?

A. Use the 'Create View' command in SQL to save the query's result set as a view.
B. Save the query directly within a Worksheet. Worksheets in Snowflake are designed to store and organize SQL queries; you can create multiple worksheets and name them descriptively to manage your scripts effectively. This allows saving, organizing, and re-running them directly from the Snowflake UI.
C. Store the query as a Stored Procedure. Useful when the query is part of a larger process and needs to be executed programmatically with parameters.
D. Export the query as a JSON file using the 'Export' feature. Best to use when needed to store the queries and not running.
E. Download the query as a text file using the 'Download' option from the worksheet menu. Re- uploading will be required, when required.

Answer: B

Explanation:
Worksheets in Snowflake are specifically designed for saving and organizing SQL queries directly within the Snowflake web interface. You can create multiple worksheets, name them appropriately, and save your SQL scripts within them. This allows easy access and re- execution of your queries. While the other options are valid for other purposes (downloading, creating views, creating stored procedures), they are not the primary and most efficient way to save queries for reuse within the Snowflake I-Jl.

NEW QUESTION # 157
A data engineer needs to grant a business analyst role ('BI ANALYST) the ability to query data in a specific schema ('SALES DATA) within a database ('REPORTING DB'). The business analyst should also be able to create temporary tables for their analysis but should not be able to modify the underlying tables. Which of the following set of commands is the MOST SECURE and LEAST PRIVILEGED way to achieve this?

A. GRANT ALL ON DATABASE REPORTING DB TO ROLE BI ANALYST; GRANT SELECT ON ALL TABLES IN SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST; GRANT CREATE TEMPORARY TABLE ON DATABASE REPORTING DB TO ROLE BI ANALYST,
B. GRANT USAGE ON DATABASE REPORTING DB TO ROLE BI ANALYST; GRANT SELECT ON ALL TABLES IN SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST; GRANT CREATE TEMPORARY TABLE ON DATABASE REPORTING DB TO ROLE BI ANALYST;
C. GRANT USAGE ON DATABASE REPORTING DB TO ROLE BI ANALYST; GRANT SELECT ON FUTURE TABLES IN SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST, GRANT CREATE TEMPORARY TABLE ON DATABASE REPORTING DB TO ROLE BI ANALYST;
D. GRANT USAGE ON DATABASE REPORTING DB TO ROLE BI ANALYST; GRANT SELECT ON SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST; GRANT CREATE TEMPORARY TABLE ON DATABASE REPORTING DB TO ROLE BI ANALYST,
E. GRANT USAGE ON DATABASE REPORTING DB TO ROLE BI ANALYST; GRANT USAGE ON SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST; GRANT SELECT ON ALL TABLES IN SCHEMA REPORTING DB.SALES DATA TO ROLE BI ANALYST; GRANT CREATE TEMPORARY TABLE ON DATABASE REPORTING DB TO ROLE BI ANALYST;

Answer: E

Explanation:
Option D provides the most secure and least privileged access. USAGE on the database and schema allows access without full control. SELECT on tables allows querying. CREATE TEMPORARY TABLE allows the creation of temporary tables within the database. Granting SELECT ON FUTURE TABLES would grant access to tables that don't exist yet, unnecessary for this scenario. Option A does not grant USAGE on the schema. Option C is overly permissive.

NEW QUESTION # 158
What is a share?

A. A Snowflake object that can only be accessed by using a reader account.
B. A Snowflake object that holds all the information required to replicate data into a secondary account.
C. A Snowflake object that holds all of the information required to share a database.
D. A Snowflake object that holds the metrics about table data that has been shared outside of Snowflake.

Answer: C

Explanation:
Asharein Snowflake is a securable object that contains all the metadata required to provide access to selected data-typically tables, views, and secure views-to other Snowflake accounts. The share object defines which objects are included and what privileges (e.g., SELECT, USAGE) consumers receive.
A share does not store data itself; it provides a reference to the provider's underlying micro-partitioned storage, enabling real-time, zero-copy access.
Reader accounts (option A) can consume shares but do not define them.
Replication objects (option C) relate to database replication, not data sharing.
Option D is incorrect because Snowflake does not generate share-specific metrics objects.
Thus, the purpose of a share is to encapsulate all metadata required for secure, controlled data sharing between Snowflake accounts.

NEW QUESTION # 159
A company is experiencing inconsistent query performance in their Snowflake environment.
Some queries execute quickly, while others, seemingly similar, take significantly longer. They suspect that the virtual warehouse sizing is not optimal. Which of the following strategies would be the MOST comprehensive approach to diagnosing and resolving this issue, assuming you have access to Snowflake's monitoring tools and SQL?

A. Enable the Query Acceleration Service. This will automatically improve query performance.
B. Cluster the tables that are frequently joined together, especially those involved in slow queries.Also, monitor average query execution time based on warehouse size over time to find an optimal size.
C. Use the Snowflake web interface to review query history and identify queries with long execution times. Analyze the query profiles of these slow queries to pinpoint performance bottlenecks such as full table scans or inefficient joins.
D. Continuously monitor the warehouse's CPU utilization and memory usage during peak hours. If utilization is consistently high, immediately upgrade the warehouse to the next larger size.
E. Implement Resource Monitors to limit the credit usage of specific users or groups. This will prevent a single user from monopolizing warehouse resources and impacting other users' query performance.

Answer: B,C

Explanation:
While monitoring CPU utilization (A) is helpful, it's not the most comprehensive. Query Acceleration service (B) may help to accelerate, but will not diagnose the underlying issue.
Resource Monitors (D) address credit usage but don't directly improve query performance. The most comprehensive approach is to analyze slow queries using query profiles (C) to understand bottlenecks. Then you must improve data locality by Clustering Tables(E). Also, the sizing of a warehouse needs monitoring over time to ensure its performing at it's best. The best choice is to first identify the root cause of performance issues (C, E) before taking action.

NEW QUESTION # 160
You are using a named file format called to load data from CSV files into a Snowflake table named `PRODUCTS'. However, you are encountering errors during the data loading process because some CSV files contain rows with more columns than defined in the `PRODUCTS table.
You want Snowflake to ignore these extra columns and load the data without errors. Which of the following approaches can achieve this goal?

A. Modify the file format object to include the MISMATCH = TRUE' parameter.
B. In the 'COPY INTO' statement, specify the 'TRUNCATECOLUMNS = TRUE parameter. This option truncates any extra columns.
C. This cannot be achieved directly. Columns number and data types should match exactly
D. Modify the file format object to include the ` = FALSE parameter.
E. In the 'COPY INTO statement, specify the 'MATCH BY COLUMN_NAME' parameter to explicitly map CSV columns to table columns.

Answer: D

Explanation:
Option B is correct. Setting = FALSE in the file format tells Snowflake to ignore extra columns in the CSV files. The default value for this parameter is TRUE, causing an error when the column count does not match. TRUNCATECOLUMNS parameter has nothing to do with the number of columns. It is used to truncate the strings when loading and can cause an error. The MATCH BY_COLIJMN_NAME is used when you have column names defined and they can have a diffent order. The statement in Option E is incorrect

NEW QUESTION # 161
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