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Snowflake SOL-C01 Exam Syllabus Topics:

Topic	Details
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.

Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q86-Q91):

NEW QUESTION # 86
You have a Snowflake table named `CUSTOMER DATA' with columns `CUSTOMER ID', `NAME,
'CITY, and 'TRANSACTION DATE. You need to implement a data masking policy that masks the
'NAME column for all users except those with the 'ACCOUNTADMIN' role. Additionally, you want to implement a row-level security policy that filters the data based on the `CITY column, allowing users with the 'CITY MANAGER role to only see data for their assigned city. How would you implement these policies?

A. Create a view on top of the 'CUSTOMER_DATA' table and implement the masking and row-level security logic within the view definition using CASE statements based on CURRENT ROLE() and CURRENT USER().
B. Create a masking policy for the `NAME' column using a CASE statement that checks the CURRENT ROLE() and applies the mask if the role is not ACCOUNTADMIW. create a security policy for row-level filtering on the 'CITY column, checking the and to determine the appropriate filter condition. Apply the row access policy to the table.
C. Create a masking policy using regular expressions to filter the data. Create a stored procedure to filter the data based on the 'CITY' column for certain users.
D. Create a stored procedure with 'EXECUTE AS OWNER to filter the data based on the 'CITY column for certain users, and masking policy to use `SHA256' on the 'NAME column
E. Create masking policy using the 'TRANSFORM' function to mask the 'NAME' column, and create a row access policy to filter rows based on 'CITY'. Ensure the row access policy uses a mapping table between CITY_MANAGER and CITY.

Answer: B,E

Explanation:
Options A and D correctly implements masking and row-level security. Option A utilizes masking policy for the 'NAME column that considers the `ACCOUNTADMIN' role. And utilizes a row-level security policy (row access policy) that consider 'CITY_MANAGER and 'CITY' for filtering. Option D utilizes `TRANSFORM' to transform and mask the 'NAME' column and implements row access policy which includes Mapping table between CITY and CITY_MANAGER. Option B,C, and E are incorrect as they either create a view, stored procedure and/or regular expressions, which are not the best practices of implementing masking and row-level security in Snowflake.

NEW QUESTION # 87
You have a Snowflake table named 'SALES DATA' that you load data into daily from a CSV file using Snowsight. Recently, the load times have increased significantly. You suspect the Virtual Warehouse size is the bottleneck. You have the following Virtual Warehouse sizes available: X- Small, Small, Medium, Large, X-Large. Choosing the best size depends on cost and speed. You examine the Query History in Snowsight and notice that the COPY INTO commands are consistently using only a small fraction of the X-Large warehouse's compute resources. Which of the following actions would be the MOST cost- effective while also potentially improving (or at least maintaining) the data loading performance?

A. Keep the X-Large warehouse but investigate other potential bottlenecks, such as the file format definition, network latency, or concurrency issues with other queries. Consider using a dedicated warehouse for loading only. Also consider increasing number of parallel threads for loading.
B. Switch to using Snowpipe for continuous data ingestion instead of COPY INTO. This may improve load times but requires additional configuration and cost analysis.
C. Decrease the Virtual Warehouse size to Small or Medium. Since the current warehouse is underutilized, a smaller size will reduce costs without significantly impacting performance.
D. Increase the Virtual Warehouse size to 2X-Large. This will guarantee faster load times.
E. Enable auto-suspend on the X-Large warehouse if it isn't already enabled. This will reduce costs when the warehouse is idle but won't address the loading bottleneck.

Answer: A

Explanation:
Since the X-Large warehouse is underutilized, increasing its size is not cost-effective. Reducing the size might further degrade performance. Enabling auto-suspend only addresses idle costs.
The best approach is to investigate other potential bottlenecks while maintaining the current (potentially oversized) warehouse. Using a dedicated warehouse isolates the loading workload.
Snowpipe is a good alternative, but it's a more complex solution that requires evaluation and isn't the immediately cost effective solution. Option D addresses both performance and cost concerns without making assumptions about Snowpipe's suitability in this specific scenario. Parallel threads increase concurrency, which can speed up loading of multiple files.

NEW QUESTION # 88
You're writing a Snowflake Notebook that needs to dynamically create tables based on a list of table names stored in a Python list called 'table_names'. You want to iterate through this list and execute a CREATE TABLE statement for each table name. However, the names might include spaces and special characters. Which approach or approaches can you use to achieve this goal safely and effectively?

A. Option E
B. Option A
C. Option D
D. Option B
E. Option C

Answer: B,C

Explanation:
Options A and D are correct. Option A uses double quotes to safely enclose the table name within the CREATE TABLE statement. This is the standard way to handle identifiers with spaces or special characters in SQL. Option D provides a Snowpark DataFrame-centric approach that automatically handles identifier quoting when creating the table using `saveAsTable' . Option B modifies the table names by replacing spaces. Option C's reliance on shell escaping ('shlex.quote') is not relevant or necessary when executing SQL within a Snowpark session.
Option E is unsafe as it does not handle the case where table names have spaces or other special characters and will result in SQL errors.

NEW QUESTION # 89
A data provider wants to share a secure view called 'SALES SUMMARY' from the 'RETAIL DATA' database with a consumer. The provider needs to ensure that the consumer can only query the view and cannot see the underlying tables. Which of the following steps are required to accomplish this? l. Create a secure view 'SALES SUMMARY'. II. Create a share. Ill. Grant
'SELECT' privilege on the 'SALES SUMMARY' view to the share. IU Grant 'USAGE privilege on the 'RETAIL DATA' database to the share. V. Grant `USAGE' privilege on the schema containing
`SALES SUMMARY' to the share.

A. l, II, III, and IV only
B. II, III, and V only
C. II and III only
D. l, II, and III only
E. l, II, III, IV, and V

Answer: E

Explanation:
To share a secure view, you need to create the view, create a share, grant SELECT on the view to the share, grant USAGE on the database to the share, and grant USAGE on the schema containing the view to the share. All steps l, II, III, IV and V are required.

NEW QUESTION # 90
A Snowflake user is attempting to query a table named 'CUSTOMERS within the `SALES DB.PUBLIC' schema. However, they are receiving an error indicating insufficient privileges.
Assuming the user has been granted the `USAGE privilege on the database 'SALES , which additional privilege(s) is/are required for the user to successfully query the 'CUSTOMERS table?

A. READ privilege on the 'CUSTOMERS' table.
B. USAGE privilege on the 'SALES DB' database and SELECT privilege on the 'CUSTOMERS table.
C. USAGE privilege on the `PUBLIC' schema.
D. USAGE privilege on the FIJBLIC' schema and SELECT privilege on the 'CUSTOMERS table.
E. SELECT privilege on the 'CUSTOMERS' table.

Answer: D

Explanation:
To query a table, a user needs 'SELECT privilege on the table and 'USAGE privilege on the schema containing the table. Having ` USAGE' on the database is not enough; 'USAGE' is also needed on the schema. READ is not a valid privilege on tables.

NEW QUESTION # 91
......

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