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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions (Q183-Q188):

NEW QUESTION # 183
A data warehouse architect is designing a Snowflake environment for a large retail company. The company has diverse data workloads, including batch data ingestion, real-time analytics, and machine learning model training. The architect needs to choose the appropriate Snowflake edition and configure the virtual warehouse sizes to optimize cost and performance. Considering the diverse workloads, which combination of Snowflake edition and virtual warehouse strategy would be most appropriate?

A. Snowflake Business Critical Edition with a single Medium virtual warehouse that auto-scales based on the workload demand.
B. Snowflake Virtual Private Snowflake (VPS) with a dedicated virtual warehouse for each department within the retail company.
C. Snowflake Enterprise Edition with separate virtual warehouses of varying sizes (Small to X-Large) for each workload (batch ingestion, real-time analytics, and ML model training). Use resource monitors to control costs.
D. Snowflake Standard Edition with a single X-Large virtual warehouse shared across all workloads.
E. Snowflake Standard Edition with separate Small virtual warehouses for batch ingestion and reporting, but use Amazon SageMaker for ML training.

Answer: C

Explanation:
Option B is the most appropriate. Enterprise Edition provides the features necessary for diverse workloads (such as materialized views and advanced security), and using separate virtual warehouses allows for workload isolation and optimized resource allocation. Resource monitors can control costs. Standard Edition (A and E) lacks the features required for advanced workloads.
Business Critical Edition (C) is overkill unless specific security or compliance requirements mandate it. VPS (D) is suitable for highly regulated industries but may be more expensive than necessary for a retail company. Using external services such as SageMaker (E) defeats the purpose of leveraging Snowflake for all workloads.

NEW QUESTION # 184
A user is trying to transfer ownership of a view from role `role_a' to The user executes the following command: ALTER VIEW employee_view TRANSFER OWNERSHIP TO ROLE role_b; The command fails with an error indicating insufficient privileges. Which of the following could be the reason(s) for the failure? (Select all that apply)

A. The user does not have the MANAGE GRANTS privilege on the schema containing the
`employee_view' .
B. The role `role_b' already owns the `employee_view' .
C. The role `role b' does not exist.
D. The user does not have the OWNERSHIP privilege on the `employee_view' .
E. The user does not have the USAGE privilege on the database containing the `employee_view'.

Answer: A,D

Explanation:
To transfer ownership, the user executing the command must have the OWNERSHIP privilege on the object and the MANAGE GRANTS privilege on the schema containing the object. If does not exist, or already owns the object, a different error would be raised. While USAGE on the database might be required for other operations, it is not a direct requirement for transferring ownership if the user has OWNERSHIP and MANAGE GRANTS.

NEW QUESTION # 185
A data engineer needs to transfer ownership of a database named 'SALES DATA' to a role named 'DATA GOVERNANCE The engineer attempts to use the following command: 'GRANT OWNERSHIP ON DATABASE SALES DATA TO ROLE DATA GOVERNANCE. However, this command fails. What is the MOST likely reason for the failure?

A. The correct syntax is 'ALTER DATABASE SALES_DATA OWNER TO ROLE
DATA_GOVERNANCE.
B. The role executing the command does not have the 'OWNERSHIP' privilege on the `SALES DATA database.
C. The `SALES DATA database contains shared data; ownership cannot be transferred in such cases.
D. Ownership can only be transferred to users, not roles.
E. The `DATA GOVERNANCE role does not have the 'OWNERSHIP' privilege on the 'SALES DATA' database.

Answer: B

Explanation:
The `GRANT OWNERSHIP command requires that the role executing the command currently owns the object (database in this case). If the role executing the command doesn't have the
`OWNERSHIP privilege, it cannot transfer ownership to another role. Options A, B, D and E are incorrect because the problem is about the role which is executing the command.

NEW QUESTION # 186
You have a JSON file stored in an internal stage containing customer data with varying schem

A. Use the `LATERAL FLATTEN' function to explode the JSON and then use and to handle different formats.
B. Some customers have address information stored as a nested JSON object, while others have it stored as a simple string. How can you efficiently query all customer records and retrieve the address information, regardless of its format?
C. Use a stored procedure to iterate through each JSON record, determine the address format, and then extract the address.
D. Use to dynamically determine the column type and then apply appropriate conversion functions.
E. Create two different views: one for customers with nested address objects and another for customers with string addresses. Then use 'IJNION ALL' on the views.
F. Load the JSON data into a relational table and use a 'UNION ALL' query to combine records with different schema.

Answer: B

Explanation:
'LATERAL FLATTEN' helps process JSON and then the and functions are used to handle the different formats of the address. This is the most efficient approach. Loading into a relational table is not suited for semi-structured data. Using two views then UNION ALL is a valid strategy, however Flatten will be more efficient. Using a stored procedure would be inefficient.

NEW QUESTION # 187
A data engineer needs to translate product names stored in a 'PRODUCTS' table from English to French using Snowflake Cortex LLM. The 'PRODUCTS' table has a 'PRODUCT ID' and
'PRODUCT NAME EN' column. They want to create a view named 'PRODUCTS FR' that contains the translated product names in a new column called 'PRODUCT NAME FR. Which of the following SQL statements is the MOST efficient and correct way to create the view using the
'TRANSLATE' function, assuming the appropriate LLM endpoint is configured?

A. CREATE VIEW PRODUCTS_FR AS SELECT PRODUCT_ID, 'en', 'fr') AS FROM PRODUCTS;
B. CREATE OR REPLACE VIEW PRODUCTS_FR AS SELECT PRODUCT_ID, PRODUCT NAME EN, source_language 'en', target_language 'fr') AS PRODUCT NAME FR FROM PRODUCTS;
C. CREATE OR REPLACE VIEW PRODUCTS FRAS SELECT PRODUCT ID, 'en', 'fr') AS FROM PRODUCTS;
D. CREATE OR REPLACE VIEW PRODUCTS_FR AS SELECT PRODUCT_ID, NAME EN) AS PRODUCT NAME FR FROM PRODUCTS;
E. CREATE OR REPLACE VIEW PRODUCTS_FR AS SELECT PRODUCT_ID,SNOWFLAKE.CORTEX.TRANSLATE(input source_language 'en', target_language 'fr') AS PRODUCT NAME FR FROM PRODUCTS;

Answer: E

Explanation:
The most efficient and correct way is option E. It correctly uses the
`SNOWFLAKE.CORTEX.TRANSLATE' function with named parameters for clarity and explicitly specifies the source and target languages. Options A and B uses incorrect library and function call and doesn't specify named parameters. option C uses SNOWFLAKE.ML.PREDICT which expects a ML model, not TRANSLATE function

NEW QUESTION # 188
......

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