DSA-C03 Exam Dumps | A data science team is tasked with deploying a pre-built anomaly detection model in Snowflake to identify

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Question 16

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Question 16/143

A data science team is tasked with deploying a pre-built anomaly detection model in Snowflake to identify fraudulent transactions. They need to use Snowflake ML functions and a Snowflake Native App (that houses the model) to achieve this. The Snowflake Native App is installed and available. The transaction data is stored in a table called 'TRANSACTIONS. Which of the following steps are essential to successfully deploy and use this pre-built model within a User Defined Function (UDF) for real-time scoring, assuming the app provides a function named 'ANOMALY SCORE?

A. Create a UDF that calls the 'ANOMALY _ SCORE function provided by the Snowflake Native App, passing the relevant transaction features as arguments.

B. Grant the USAGE privilege on the Snowflake Native App to the role executing the UDF. This ensures the UDF can access the app's functionality.

C. Ensure the 'TRANSACTIONS' table is shared with the Snowflake Native App's container so the model can directly access the data.

D. Train the pre-built anomaly detection model using Snowflake's ML functions (e.g., 'CREATE MODELS) with the 'TRANSACTIONS' data before creating the UDE

E. Create an external function in API Integration instead of UDF.

Correct Answer: A,B

Options A and B are correct. A UDF is required to call the function from the Native App and to expose the model's functionality for scoring. Granting 'USAGE on the app to the executing role is necessary for the UDF to access the app's functions. Option C is incorrect because UDFs pass data as arguments, avoiding the need to share tables directly. Option D is incorrect since you're using pre-built model, training isn't needed. Option E is incorrect since it specifically asks for UDF with a Snowflake Native App.

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