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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:

1. You have a table 'SALES DATA' in your production environment. You want to create a development environment using cloning, but only want to include data up to a specific point in time to minimize storage costs and potential exposure of recent, sensitive data'. You know there were significant changes to the 'SALES DATA' table structure on '2024-01-15'. Your goal is to create a clone that only includes the structure as of '2024-01-14'. Which Snowflake command is MOST appropriate for this scenario?

A)

B)

C)

D)

E)

2. You have a base table 'ORDERS' with columns 'ORDER ID, 'CUSTOMER D', 'ORDER DATE, and 'ORDER AMOUNT'. You need to create a view that aggregates the total order amount per customer per month. However, for data governance purposes, you need to ensure that the view only shows data for the last 3 months. What is the MOST efficient and secure way to create this view in Snowflake?

A) Option B
B) Option D
C) Option E
D) Option C
E) Option A

3. You are tasked with creating an external function in Snowflake that calls a REST API. The API requires a bearer token for authentication, and the function needs to handle potential network errors and API rate limiting. Which of the following code snippets demonstrates the BEST practices for defining and securing this external function, including error handling?

A) Option B
B) Option D
C) Option E
D) Option C
E) Option A

4. A data engineer is tasked with creating a Snowpark Python UDF to perform sentiment analysis on customer reviews. The UDF, named 'analyze_sentiment' , takes a string as input and returns a string indicating the sentiment ('Positive', 'Negative', or 'Neutral'). The engineer wants to leverage a pre-trained machine learning model stored in a Snowflake stage called 'models'. Which of the following code snippets correctly registers and uses this UDF?

A) Option B
B) Option D
C) Option E
D) Option C
E) Option A

5. Consider the following Snowflake UDTF definition written in Python:

Which of the following statements are TRUE regarding the deployment and usage of this UDTF?

A) The UDTF can be called directly in SQL using 'SELECT FROM TABLE(process_json(VARlANT COLUMN));' without any prior registration.
B) The UDTF needs to be registered using 'session.udtf.register' or 'create or replace function' with the 'imports' clause referencing the Python file, and the handler' specifying the function name.
C) The return type of the generator 'yield' must strictly adhere to the declared output schema , or errors will occur during execution.
D) The library needs to be explicitly installed and configured within the UDTF's environment using a Snowpark session.
E) The UDTF will automatically be available in all schemas across all databases in the Snowflake account.

Solutions: