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

1. You have a table 'CUSTOMERS' with columns 'CUSTOMER ID', 'FIRST NAME', 'LAST NAME, and 'EMAIL'. You need to transform this data into a semi-structured JSON format and store it in a VARIANT column named 'CUSTOMER DATA' in a table called 'CUSTOMER JSON'. The desired JSON structure should include a root element 'customer' containing 'id', 'name', and 'contact' fields. Which of the following SQL statements, used in conjunction with a CREATE TABLE and INSERT INTO statement for CUSTOMER JSON, correctly transforms the data?

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

2. A data engineer is using the Snowflake Spark connector to read a large table from Snowflake into a Spark DataFrame. The table contains a 'TIMESTAMP NTT column. After loading the data, the engineer observes that the values in the 'TIMESTAMP NTZ' column are not preserved accurately when retrieved from the DataFrame. What are the potential issues and what configurations can be adjusted in Snowflake to improve the result?

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

3. You are tasked with implementing data masking on a 'CUSTOMER' table. The requirement is to mask the 'EMAIL' column for all users except those with the 'DATA ADMIN' role. You have the following code snippet. What is wrong with it?

A) The masking policy is applied to the wrong column. It should be applied to the ID column, not the EMAIL column.
B) The masking policy syntax is incorrect. It should use 'CASE WHEN IS_ROLE_IN_SESSION('DATA_ADMIN') THEN EMAIL ELSE '[email protected]' END'.
C) Without masking poliy code, it's impossible to determine if there is anything wrong.
D) The WITH clause is unneccessary.
E) There is no code provided, so there is nothing wrong with it.

4. You are implementing Snowpipe using the REST API for a custom data ingestion process. Your application uploads data files to an internal stage named '@MY STAGE and then calls the Snowpipe REST API to trigger the data load. However, you are encountering 'insufficient privileges' errors when calling the API, even though the role used to authenticate the API requests has the 'USAGE' privilege on the stage and the 'OPERATE' privilege on the pipe. The Pipe name is 'MY PIPE'. Which of the following is the MOST LIKELY cause of this error, and what can you do to resolve it?

A) The role used to authenticate the API requests requires the 'INSERT privilege on the target table in addition to 'USAGE on the stage and 'OPERATE on the pipe. Grant the 'INSERT privilege to the role.
B) The role used to authenticate the API requests does not have the 'OWNERSHIP' privilege on the Snowpipe.
C) The role used to authenticate the API requests does not have the 'SELECT' privilege on the underlying table that the Snowpipe is loading data into.
D) The Snowpipe's 'EXECUTE TASK' privilege has not been granted to the role used for the REST API calls. Grant the 'EXECUTE TASK' privilege to the role.
E) The role doesn't have the 'USAGE' privilege on the database and schema containing the stage and pipe. Grant 'USAGE' on the database and schema.

5. You're designing a data pipeline in Snowflake that utilizes an external function to perform sentiment analysis on customer reviews using a third-party NLP service. This service charges per request. You need to minimize costs while ensuring timely processing of the reviews.
Which of the following strategies would be most effective in optimizing the cost and performance of your external function?

A) Bypass the external function completely and rely solely on Snowflake's built-in NLP functions for sentiment analysis.
B) Set 'MAX BATCH_ROWS' to a very high value (e.g., 10000) to maximize the number of rows processed per API call, even if it increases latency for individual reviews.
C) Pre-process the customer reviews in Snowflake to filter out irrelevant reviews (e.g., very short reviews or reviews with stop words) before sending them to the external function.
D) Implement rate limiting and error handling in the external service (e.g., AWS Lambda or Azure Function) to gracefully handle API usage limits and prevent excessive charges due to errors.
E) Implement a caching mechanism (e.g., using a Snowflake table or an external cache) to store the sentiment analysis results for frequently occurring reviews or similar text patterns, avoiding redundant API calls.

Solutions: