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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. A data engineering team is using a Snowflake stream to capture changes made to a source table named 'orders'. They want to only capture 'INSERT and 'UPDATE operations but exclude 'DELETE operations from being captured in the stream. Which of the following configurations will achieve this requirement? Assume the stream has already been created and is named 'orders_stream'.

A) It's impossible to configure a stream to exclude specific DML operations. All changes are always tracked.
B) Use task and stream combination. In the task, create view using 'select from orders where metadata$isDelete = false' and create stream on that view.
C) Create a Snowflake task that periodically truncates the stream's metadata table, removing DELETE records.
D) Create a view on top of the base table that filters out deleted rows, and then create a stream on the view.
E) Alter the stream using the 'HIDE_DELETES parameter: 'ALTER STREAM orders_stream SET HIDE_DELETES = TRUE;'

2. You have created a secure external function that uses a Snowflake secret to retrieve a cryptographic key and mask sensitive data'. However, users are still able to see the sensitive data'. Which of the following actions is MOST likely to resolve the issue?

A) Ensure that the user calling the function has the 'USAGE privilege on the security integration associated with the external function.
B) Grant the 'EXECUTE FUNCTION' privilege on the function to the user.
C) Verify that the user has the 'OWNERSHIP privilege on the table containing the sensitive data.
D) Grant the ' SELECT privilege on the Snowflake secret object to the user.
E) Ensure that the user has the 'USAGE privilege on the database and schema where the secret is stored.

3. You have a Snowflake table called 'ORDERS' with a column named 'ORDER DETAILS that contains JSON data'. You need to create a UDF to extract a specific value from the JSON and return it. The JSON structure is consistent: '{'customer': {'name': 'John Doe', 'email': '[email protected]'}, 'items': [{'item id': 1, 'quantity': 2}, {'item id': 2, 'quantity': You want to extract the customer's email address. Which of the following UDF definitions is the most efficient and correct?

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

4. You need to implement a data masking policy on the 'EMAIL' column of the 'EMPLOYEES' table. The requirement is to redact the entire email address with 'XXXXX' if the user's role is 'PUBLIC'. If the user's role is 'ANALYST', the domain part of the email should be visible, but the username should be redacted. For all other roles, the full email should be visible. Which of the following SQL statements CORRECTLY implements this masking policy?

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

5. A large e-commerce company is experiencing performance issues with its daily sales report queries. These queries aggregate data from a fact table 'SALES FACT (100 billion rows) and several dimension tables, including 'CUSTOMER DIM', 'PRODUCT DIM', and 'DATE DIM'. The queries are run every morning and are essential for business decision-making. The team has identified that the 'SALES FACT table's primary key is 'SALE ID, but the queries frequently filter and join on 'CUSTOMER and 'PRODUCT ID. You want to use query acceleration service for these reports without changing query logic. Which combination of actions will MOST effectively leverage query acceleration service, assuming sufficient credits?

A) Increase the size of the virtual warehouse used for running the reports and enable query acceleration. Set the parameter to a high value.
B) Enable search optimization on the columns 'CUSTOMER ID' and 'PRODUCT ID of the 'SALES FACT table, then enable query acceleration on the virtual warehouse. Set the QUERY_ACCELERATION_MAX_SCALE_FACTOR parameter to a reasonable value based on testing.
C) Create materialized views that pre-aggregate the sales data based on 'CUSTOMER ID', 'PRODUCT ID, and 'DATE ID, then enable query acceleration on the virtual warehouse.
D) Enable Automatic Clustering on the 'SALES FACT table based on 'CUSTOMER ID' and 'PRODUCT ID, then enable query acceleration on the virtual warehouse.
E) Enable clustering on the 'CUSTOMER DIM' and 'PRODUCT DIMS tables.

Solutions: