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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. Consider the following scenario: You have a Snowflake task that refreshes a materialized view. The materialized view is based on a large base table that is constantly being updated. The refresh operation is taking longer than expected, impacting downstream reporting. Which of the following actions will likely NOT improve the performance of the materialized view refresh?

A) Analyzing the Query Profile of the Materialized View Refresh query to identify Bottlenecks and Optimization areas.
B) Ensuring the base table used by the materialized view has an appropriate clustering key.
C) Adding more columns to the materialized view, even if they are not immediately required for reporting.
D) Increasing the warehouse size used by the task executing the refresh.
E) Using the 'AUTO_REFRESH' property of the materialized view when appropriate and feasible.

2. You have an external table named in Snowflake that points to a set of CSV files in an AWS S3 bucket. The CSV files have a header row, and the data is comma-separated. However, some of the files in the S3 bucket are gzipped. You need to define the external table to correctly read both compressed and uncompressed files. Which of the following SQL statements BEST achieves this?

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

3. A Data Engineer needs to implement dynamic data masking for a PII column named in a table 'CUSTOMERS. The masking policy should apply only to users with the role 'ANALYST. If the user is not an 'ANALYST, the full 'EMAIL' address should be displayed. Which of the following is the MOST efficient and secure way to achieve this using Snowflake's masking policies?

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

4. You are designing a data sharing solution where the consumer account needs real-time access to a secure view that aggregates data from several tables in your provider account. The consumer should not be able to see the underlying tables. Which of the following approaches offers the MOST secure and efficient way to implement this data sharing while minimizing the risk of data leakage and performance impact on your provider account?

A) Create a UDF that encapsulates the data aggregation logic and share the UDF's result using a data share, calling the UDF on demand.
B) Create a materialized view on top of the tables, refresh it periodically, and share the materialized view.
C) Create a standard view that joins the tables and share the view using a data share. Implement row-level security policies on the underlying tables.
D) Create a secure view that joins the tables and share only the secure view using a data share.
E) Create a shared database and grant SELECT privilege on the underlying tables directly to the consumer's role.

5. You have a table named 'TRANSACTIONS with the following definition: CREATE TABLE TRANSACTIONS ( TRANSACTION ID NUMBER, TRANSACTION DATE DATE, CUSTOMER_ID NUMBER, AMOUNT PRODUCT_CATEGORY VARCHAR(50) Users frequently query this table using filters on both 'TRANSACTION_DATE and 'PRODUCT CATEGORY. You want to optimize query performance. What is the MOST effective approach?

A) Cluster the table on ' TRANSACTION_DATE and then create a materialized view filtered by PRODUCT_CATEGORY&.
B) Partition the table by 'TRANSACTION DATE
C) Cluster the table using a composite key of '(TRANSACTION_DATE, PRODUCT CATEGORY)'.
D) Create separate indexes on 'TRANSACTION DATE' and 'PRODUCT CATEGORY.
E) Create a materialized view joining 'TRANSACTIONS' with a dimension table containing product category information.

Solutions: