最も有効な DEA-C02 試験参考書

A data engineer needs to optimize the performance of a series of complex transformations performed using Snowflake stored procedures. These procedures involve multiple table joins, aggregations, and data filtering operations. The current execution time is unacceptably long. Which of the following optimization strategies are most likely to provide the greatest performance improvements, considering both code-level optimizations and Snowflake's architecture? Select all that apply.

• A. Ensure the underlying tables are appropriately clustered and consider using materialized views for frequently accessed aggregations or pre-computed results to improve query performance.
• B. Implement data caching within the stored procedures using temporary tables to store intermediate results, reducing the need to repeatedly query the same data.
• C. Refactor the stored procedures to leverage set-based operations (e.g., using SQL statements with joins and aggregations) whenever possible, allowing Snowflake to parallelize the execution across multiple nodes.
• D. Rewrite the stored procedures to use procedural logic (e.g., loops and cursors) more extensively, as this allows for fine-grained control over the execution flow and can improve performance for certain operations.
• E. Use external functions written in languages like Python or Java for computationally intensive tasks that are not efficiently handled by SQL, taking advantage of Snowflake's support for external functions.

You're configuring a Kafka connector to load data into Snowflake. You need to ensure that only records with a specific 'event_type' field equal to 'payment_processed' are loaded into the 'PAYMENT TABLE in Snowflake. Given the following connector configuration snippet, which additional property must be added to the 'transforms' section to achieve this filtering?

• A. Option C
• B. Option B
• C. Option D
• D. Option E
• E. Option A

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

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 C
• B. Option B
• C. Option D
• D. Option E
• E. Option A

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 C
• B. Option B
• C. Option D
• D. Option E
• E. Option A