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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) DEA-C02 Prüfungsfragen mit Lösungen:

1. You are implementing a data share between two Snowflake accounts. The provider account wants to grant the consumer account access to a function that returns anonymized customer data based on a complex algorithm. The provider wants to ensure that the consumer cannot see the underlying implementation details of the anonymization algorithm. Which of the following approaches can achieve this goal? (Select TWO)

A) Share the underlying table and provide the consumer account with the anonymization algorithm separately.
B) Create a view that calls the secure UDF and share that view with the consumer account.
C) Create an external function in the provider account and grant usage to the share. Share the share with the consumer account.
D) Create a standard UDF in the provider account and grant usage on the UDF to the share. Share the share with the consumer account.
E) Create a secure UDF in the provider account and grant usage on the secure UDF to the share. Share the share with the consumer account.

2. You need to load data from a stream of CSV files into a Snowflake table. The CSV files are delivered to an AWS S3 bucket and contain header rows. The files occasionally include records where a text field contains a delimiter character (comma) within the text itself, but these fields are properly enclosed within double quotes. You want to create a file format object that correctly handles the data, including quoted delimiters, and skips the header row. Which of the following file format options are required to achieve this? (Choose two)

A) FIELD DELIMITER = ','
B) ERROR ON COLUMN COUNT MISMATCH = FALSE
C) FIELD OPTIONALLY ENCLOSED BY =
D) SKIP HEADER = 1
E) FILE_FORMAT = (TYPE = CSV)

3. You are tasked with optimizing a continuous data pipeline that loads data from an external stage into a Snowflake table using streams.
The pipeline is experiencing significant latency during peak hours. The stream is defined on a very large table with frequent updates and deletes. Which of the following strategies would be MOST effective in reducing the latency of the data pipeline, considering stream performance and cost implications?

A) Reduce the RETENTION TIME of the stream. This will limit the amount of historical data tracked and improve performance.
B) Increase the size of the virtual warehouse used for loading data. This will provide more compute resources for processing the stream.
C) Create multiple streams on the same base table, each filtering for specific types of changes (e.g., INSERT, UPDATE, DELETE).
D) Implement a more aggressive pruning strategy on the base table to reduce the amount of data that the stream needs to track.
E) Implement a materialized view on top of the stream to pre-aggregate the data.

4. A data engineer observes that a daily data transformation pipeline in Snowflake, which processes data from external stage 's3://my- bucket/raw_dataP , is consistently taking longer to complete. Upon investigation, the engineer finds that the COPY INTO statement is the bottleneck. The COPY INTO statement is as follows:

Which of the following could be the root cause of the performance degradation and how would you address them? Select two options.

A) The 'ON_ERROR = 'CONTINUE" option is causing the COPY INTO statement to perform additional error handling, slowing down the process. Remove the 'ON ERROR clause to improve performance.
B) The external stage contains a large number of small files. Snowflake's COPY INTO statement performs best with fewer, larger files. Consolidate the small files into larger files before loading.
C) The virtual warehouse used for the COPY INTO operation is undersized. Increase the virtual warehouse size to improve performance.
D) Snowflake automatically optimizes COPY INTO operations. No specific action is needed.
E) The PATTERN '. .csv' is inefficient. Refine the PATTERN to be more specific, targeting only the necessary files, potentially using date-based partitioning. If date partitioning is used, leverage partition pruning by including the appropriate date criteria in the COPY INTO statement.

5. You are tasked with implementing a data governance strategy in Snowflake for a large data warehouse. Your objective is to classify sensitive data columns, such as customer phone numbers and email addresses, using tags. You want to define a flexible tagging system that allows different levels of sensitivity (e.g., 'Confidential', 'Restricted') to be applied to various columns. Furthermore, you need to ensure that any data replicated to different regions maintains these classifications. Which of the following statements accurately describe best practices for implementing and maintaining data classification using tags in Snowflake, especially in a multi-region setup? Choose TWO.

A) Always grant the ACCOUNTADMIN role to users who need to apply tags. This simplifies the process and ensures they have all necessary privileges.
B) Create a scheduled task that automatically identifies sensitive data based on regular expressions and applies the appropriate tags. This automates the classification process.
C) When replicating data between regions, the tags are automatically replicated along with the data, provided that replication is configured using database replication or failover groups including the tagging schema.
D) Define tag schemas at the account level and replicate them to all regions. This ensures consistency of tag definitions across the entire organization.
E) Tags and tag values must be uniquely defined across all schemas to avoid conflicts and ensure accurate data classification; Snowflake enforces uniqueness implicitly.

Fragen und Antworten: