DEA-C01最新対策問題、DEA-C01ミシュレーション問題
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Snowflake DEA-C01 認定試験の出題範囲:
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あるSnowflakeのDEA-C01テストトレントに関しては、Xhs1991のDEA-C01ガイドトレントが有効であるかどうかを示す最も強力な証拠となるのはパスレートのみであるため、パスレートが最高の広告になるというのが常識です。 有用かどうか。 すべてのお客様のフィードバックからの統計によると、DEA-C01テストトレントの指導の下で試験を準備したお客様の間でのDEA-C01試験問題のSnowPro Advanced: Data Engineer Certification Exam合格率は、 98%から100%に達しました。
Snowflake SnowPro Advanced: Data Engineer Certification Exam 認定 DEA-C01 試験問題 (Q267-Q272):
質問 # 267
An ecommerce company uses AWS Glue ETL to process and analyze orders. The company wants to build an extract, transform, and load (ETL) pipeline that processes placed, shipped, delivered, and canceled orders differently.
The company integrates the order processing system with Amazon EventBridge. The company configures EventBridge Scheduler rules for each order status to invoke different AWS Glue workflows. When the company examines Amazon CloudWatch metrics for the workflow, the company notices that the FailedInvocations metric shows a high value for canceled orders.
The company must determine the cause of the failed invocations.
Which solution will meet this requirement?
- A. Change the retry policy in EventBridge Scheduler to reduce the value for maximum retries.
- B. Configure a dead-letter queue in EventBridge Scheduler to store failed events. Analyze the failed order events.
- C. Use the archive and replay features in EventBridge Scheduler to investigate the issue.
- D. Change the retry policy in EventBridge Scheduler to increase the value for maximum age of event.
正解:B
解説:
Configuring a dead-letter queue for EventBridge Scheduler captures the events that could not be delivered to the target along with the failure context. Reviewing the failed canceled-order events in the DLQ provides the most direct way to identify why the invocations are failing (for example, payload issues, permission errors, or target configuration problems) without changing retry behavior.
質問 # 268
A retail company stores point-of-sale transaction data in an Amazon RDS for MySQL database.
The company maintains historical sales analytics in Amazon Redshift. The company needs to create daily reports that combine the current day's transactions with historical sales patterns for trend analysis. The company requires a solution that provides near real-time insights while minimizing data transfer costs and maintenance overhead.
Which solution will meet these requirements?
- A. Export RDS for MySQL data to an Amazon S3 bucket on a regular schedule. Use the COPY command to load the data into Amazon Redshift staging tables. Join the data with historical data.
- B. Implement Amazon Redshift federated queries to directly access RDS for MySQL data and join it with existing Redshift tables in a single query.
- C. Configure AWS Database Migration Service (AWS DMS) to continuously replicate data from RDS for MySQL to Amazon Redshift. Use Redshift queries to create consolidated reports.
- D. Use AWS Glue to create an extract, transform, and load (ETL) pipeline that runs every hour to copy incremental data from RDS for MySQL to Amazon Redshift. Generate reports.
正解:C
解説:
AWS DMS with ongoing replication (CDC) continuously streams new RDS for MySQL transactions into Amazon Redshift, providing near real-time freshness with minimal maintenance and transferring only changes instead of full batches. Reports can then run in Redshift joining current and historical data without hourly ETL jobs or S3 staging.
質問 # 269
A media company uploads large video files to Amazon S3 for processing. After processing, the company needs to keep the original files for 90 days in case the files require reprocessing. After
90 days, the company can delete the files to reduce storage costs. The company stores the processed videos in a different S3 bucket. Which S3 Lifecycle configuration will meet these requirements for the original files MOST cost-effectively?
- A. Store the files in S3 Standard for 90 days. Enable versioning. Enable Object Lock on the files for
90 days. Then expire the files. - B. Store the files in S3 Intelligent-Tiering for 90 days. Enable versioning. Add S3 Lifecycle management to expire the files.
- C. Store the files in S3 Standard for 90 days. Implement S3 Lifecycle management to expire the files.
- D. Store the files in S3 Standard for 90 days. Transition the files to S3 Glacier Flexible Retrieval for long-term storage. Then expire the files.
正解:C
解説:
Keeping the files in S3 Standard for 90 days and using an S3 Lifecycle expiration rule is the most cost-effective option among the choices because the objects only need to be retained for 90 days and then deleted. Adding Glacier Flexible Retrieval would introduce archival and restore behavior intended for longer-term storage, and AWS notes that S3 Glacier Flexible Retrieval is a long-term archival class with a 90-day minimum storage duration. S3 Intelligent-Tiering also adds monitoring and automation charges, and Object Lock/versioning add unnecessary cost and controls beyond the stated requirement.
Reference:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/glacier-storage-classes.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general- considerations.html
https://docs.aws.amazon.com/AmazonS3/latest/userguide/intelligent-tiering.html
質問 # 270
A company stores server logs in an Amazon S3 bucket. The company needs to keep the logs for
1 year. The logs are not required after 1 year.
A data engineer needs a solution to automatically delete logs that are older than 1 year.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Schedule a cron job on an Amazon EC2 instance to delete the logs after 1 year.
- B. Create an AWS Lambda function to delete the logs after 1 year.
- C. Configure an AWS Step Functions state machine to delete the logs after 1 year.
- D. Define an S3 Lifecycle configuration to delete the logs after 1 year.
正解:D
解説:
An S3 Lifecycle configuration is the best choice for this requirement because it allows the company to define a rule that will automatically delete objects in an S3 bucket after a specified period, in this case, 1 year. This solution provides the least operational overhead because it is a built-in feature of Amazon S3, requires no additional infrastructure or management, and is designed specifically for managing object lifecycles.
質問 # 271
A company maintains multiple extract, transform, and load (ETL) workflows that ingest data from the company's operational databases into an Amazon S3 based data lake. The ETL workflows use AWS Glue and Amazon EMR to process data.
The company wants to improve the existing architecture to provide automated orchestration and to require minimal manual effort.
Which solution will meet these requirements with the LEAST operational overhead?
- A. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) workflows
- B. AWS Lambda functions
- C. AWS Glue workflows
- D. AWS Step Functions tasks
正解:D
解説:
https://docs.aws.amazon.com/step-functions/latest/dg/connect-emr.html
https://docs.aws.amazon.com/step-functions/latest/dg/connect-glue.html
質問 # 272
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