弊社の権威的な問題集

弊社の目的はAmazonのData-Engineer-Associate認定試験に参加するつもりの受験者たちは我々の問題集を利用して試験に合格できるということです。だから、我々のIT技術専門家たちは日も夜も努力して、過去のData-Engineer-Associate試験を整理と分析して、現在の高質量のAWS Certified Data Engineer - Associate (DEA-C01)問題集を開発します。この問題集は的中率が高くて、通過率が高いです。

CertShikenのData-Engineer-Associate試験を利用すると、試験の準備をする時に時間をたくさん節約することができます。弊社の問題集を通じて、受験者としてのあなたはData-Engineer-Associate試験に関する専門知識をよく習得し、自分の能力を高めることができます。数年以来の努力を通して、今まで、弊社は自分のData-Engineer-Associate試験問題集に自信を持って、弊社の商品で試験に一発合格できるということを信じています。

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あなたに最大の利便性をもたらすために、我々はあなたに行き届いたサービスを提供します。あなたが商品の質量を確認できるために、CertShikenというサイトで無料なData-Engineer-Associate試験問題集のサンプルを提供して、あなたはこのサンプルを無料でダウンロードできて、自分にふさわしいかどうか確認できます。

それだけでなく、我々は最高のアフターサービスを提供します。あなたはご購入になってから、我々はData-Engineer-Associate問題集（AWS Certified Data Engineer - Associate (DEA-C01)）の一年間の更新サービスを無料で提供します。この一年で、もし問題集が更新されたら、弊社はあなたにメールをお送りいたします。

そのほか、弊社はお客様に承諾します。もしあなたはData-Engineer-Associate試験に失敗したら、我々は問題集の費用を全額であなたに戻り返します。Data-Engineer-Associate問題集をご購入になった半年以内、我々は失敗したら全額で返金することを承諾いたします。我々はこの承諾をするのは我々は自分のAmazonのData-Engineer-Associate問題集に自信を持っているからです。

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Credit cardは世界での一番安全的な支払いプラットフォームだと知られています。手続きの費用が少なくて、保障があります。弊社は皆様の利益を守るために、Credit Cardを我々の主な支払い方式として、最も安全的な支払いを実現します。AmazonのData-Engineer-Associate問題集もCredit Cardで支払われることができます。

Data-Engineer-Associate試験問題集をすぐにダウンロード：成功に支払ってから、我々のシステムは自動的にメールであなたの購入した商品をあなたのメールアドレスにお送りいたします。（12時間以内で届かないなら、我々を連絡してください。Note：ゴミ箱の検査を忘れないでください。）

Amazon AWS Certified Data Engineer - Associate (DEA-C01) 認定 Data-Engineer-Associate 試験問題:

1. A company wants to use Apache Spark jobs that run on an Amazon EMR cluster to process streaming data.
The Spark jobs will transform and store the data in an Amazon S3 bucket. The company will use Amazon Athena to perform analysis.
The company needs to optimize the data format for analytical queries.
Which solutions will meet these requirements with the SHORTEST query times? (Select TWO.)

A) Use ORC format. Store schema definitions in separate files in Amazon S3.
B) Use Apache Parquet format. Use AWS Glue Data Catalog to track schema changes.
C) Use Avro format. Use AWS Glue Data Catalog to track schema changes.
D) Use Apache Parquet format. Use an external Amazon DynamoDB table to track schema changes.
E) Use ORC format. Use AWS Glue Data Catalog to track schema changes.

2. A data engineer needs to analyze time-sensitive sales data. The company stores the data in an Amazon S3 bucket. The data engineer uses AWS Glue Data Catalog to access the data.
When performing the analysis, the data engineer notices that some records are missing or out of date.
What is the likely cause of these issues?

A) Versioning is not enabled on the S3 bucket.
B) AWS Glue Data Catalog is not up to date with the latest S3 partition changes.
C) The AWS Glue job schedules overlap with one another.
D) Incorrect IAM roles are assigned to the AWS Glue jobs.

3. A data engineer must build an extract, transform, and load (ETL) pipeline to process and load data from 10 source systems into 10 tables that are in an Amazon Redshift database. All the source systems generate .csv, JSON, or Apache Parquet files every 15 minutes. The source systems all deliver files into one Amazon S3 bucket. The file sizes range from 10 MB to 20 GB. The ETL pipeline must function correctly despite changes to the data schema.
Which data pipeline solutions will meet these requirements? (Choose two.)

A) Use an Amazon EventBridge rule to invoke an AWS Glue workflow job every 15 minutes. Configure the AWS Glue workflow to have an on-demand trigger that runs an AWS Glue crawler and then runs an AWS Glue job when the crawler finishes running successfully. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.
B) Configure an AWS Lambda function to invoke an AWS Glue job when a file is loaded into the S3 bucket. Configure the AWS Glue job to read the files from the S3 bucket into an Apache Spark DataFrame. Configure the AWS Glue job to also put smaller partitions of the DataFrame into an Amazon Kinesis Data Firehose delivery stream. Configure the delivery stream to load data into the Amazon Redshift tables.
C) Use an Amazon EventBridge rule to run an AWS Glue job every 15 minutes. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.
D) Configure an AWS Lambda function to invoke an AWS Glue workflow when a file is loaded into the S3 bucket. Configure the AWS Glue workflow to have an on-demand trigger that runs an AWS Glue crawler and then runs an AWS Glue job when the crawler finishes running successfully. Configure the AWS Glue job to process and load the data into the Amazon Redshift tables.
E) Configure an AWS Lambda function to invoke an AWS Glue crawler when a file is loaded into the S3 bucket. Configure an AWS Glue job to process and load the data into the Amazon Redshift tables.
Create a second Lambda function to run the AWS Glue job. Create an Amazon EventBridge rule to invoke the second Lambda function when the AWS Glue crawler finishes running successfully.

4. A data engineer needs to securely transfer 5 TB of data from an on-premises data center to an Amazon S3 bucket. Approximately 5% of the data changes every day. Updates to the data need to be regularly proliferated to the S3 bucket. The data includes files that are in multiple formats. The data engineer needs to automate the transfer process and must schedule the process to run periodically.
Which AWS service should the data engineer use to transfer the data in the MOST operationally efficient way?

A) AWS DataSync
B) AWS Glue
C) Amazon S3 Transfer Acceleration
D) AWS Direct Connect

5. A company stores sensitive transaction data in an Amazon S3 bucket. A data engineer must implement controls to prevent accidental deletions.

A) Enable versioning on the S3 bucket and configure MFA delete.
B) Create an S3 Lifecycle rule that moves deleted files to S3 Glacier Deep Archive.
C) Configure an S3 bucket policy rule that denies the creation of S3 delete markers.
D) Set up AWS Config remediation actions to prevent users from deleting S3 objects.

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