Data-Engineer-Associate試験、最新のData-Engineer-Associate試験問題対策、AWS Certified Data Engineer - Associate (DEA-C01)無料デモ

BONUS！！！ CertJuken Data-Engineer-Associateダンプの一部を無料でダウンロード：https://drive.google.com/open?id=1aixICd2GA7_q-4fxTSFYNJV-ykKyQWlo

この驚くほど高く受け入れられている試験に適合するには、Data-Engineer-Associate学習教材のような上位の実践教材で準備する必要があります。彼らは時間とお金の面で最良の選択です。この試験について決心している限り、その職業は疑う余地がないことを理解できます。そして、彼らの職業はData-Engineer-Associateトレーニング準備で徹底的に表現されています。彼らはData-Engineer-Associate試験の本当の知識をつかみ、忘れられない経験をするのに非常に役立ちます。この小さなメリットをお見逃しなく。

私はあなたがData-Engineer-Associate試験に合格したいことを知っています。私たちのData-Engineer-Associate学習教材は、多くの人が試験に合格するのを助け、あなたを助けようと思います。私たちのData-Engineer-Associate学習教材の99％の合格率は高いです。また、あなたの自分の努力が必要です。そして、私たちのData-Engineer-Associate試験問題を利用すれば、あなたは絶対試験に合格できます。

>> Data-Engineer-Associate日本語認定対策 <<

Amazon Data-Engineer-Associate模試エンジン、Data-Engineer-Associate日本語版復習指南

CertJukenはあなたが次のAmazonのData-Engineer-Associate認定試験に合格するように最も信頼できるトレーニングツールを提供します。CertJukenのAmazonのData-Engineer-Associate勉強資料は問題と解答を含めています。それは実践の検査に合格したソフトですから、全ての関連するIT認証に満たすことができます。

Amazon AWS Certified Data Engineer - Associate (DEA-C01) 認定 Data-Engineer-Associate 試験問題 (Q72-Q77):

質問 # 72
A company stores data in a data lake that is in Amazon S3. Some data that the company stores in the data lake contains personally identifiable information (PII). Multiple user groups need to access the raw data. The company must ensure that user groups can access only the PII that they require.
Which solution will meet these requirements with the LEAST effort?

A. Use Amazon QuickSight to access the data. Use column-level security features in QuickSight to limit the PII that users can retrieve from Amazon S3 by using Amazon Athena. Define QuickSight access levels based on the PII access requirements of the users.
B. Use Amazon Athena to query the data. Set up AWS Lake Formation and create data filters to establish levels of access for the company's IAM roles. Assign each user to the IAM role that matches the user's PII access requirements.
C. Build a custom query builder UI that will run Athena queries in the background to access the data.
Create user groups in Amazon Cognito. Assign access levels to the user groups based on the PII access requirements of the users.
D. Create IAM roles that have different levels of granular access. Assign the IAM roles to IAM user groups. Use an identity-based policy to assign access levels to user groups at the column level.

正解：B

解説：
Amazon Athena is a serverless, interactive query service that enables you to analyze data in Amazon S3 using standard SQL. AWS Lake Formation is a service that helps you build, secure, and manage data lakes on AWS. You can use AWS Lake Formation to create data filters that define the level of access for different IAM roles based on the columns, rows, or tags of the data. By using Amazon Athena to query the data and AWS Lake Formation to create data filters, the company can meet the requirements of ensuring that user groups can access only the PII that they require with the least effort. The solution is to use Amazon Athena to query the data in the data lake that is in Amazon S3. Then, set up AWS Lake Formation and create data filters to establish levels of access for the company's IAM roles. For example, a data filter can allow a user group to access only the columns that contain the PII that they need, such as name and email address, and deny access to the columns that contain the PII that they do not need, such as phone number and social security number.
Finally, assign each user to the IAM role that matches the user's PII access requirements. This way, the user groups can access the data in the data lake securely and efficiently. The other options are either not feasible or not optimal. Using Amazon QuickSight to access the data (option B) would require the company to pay for the QuickSight service and to configure the column-level security features for each user. Building a custom query builder UI that will run Athena queries in the background to access the data (option C) would require the company to develop and maintain the UI and to integrate it with Amazon Cognito. Creating IAM roles that have different levels of granular access (option D) would require the company to manage multiple IAM roles and policies and to ensure that they are aligned with the data schema. References:
* Amazon Athena
* AWS Lake Formation
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 4: Data Analysis and Visualization, Section 4.3: Amazon Athena

質問 # 73
An ecommerce company wants to use AWS to migrate data pipelines from an on-premises environment into the AWS Cloud. The company currently uses a third-party too in the on-premises environment to orchestrate data ingestion processes.
The company wants a migration solution that does not require the company to manage servers. The solution must be able to orchestrate Python and Bash scripts. The solution must not require the company to refactor any code.
Which solution will meet these requirements with the LEAST operational overhead?

A. AWS Step Functions
B. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
C. AWS Glue
D. AWS Lambda

正解：B

解説：
The ecommerce company wants to migrate its data pipelines into the AWS Cloud without managing servers, and the solution must orchestrate Python and Bash scripts without refactoring code. Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is the most suitable solution for this scenario.
Option B: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
MWAA is a managed orchestration service that supports Python and Bash scripts via Directed Acyclic Graphs (DAGs) for workflows. It is a serverless, managed version of Apache Airflow, which is commonly used for orchestrating complex data workflows, making it an ideal choice for migrating existing pipelines without refactoring. It supports Python, Bash, and other scripting languages, and the company would not need to manage the underlying infrastructure.
Other options:
AWS Lambda (Option A) is more suited for event-driven workflows but would require breaking down the pipeline into individual Lambda functions, which may require refactoring.
AWS Step Functions (Option C) is good for orchestration but lacks native support for Python and Bash without using Lambda functions, and it may require code changes.
AWS Glue (Option D) is an ETL service primarily for data transformation and not suitable for orchestrating general scripts without modification.
Reference:
Amazon Managed Workflows for Apache Airflow (MWAA) Documentation

質問 # 74
An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures.
The POC test uses objects in Amazon S3 that contain the metrics in .csv format. The POC test uses Amazon Athena to query the dat a. The data is partitioned in the S3 bucket by date.
As the amount of data increases, the company wants to optimize the storage solution to improve query performance.
Which combination of solutions will meet these requirements? (Choose two.)

A. Preprocess the .csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates.
B. Use an S3 bucket that is in the same AWS Region where the company runs Athena queries.
C. Add a randomized string to the beginning of the keys in Amazon S3 to get more throughput across partitions.
D. Preprocess the .csv data to JSON format by fetching only the document keys that the query requires.
E. Use an S3 bucket that is in the same account that uses Athena to query the data.

正解：A、B

解説：
Using an S3 bucket that is in the same AWS Region where the company runs Athena queries can improve query performance by reducing data transfer latency and costs. Preprocessing the .csv data to Apache Parquet format can also improve query performance by enabling columnar storage, compression, and partitioning, which can reduce the amount of data scanned and fetched by the query. These solutions can optimize the storage solution for the POC test without requiring much effort or changes to the existing data pipeline. The other solutions are not optimal or relevant for this requirement. Adding a randomized string to the beginning of the keys in Amazon S3 can improve the throughput across partitions, but it can also make the data harder to query and manage. Using an S3 bucket that is in the same account that uses Athena to query the data does not have any significant impact on query performance, as long as the proper permissions are granted. Preprocessing the .csv data to JSON format does not offer any benefits over the .csv format, as both are row-based and verbose formats that require more data scanning and fetching than columnar formats like Parquet. Reference:
Best Practices When Using Athena with AWS Glue
Optimizing Amazon S3 Performance
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

質問 # 75
A retail company is expanding its operations globally. The company needs to use Amazon QuickSight to accurately calculate currency exchange rates for financial reports. The company has an existing dashboard that includes a visual that is based on an analysis of a dataset that contains global currency values and exchange rates.
A data engineer needs to ensure that exchange rates are calculated with a precision of four decimal places.
The calculations must be precomputed. The data engineer must materialize results in QuickSight super-fast, parallel, in-memory calculation engine (SPICE).
Which solution will meet these requirements?

A. Define and create the calculated field in the dataset.
B. Define and create the calculated field in the dashboard.
C. Define and create the calculated field in the visual.
D. Define and create the calculated field in the analysis.

正解：A

質問 # 76
A company uses AWS Step Functions to orchestrate a data pipeline. The pipeline consists of Amazon EMR jobs that ingest data from data sources and store the data in an Amazon S3 bucket. The pipeline also includes EMR jobs that load the data to Amazon Redshift.
The company's cloud infrastructure team manually built a Step Functions state machine. The cloud infrastructure team launched an EMR cluster into a VPC to support the EMR jobs. However, the deployed Step Functions state machine is not able to run the EMR jobs.
Which combination of steps should the company take to identify the reason the Step Functions state machine is not able to run the EMR jobs? (Choose two.)

A. Check the retry scenarios that the company configured for the EMR jobs. Increase the number of seconds in the interval between each EMR task. Validate that each fallback state has the appropriate catch for each decision state. Configure an Amazon Simple Notification Service (Amazon SNS) topic to store the error messages.
B. Query the flow logs for the VPC. Determine whether the traffic that originates from the EMR cluster can successfully reach the data providers. Determine whether any security group that might be attached to the Amazon EMR cluster allows connections to the data source servers on the informed ports.
C. Verify that the Step Functions state machine code has all IAM permissions that are necessary to create and run the EMR jobs. Verify that the Step Functions state machine code also includes IAM permissions to access the Amazon S3 buckets that the EMR jobs use. Use Access Analyzer for S3 to check the S3 access properties.
D. Use AWS CloudFormation to automate the Step Functions state machine deployment. Create a step to pause the state machine during the EMR jobs that fail. Configure the step to wait for a human user to send approval through an email message. Include details of the EMR task in the email message for further analysis.
E. Check for entries in Amazon CloudWatch for the newly created EMR cluster. Change the AWS Step Functions state machine code to use Amazon EMR on EKS. Change the IAM access policies and the security group configuration for the Step Functions state machine code to reflect inclusion of Amazon Elastic Kubernetes Service (Amazon EKS).

正解：B、C

解説：
To identify the reason why the Step Functions state machine is not able to run the EMR jobs, the company should take the following steps:
* Verify that the Step Functions state machine code has all IAM permissions that are necessary to create and run the EMR jobs. The state machine code should have an IAM role that allows it to invoke the EMR APIs, such as RunJobFlow, AddJobFlowSteps, and DescribeStep. The state machine code should also have IAM permissions to access the Amazon S3 buckets that the EMR jobs use as input and output locations. The company can use Access Analyzer for S3 to check the access policies and permissions of the S3 buckets12. Therefore, option B is correct.
* Query the flow logs for the VPC. The flow logs can provide information about the network traffic to and from the EMR cluster that is launched in the VPC. The company can use the flow logs to determine whether the traffic that originates from the EMR cluster can successfully reach the data providers, such as Amazon RDS, Amazon Redshift, or other external sources. The company can also determine whether any security group that might be attached to the EMR cluster allows connections to the data source servers on the informed ports. The company can use Amazon VPC Flow Logs or Amazon CloudWatch Logs Insights to query the flow logs3 . Therefore, option D is correct.
Option A is incorrect because it suggests using AWS CloudFormation to automate the Step Functions state machine deployment. While this is a good practice to ensure consistency and repeatability of the deployment, it does not help to identify the reason why the state machine is not able to run the EMR jobs. Moreover, creating a step to pause the state machine during the EMR jobs that fail and wait for a human user to send approval through an email message is not a reliable way to troubleshoot the issue. The company should use the Step Functions console or API to monitor the execution historyand status of the state machine, and use Amazon CloudWatch to view the logs and metrics of the EMR jobs .
Option C is incorrect because it suggests changing the AWS Step Functions state machine code to use Amazon EMR on EKS. Amazon EMR on EKS is a service that allows you to run EMR jobs on Amazon Elastic Kubernetes Service (Amazon EKS) clusters. While this service has some benefits, such as lower cost and faster execution time, it does not support all the features and integrations that EMR on EC2 does, such as EMR Notebooks, EMR Studio, and EMRFS. Therefore, changing the state machine code to use EMR on EKS may not be compatible with the existing data pipeline and may introduce new issues.
Option E is incorrect because it suggests checking the retry scenarios that the company configured for the EMR jobs. While this is a good practice to handle transient failures and errors, it does not help to identify the root cause of why the state machine is not able to run the EMR jobs. Moreover, increasing the number of seconds in the interval between each EMR task may not improve the success rate of the jobs, and may increase the execution time and cost of the state machine. Configuring an Amazon SNS topic to store the error messages may help to notify the company of any failures, but it does not provide enough information to troubleshoot the issue.
:
1: Manage an Amazon EMR Job - AWS Step Functions
2: Access Analyzer for S3 - Amazon Simple Storage Service
3: Working with Amazon EMR and VPC Flow Logs - Amazon EMR
[4]: Analyzing VPC Flow Logs with Amazon CloudWatch Logs Insights - Amazon Virtual Private Cloud
[5]: Monitor AWS Step Functions - AWS Step Functions
[6]: Monitor Amazon EMR clusters - Amazon EMR
[7]: Amazon EMR on Amazon EKS - Amazon EMR

質問 # 77
......

長い間Data-Engineer-Associate認定を希望しているかもしれませんが、Amazon勉強する時間や良い方法がありません。勉強はつまらないと思っていたのかもしれません。 Data-Engineer-Associateの学習教材があなたの心を変えます。当社の製品を使用すると、すぐに勉強の幸せを感じるでしょう。熱心なCertJuken専門家のおかげで、Data-Engineer-Associate試験に合格するためのすばらしい学習ツールが考案されました。最初にデモを試してみると、勉強をやめられないことがわかります。 Data-Engineer-Associate学習教材を使用すると、自分自身に挑戦して、もっと知りたいと思うでしょう。

Data-Engineer-Associate模試エンジン: https://www.certjuken.com/Data-Engineer-Associate-exam.html

Data-Engineer-Associate学習教材は、他のトレーニング教材よりも高い合格率を持っているため、完全な結果を得ることができると確信しています、10年以上の発展とともに、私たちのData-Engineer-Associate試験問題集ファイルは、業界の最前線に位置しています、CertJukenが提供したAmazonのData-Engineer-Associate試験問題と解答が真実の試験の練習問題と解答は最高の相似性があります、弊社を信頼することを選択できる場合、Data-Engineer-Associateスタディガイドを使用すると良い経験が得られ、試験に合格し、テストData-Engineer-Associate認定で良い成績を得ることができると思います、Amazon Data-Engineer-Associate日本語認定対策そのけん異性は言うまでもありません、Amazon Data-Engineer-Associate日本語認定対策競争力が激しいこの社会では、面接と昇進とか場合に君の実力を証明する資格認定が不可欠です。

得体のしれない恐怖を感じ、走リ出す、目めのふちが黒くろずみ、肩かたが落おちて、病人びょうにんのようであった、Data-Engineer-Associate学習教材は、他のトレーニング教材よりも高い合格率を持っているため、完全な結果を得ることができると確信しています。

正確的なData-Engineer-Associate日本語認定対策 & 合格スムーズData-Engineer-Associate模試エンジン | 大人気Data-Engineer-Associate日本語版復習指南

10年以上の発展とともに、私たちのData-Engineer-Associate試験問題集ファイルは、業界の最前線に位置しています、CertJukenが提供したAmazonのData-Engineer-Associate試験問題と解答が真実の試験の練習問題と解答は最高の相似性があります。

弊社を信頼することを選択できる場合、Data-Engineer-Associateスタディガイドを使用すると良い経験が得られ、試験に合格し、テストData-Engineer-Associate認定で良い成績を得ることができると思います、そのけん異性は言うまでもありません。

2025年CertJukenの最新Data-Engineer-Associate PDFダンプおよびData-Engineer-Associate試験エンジンの無料共有：https://drive.google.com/open?id=1aixICd2GA7_q-4fxTSFYNJV-ykKyQWlo