Chris West Chris West's Profile Page

Chris West Chris West

0 Course Enrolled • 0 Course Completed

Biography

最新のData-Engineer-Associateオンライン試験一回合格-ハイパスレートのData-Engineer-Associate認定試験トレーリング

BONUS！！！ Jpexam 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=1Ss8c3Awhi1x1nZ75zLNQnIfyErTEXi8B

もし、あなたはData-Engineer-Associate試験に合格することを願っています。しかし、いい復習資料を見つけません。Data-Engineer-Associate復習資料はちようどあなたが探しているものです。Data-Engineer-Associate復習資料は的中率が高く、便利で、使いやすく、全面的なものです。従って、早くData-Engineer-Associate復習資料を入手しましょう！

Amazon　Data-Engineer-Associate試験参考書を利用すれば、あなたは多くの時間を節約するだけでなく、いろいろな知識を身につけます。最も重要なのは、Data-Engineer-Associate認定試験資格証明書を取得できるということです。また、Data-Engineer-Associate試験参考書の合格率は高いので、Data-Engineer-Associate試験に落ちる必要がないです。

>> Data-Engineer-Associateオンライン試験 <<

Amazon Data-Engineer-Associate認定試験トレーリング、Data-Engineer-Associate試験問題解説集

Amazon　Data-Engineer-Associate認定資格試験が難しいので、弊社のData-Engineer-Associate問題集はあなたに適当する認定資格試験問題集を見つけるし、本当の試験問題の難しさを克服することができます。弊社はAmazon　Data-Engineer-Associate認定試験の最新要求に従って関心を持って、全面的かつ高品質な模擬試験問題集を提供します。また、購入する前に、無料でData-Engineer-AssociateのPDF版デモをダウンロードでき、信頼性を確認することができます。

Amazon AWS Certified Data Engineer - Associate (DEA-C01) 認定 Data-Engineer-Associate 試験問題 (Q53-Q58):

質問 # 53
A manufacturing company wants to collect data from sensors. A data engineer needs to implement a solution that ingests sensor data in near real time.
The solution must store the data to a persistent data store. The solution must store the data in nested JSON format. The company must have the ability to query from the data store with a latency of less than 10 milliseconds.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use AWS Lambda to process the sensor data. Store the data in Amazon S3 for querying.
B. Use Amazon Simple Queue Service(Amazon SQS) to buffer incomingsensor data. Use AWS Glue to store thedata in Amazon RDS for querying.
C. Use Amazon Kinesis Data Streams to capture the sensor data. Store the data in Amazon DynamoDB for querying.
D. Use a self-hosted Apache Kafka cluster to capture the sensor data. Store the data in Amazon S3 for querying.

正解：C

質問 # 54
A data engineer must manage the ingestion of real-time streaming data into AWS. The data engineer wants to perform real-time analytics on the incoming streaming data by using time-based aggregations over a window of up to 30 minutes. The data engineer needs a solution that is highly fault tolerant.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data that might occasionally contain duplicates by using multiple types of aggregations.
B. Use an AWS Lambda function that includes both the business and the analytics logic to perform aggregations for a tumbling window of up to 30 minutes, based on the event timestamp.
C. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to analyze the data by using multiple types of aggregations to perform time-based analytics over a window of up to 30 minutes.
D. Use an AWS Lambda function that includes both the business and the analytics logic to perform time- based aggregations over a window of up to 30 minutes for the data in Amazon Kinesis Data Streams.

正解：D

解説：
This solution meets the requirements of managing the ingestion of real-time streaming data into AWS and performing real-time analytics on the incoming streaming data with the least operational overhead. Amazon Managed Service for Apache Flink is a fully managed service that allows you to run Apache Flink applications without having to manage any infrastructure or clusters. Apache Flink is a framework for stateful stream processing that supports various types of aggregations, such as tumbling, sliding, and session windows, over streaming data. By using Amazon Managed Service for Apache Flink, you can easily connect to Amazon Kinesis Data Streams as the source and sink of your streaming data, and perform time-based analytics over a window of up to 30 minutes. This solution is also highly fault tolerant, as Amazon Managed Service for Apache Flink automatically scales, monitors, and restarts your Flink applications in case of failures. References:
* Amazon Managed Service for Apache Flink
* Apache Flink
* Window Aggregations in Flink

質問 # 55
A company runs multiple applications on AWS. The company configured each application to output logs. The company wants to query and visualize the application logs in near real time.
Which solution will meet these requirements?

A. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Use CloudWatch log anomaly detection to query and visualize the log data.
B. Create an Amazon OpenSearch Service domain. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an OpenSearch Service subscription filter for each log group to stream the data to OpenSearch. Create the required queries and dashboards in OpenSearch Service to analyze and visualize the data.
C. Configure the applications to output logs to Amazon CloudWatch Logs log groups. Create an Amazon S3 bucket. Create an AWS Lambda function that runs on a schedule to export the required log groups to the S3 bucket. Use Amazon Athena to query the log data in the S3 bucket.
D. Update the application code to send the log data to Amazon QuickSight by using Super-fast, Parallel, In- memory Calculation Engine (SPICE). Create the required analyses and dashboards in QuickSight.

正解：B

解説：
The optimal solution for near-real-time querying and visualization of logs is to integrateAmazon CloudWatch LogswithAmazon OpenSearch Serviceusingsubscription filters, which stream the logs directly into OpenSearch for querying and dashboarding:
"Use OpenSearch Service with CloudWatch Logs and create a subscription filter to stream log data in near real time into OpenSearch. Then use OpenSearch dashboards for visualization."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf This approach offers low latency and avoids batch exports, unlike the scheduled Athena + S3 pattern.

質問 # 56
A company has an Amazon Redshift data warehouse that users access by using a variety of IAM roles. More than 100 users access the data warehouse every day.
The company wants to control user access to the objects based on each user's job role, permissions, andhow sensitive the data is.
Which solution will meet these requirements?

A. Use the role-based access control (RBAC) feature of Amazon Redshift.
B. Use the column-level security (CLS) feature of Amazon Redshift.
C. Use dynamic data masking policies in Amazon Redshift.
D. Use the row-level security (RLS) feature of Amazon Redshift.

正解：A

解説：
Amazon Redshift supportsRole-Based Access Control (RBAC)to manage access to database objects. RBAC allows administrators to create roles for job functions and assign privileges at the schema, table, or column level based on data sensitivity and user roles.
"RBAC in Amazon Redshift helps manage permissions more efficiently at scale by assigning users to roles that reflect their job function. It simplifies user management and secures access based on job role and data sensitivity."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf RBAC is preferred over RLS or CLS alone because it offers a more comprehensive and scalable solution across multiple users and permissions.

質問 # 57
A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded.
A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB.
How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table?

A. Use a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events.
B. Use the Amazon Redshift Data API to publish an event to Amazon EventBridqe. Configure an EventBridge rule to invoke the Lambda function.
C. Use the Amazon Redshift Data API to publish a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function.
D. Use a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.

正解：C

解説：
The Amazon Redshift Data API enables you to interact with your Amazon Redshift data warehouse in an easy and secure way. You can use the Data API to run SQL commands, such as loading data into tables, without requiring a persistent connection to the cluster. The Data API also integrates with Amazon EventBridge, which allows you to monitor the execution status of your SQL commands and trigger actions based on events. By using the Data API to publish an event to EventBridge, the data engineer can invoke the Lambda function that writes the load statuses to the DynamoDB table. This solution is scalable, reliable, and cost-effective. The other options are either not possible or not optimal. You cannot use a second Lambda function to invoke the first Lambda function based on CloudWatch or CloudTrail events, as these services do not capture the load status of Redshift tables. You can use the Data API to publish a message to an SQS queue, but this would require additional configuration and polling logic to invoke the Lambda function from the queue. This would also introduce additional latency and cost. Reference:
Using the Amazon Redshift Data API
Using Amazon EventBridge with Amazon Redshift
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.2: Amazon Redshift

質問 # 58
......

あなたの人生に残念と後悔を残しないように、私たちはできるだけ人生を変えるあらゆるチャンスをつかむ必要があります。あなたはそれをやったことができましたか。JpexamのAmazonのData-Engineer-Associate試験トレーニング資料は成功したいIT職員のために作成されたのです。あなたがAmazonのData-Engineer-Associate認定試験に合格することを助けます。成功と擦れ違うことを避けるように速く行動しましょう。

Data-Engineer-Associate認定試験トレーリング: https://www.jpexam.com/Data-Engineer-Associate_exam.html

Amazon Data-Engineer-Associateオンライン試験数年以来の試験問題集を研究しています、Amazon Data-Engineer-Associateオンライン試験未来のある日、椅子で休むとき、自分の人生を思い出したときに笑顔が出たら成功な人生になります、Amazon Data-Engineer-Associateオンライン試験教材の品質は保証されています、Jpexam Data-Engineer-Associate認定試験トレーリングは、高品質試験トレーニング資材を持っています、JpexamのAmazonのData-Engineer-Associate試験トレーニング資料は特別に受験生を対象として研究されたものです、無料デモの問題はData-Engineer-Associate試験練習資料の一部分です、Amazon Data-Engineer-Associate オンライン試験しかしながら、試験の大切さと同じ、この試験も非常に難しいです。

あ、あぐッ、こういうの、嫌いだな、数年以来の試験問題集を研究してData-Engineer-Associateいます、未来のある日、椅子で休むとき、自分の人生を思い出したときに笑顔が出たら成功な人生になります、教材の品質は保証されています。

実際的なData-Engineer-Associateオンライン試験 & 合格スムーズData-Engineer-Associate認定試験トレーリング | 100％合格率のData-Engineer-Associate試験問題解説集

Jpexamは、高品質試験トレーニング資材を持っています、JpexamのAmazonのData-Engineer-Associate試験トレーニング資料は特別に受験生を対象として研究されたものです。

2025年Jpexam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=1Ss8c3Awhi1x1nZ75zLNQnIfyErTEXi8B