Mike Hall Mike Hall's Profile Page

Mike Hall Mike Hall

0 Course Enrolled • 0 Course Completed

Biography

Data-Engineer-Associate模擬試験問題集、Data-Engineer-Associate日本語版参考資料

無料でクラウドストレージから最新のXhs1991 Data-Engineer-Associate PDFダンプをダウンロードする：https://drive.google.com/open?id=1Qu16nOhdcMXiX4g7gvUFVtUvD82xELwk

Xhs1991は客様の要求を満たせていい評判をうけいたします。たくさんのひとは弊社の商品を使って、試験に順調に合格しました。そして、かれたちがリピーターになりました。Xhs1991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、一年の無料オンラインの更新のサービスがあり、100%のパス率を保証して、もし試験に合格しないと、弊社は全額で返金いたします。

Amazon Data-Engineer-Associate認証はIT業界にとても重要な地位があることがみんなが、たやすくその証本をとることはではありません。いまの市場にとてもよい問題集が探すことは難しいです。でも、Xhs1991にいつでも最新な問題を探すことができ、完璧な解説を楽に勉強することができます。

>> Data-Engineer-Associate模擬試験問題集 <<

Data-Engineer-Associate日本語版参考資料 & Data-Engineer-Associate受験資料更新版

学習の目的は何ですか？なぜ勉強する必要があるのですか？なぜData-Engineer-Associate試験に長い間勉強したのですか？多くの人が考えるように、いつか三角形の面積の式を忘れても、私たちはまだ非常によく生きることができますが、Data-Engineer-Associate試験を学び知識を取得しようとする知識がなければ、どのようにできますか将来の生活に良い機会がありますか？したがって、試験は必要です。テストData-Engineer-Associate認定を取得し、認定を取得し、私たちをより良く証明し、将来の人生への道を開くために。

Amazon AWS Certified Data Engineer - Associate (DEA-C01) 認定 Data-Engineer-Associate 試験問題 (Q55-Q60):

質問 # 55
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 Amazon Simple Queue Service(Amazon SQS) to buffer incomingsensor data. Use AWS Glue to store thedata in Amazon RDS for querying.
B. Use a self-hosted Apache Kafka cluster to capture the sensor data. Store the data in Amazon S3 for querying.
C. Use Amazon Kinesis Data Streams to capture the sensor data. Store the data in Amazon DynamoDB for querying.
D. Use AWS Lambda to process the sensor data. Store the data in Amazon S3 for querying.

正解：C

質問 # 56
A company uses Amazon DataZone as a data governance and business catalog solution. The company stores data in an Amazon S3 data lake. The company uses AWS Glue with an AWS Glue Data Catalog.
A data engineer needs to publish AWS Glue Data Quality scores to the Amazon DataZone portal.
Which solution will meet this requirement?

A. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an Amazon Redshift data source.Enable the data quality configuration for the data source.
B. Create a data quality ruleset with Data Quality Definition Language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.
C. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.
D. Create a data quality ruleset with Data Quality Definition Language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.

正解：D

解説：
Publishing AWS Glue data quality scores to Amazon DataZone requires creating aDQDL ruleset, scheduling it to run regularly, and then linking the corresponding AWS Glue table as a data source in the DataZone project. The setup ensures that data quality scores from Glue are correctly published and accessible within Amazon DataZone:
"You can define DQDL rulesets for Glue tables and publish the data quality results to DataZone when the project is configured with an AWS Glue data source and the rulesets are scheduled."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf OptionCfollows the expected flow without unnecessary complexity and aligns perfectly with theintegration flow supported by AWS.

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

正解：B

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
A company needs to set up a data catalog and metadata management for data sources that run in the AWS Cloud. The company will use the data catalog to maintain the metadata of all the objects that are in a set of data stores. The data stores include structured sources such as Amazon RDS and Amazon Redshift. The data stores also include semistructured sources such as JSON files and .xml files that are stored in Amazon S3.
The company needs a solution that will update the data catalog on a regular basis. The solution also must detect changes to the source metadata.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use the AWS Glue Data Catalog as the central metadata repository. Use AWS Glue crawlers to connect to multiple data stores and to update the Data Catalog with metadata changes. Schedule the crawlers to run periodically to update the metadata catalog.
B. Use the AWS Glue Data Catalog as the central metadata repository. Extract the schema for Amazon RDS and Amazon Redshift sources, and build the Data Catalog. Use AWS Glue crawlers for data that is in Amazon S3 to infer the schema and to automatically update the Data Catalog.
C. Use Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the DynamoDB data catalog. Schedule the Lambda functions to run periodically.
D. Use Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the Aurora data catalog. Schedule the Lambda functions to run periodically.

正解：A

解説：
This solution will meet the requirements with the least operational overhead because it uses the AWS Glue Data Catalog as the central metadata repository for data sources that run in the AWS Cloud. The AWS Glue Data Catalog is a fully managed service that provides a unified view of your data assets across AWS and on- premises data sources. It stores the metadata of your data in tables, partitions, and columns, and enables you to access and query your data using various AWS services, such as Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum. You can use AWS Glue crawlers to connect to multiple data stores, such as Amazon RDS, Amazon Redshift, and Amazon S3, and to update the Data Catalog with metadata changes.
AWS Glue crawlers can automatically discover the schema and partition structure of your data, and create or update the corresponding tables in the Data Catalog. You can schedule the crawlers to run periodically to update the metadata catalog, and configure them to detect changes to the source metadata, such as new columns, tables, or partitions12.
The other options are not optimal for the following reasons:
* A. Use Amazon Aurora as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the Aurora data catalog. Schedule the Lambda functions to run periodically. This option is not recommended, as it would require more operational overhead to create and manage an Amazon Aurora database as the data catalog, and to write and maintain AWS Lambda functions to gather and update the metadata information from multiple sources. Moreover, this option would not leverage the benefits of the AWS Glue Data Catalog, such as data cataloging, data transformation, and data governance.
* C. Use Amazon DynamoDB as the data catalog. Create AWS Lambda functions that will connect to the data catalog. Configure the Lambda functions to gather the metadata information from multiple sources and to update the DynamoDB data catalog. Schedule the Lambda functions to run periodically. This option is also not recommended, as it would require more operational overhead to create and manage an Amazon DynamoDB table as the data catalog, and to write and maintain AWS Lambda functions to gather and update the metadata information from multiple sources. Moreover, this option would not leverage the benefits of the AWS Glue Data Catalog, such as data cataloging, data transformation, and data governance.
* D. Use the AWS Glue Data Catalog as the central metadata repository. Extract the schema for Amazon RDS and Amazon Redshift sources, and build the Data Catalog. Use AWS Glue crawlers for data that is in Amazon S3 to infer the schema and to automatically update the Data Catalog. This option is not optimal, as it would require more manual effort to extract the schema for Amazon RDS and Amazon Redshift sources, and to build the Data Catalog. This option would not take advantage of the AWS Glue crawlers' ability to automatically discover the schema and partition structure of your data from various data sources, and to create or update the corresponding tables in the Data Catalog.
References:
* 1: AWS Glue Data Catalog
* 2: AWS Glue Crawlers
* : Amazon Aurora
* : AWS Lambda
* : Amazon DynamoDB

質問 # 59
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 analysis.
B. Define and create the calculated field in the visual.
C. Define and create the calculated field in the dataset.
D. Define and create the calculated field in the dashboard.

正解：C

質問 # 60
......

コンテンツの更新に加えて、Data-Engineer-Associateトレーニング資料のシステムも更新されます。ご意見がありましたら、私たちの共通の目標は、ユーザーが満足する製品を作成することであると言えます。学習を開始した後、メールをチェックするための固定時間を設定できることを願っています。 Data-Engineer-Associate実践ガイドまたはシステムの内容が更新された場合、更新された情報を電子メールアドレスに送信します。もちろん、製品の更新状況については、当社の電子メールをご覧ください。 Data-Engineer-Associate模擬試験を使用してData-Engineer-Associate試験に合格するように協力できることを願っています。

Data-Engineer-Associate日本語版参考資料: https://www.xhs1991.com/Data-Engineer-Associate.html

Amazon Data-Engineer-Associate模擬試験問題集しかし、働いている皆様は多くの時間と精力を使って試験を準備することができません、もちろん、Data-Engineer-Associate問題集を選ぶべきです、あなたがするべきことは、Xhs1991のAmazonのData-Engineer-Associate試験トレーニング資料に受かるのです、遠慮なく、我々はあなたがData-Engineer-Associate日本語版参考資料 - AWS Certified Data Engineer - Associate (DEA-C01)試験問題を購入する前に、あなたに無料デモを提供します、キーポイントと最新情報を選択して、Data-Engineer-Associateガイドトレントを完成させています、知識の時代の到来により、さまざまな労働条件や学習条件で自分自身を証明するために、Amazon Data-Engineer-Associate日本語版参考資料などの専門的な証明書が必要になります、Data-Engineer-Associateは、グロバールで最大の会社の1つです。

もっとひどくなるかもしれない、だが、兄の手前、修学旅行には行かせることはできなかったのだ、しかし、働いている皆様は多くの時間と精力を使って試験を準備することができません、もちろん、Data-Engineer-Associate問題集を選ぶべきです。

有難いData-Engineer-Associate模擬試験問題集一回合格-権威のあるData-Engineer-Associate日本語版参考資料

あなたがするべきことは、Xhs1991のAmazonのData-Engineer-Associate試験トレーニング資料に受かるのです、遠慮なく、我々はあなたがAWS Certified Data Engineer - Associate (DEA-C01)試験問題を購入する前に、あなたに無料デモを提供します、キーポイントと最新情報を選択して、Data-Engineer-Associateガイドトレントを完成させています。