Data-Engineer-Associate日本語解説集、Data-Engineer-Associate学習体験談

Wiki Article

さらに、Topexam Data-Engineer-Associateダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1naVOokuzuQV7oPwxbNQXlgQc9_EMgJT2

初心者でも経験豊富な人でも、Topexam学習教材は、長年にわたる試験概要の変化と業界の傾向に基づいて編集された専門家にとって最適な選択です。 Data-Engineer-Associateテストトレントは、学習の効率を向上させるのに役立つだけでなく、レビュー時間を最大数か月から1か月、さらには2週間または3週間に短縮するのにも役立ちます。 最大の改善を得る。 そして、Data-Engineer-Associate試験問題により、Amazon、あなたのAWS Certified Data Engineer - Associate (DEA-C01)成功が保証されます。

TopexamのAmazonのData-Engineer-Associate試験トレーニング資料の知名度が非常に高いことを皆はよく知っています。Topexam は世界的によく知られているサイトです。どうしてこのような大きな連鎖反応になりましたか。それはTopexamのAmazonのData-Engineer-Associate試験トレーニング資料は適用性が高いもので、本当にみなさんが良い成績を取ることを助けられるからです。

>> Data-Engineer-Associate日本語解説集 <<

Data-Engineer-Associate学習体験談 & Data-Engineer-Associate試験参考書

もし君がサラリーマンで、もし君が早い時間でAmazonのData-Engineer-Associate認定試験に合格したいなら、Topexamは君のベストな選択になります。うちのAmazonのData-Engineer-Associate学習教材はTopexamのIT専門家たちが研究して、実践して開発されたものです。それは十年過ぎのIT認証経験を持っています。うちの商品を使ったら、君は最も早い時間で、簡単に認定試験に合格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 (Q247-Q252):

質問 # 247
A company uses Amazon S3 buckets, AWS Glue tables, and Amazon Athena as components of a data lake.
Recently, the company expanded its sales range to multiple new states. The company wants to introduce state names as a new partition to the existing S3 bucket, which is currently partitioned by date.
The company needs to ensure that additional partitions will not disrupt daily synchronization between the AWS Glue Data Catalog and the S3 buckets.
Which solution will meet these requirements with the LEAST operational overhead?

正解：D

解説：
Explanation: Scheduling an AWS Glue crawler to periodically update the Data Catalog automates the process of detecting new partitions and updating the catalog, which minimizes manual maintenance and operational overhead.


質問 # 248
A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket.
The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility.
Which solution will meet these requirements with the LOWEST latency?

正解：C

解説：
This solution will meet the requirements with the lowest latency because it uses Amazon Managed Service for Apache Flink to process the sensor data in real time and write it to Amazon Timestream, a fast, scalable, and serverless time series database. Amazon Timestream is optimized for storing and analyzing time series data, such as sensor data, and can handle trillions of events per day with millisecond latency. By using Amazon Timestream as a source, you can create an Amazon QuickSight dashboard that displays a real-time view of operational efficiency on a large screen in the manufacturingfacility. Amazon QuickSight is a fully managed business intelligence service that can connect to various data sources, including Amazon Timestream, and provide interactive visualizations and insights123.
The other options are not optimal for the following reasons:
* A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard. This option is similar to option C, but it uses Grafana instead of Amazon QuickSight to create the dashboard.
Grafana is an open source visualization tool that can also connect to Amazon Timestream, but it requires additional steps to set up and configure, such as deploying a Grafana server on Amazon EC2, installing the Amazon Timestream plugin, and creating an IAM role for Grafana to access Timestream.
These steps can increase the latency and complexity of the solution.
* B. Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard. This option is not suitable for displaying a real-time view of operational efficiency, as it introduces unnecessary delays and costs in the data pipeline. First, the sensor data is written to an S3 bucket by Amazon Kinesis Data Firehose, which can have a buffering interval of up to 900 seconds. Then, the S3 bucket sends a notification to a Lambda function, which can incur additional invocation and execution time. Finally, the Lambda function publishes the data to Amazon Aurora, a relational database that is not optimized for time series data and can have higher storage and performance costs than Amazon Timestream .
* D. Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.
This option is also not suitable for displaying a real-time view of operational efficiency, as it uses AWS Glue bookmarks to read sensor data from the S3 bucket. AWS Glue bookmarks are a feature that helps AWS Glue jobs and crawlers keep track of the data that has already been processed, so that they can resume from where they left off. However, AWS Glue jobs and crawlers are not designed for real-time data processing, as they can have a minimum frequency of 5 minutes and a variable start-up time.
Moreover, this option also uses Grafana instead of Amazon QuickSight to create the dashboard, which can increase the latency and complexity of the solution .
:
1: Amazon Managed Streaming for Apache Flink
2: Amazon Timestream
3: Amazon QuickSight
4: Analyze data in Amazon Timestream using Grafana
5: Amazon Kinesis Data Firehose
6: Amazon Aurora
7: AWS Glue Bookmarks
8: AWS Glue Job and Crawler Scheduling


質問 # 249
A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time.
Which solution will run the Glue jobs in the MOST cost-effective way?

正解：A

解説：
The FLEX execution class allows you to run AWS Glue jobs on spare compute capacity instead of dedicated hardware. This can reduce the cost of running non-urgent or non-time sensitive data integration workloads, such as testing and one-time data loads. The FLEX execution class is available for AWS Glue 3.0 Spark jobs.
The other options are not as cost-effective as FLEX, because they either use dedicated resources (STANDARD) or do not affect the cost at all (Spot Instance type and GlueVersion). References:
Introducing AWS Glue Flex jobs: Cost savings on ETL workloads
Serverless Data Integration - AWS Glue Pricing
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide (Chapter 5, page 125)


質問 # 250
A company analyzes data in a data lake every quarter to perform inventory assessments. A data engineer uses AWS Glue DataBrew to detect any personally identifiable information (PII) about customers within the dat a. The company's privacy policy considers some custom categories of information to be PII. However, the categories are not included in standard DataBrew data quality rules.
The data engineer needs to modify the current process to scan for the custom PII categories across multiple datasets within the data lake.
Which solution will meet these requirements with the LEAST operational overhead?

正解：D

解説：
The data engineer needs to detect custom categories of PII within the data lake using AWS Glue DataBrew. While DataBrew provides standard data quality rules, the solution must support custom PII categories.
Option B: Implement custom data quality rules in DataBrew. Apply the custom rules across datasets.
This option is the most efficient because DataBrew allows the creation of custom data quality rules that can be applied to detect specific data patterns, including custom PII categories. This approach minimizes operational overhead while ensuring that the specific privacy requirements are met.
Options A, C, and D either involve manual intervention or developing custom scripts, both of which increase operational effort compared to using DataBrew's built-in capabilities.
Reference:
AWS Glue DataBrew Documentation


質問 # 251
A data engineer is troubleshooting an AWS Glue workflow that occasionally fails. The engineer determines that the failures are a result of data quality issues. A business reporting team needs to receive an email notification any time the workflow fails in the future.
Which solution will meet this requirement?

正解：B


質問 # 252
......

そうでなければ、時代遅れになるリスクを負います。当社のData-Engineer-Associate認定テストは、技術スキルを向上させ、さらに重要なこととして、厳しい労働環境で明るい未来のために戦う自信を高めるのに役立ちます。当社の専門家は、Data-Engineer-Associate学習ツールの開発に多くの時間とエネルギーを費やしています。あなたは私たちを信頼し、あなたの将来の発展において私たちをあなたの正直な協力者にすることができます。参考までに、Data-Engineer-Associate試験の利点をいくつかご紹介します。

Data-Engineer-Associate学習体験談: https://www.topexam.jp/Data-Engineer-Associate_shiken.html

Amazon Data-Engineer-Associate日本語解説集
仮想試験 - 時間制限付きに試験問題で自分自身をテストします、その後、リンクをクリックしてログインすると、ソフトウェアを使用してData-Engineer-Associate prepトレントをすぐに学習できます、Data-Engineer-Associateクイズトレントは、急速な発展の世界のさまざまな分野の多くの専門家や教授によって設計されました、Topexam Data-Engineer-Associate学習体験談が短期な訓練を提供し、一回に君の試験に合格させることができます、TopexamのAmazonのData-Engineer-Associate試験トレーニング資料は豊富な経験を持っているIT専門家が研究したものです、Amazon Data-Engineer-Associate日本語解説集 我々の専門家たちはタイムリーに勉強資料を更新しています。

慧夢は実に楽しそうだった、けれど、気持ちいい、
仮想試験 - 時間制限付きに試験問題で自分自身をテストします、その後、リンクをクリックしてログインすると、ソフトウェアを使用してData-Engineer-Associate prepトレントをすぐに学習できます。

試験の準備方法-効率的なData-Engineer-Associate日本語解説集試験-実際的なData-Engineer-Associate学習体験談

Data-Engineer-Associateクイズトレントは、急速な発展の世界のさまざまな分野の多くの専門家や教授によって設計されました、Topexamが短期な訓練を提供し、一回に君の試験に合格させることができます、TopexamのAmazonのData-Engineer-Associate試験トレーニング資料は豊富な経験を持っているIT専門家が研究したものです。

BONUS！！！ Topexam 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=1naVOokuzuQV7oPwxbNQXlgQc9_EMgJT2

Report this wiki page