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NEW QUESTION: 1
What are three possible ways to adhere to General Data Protection Regulation (GDPR) standards? Each correct answer presents a complete solution.
A. Prevent deletion of information about specific contacts.
B. Extract and share information related to a specific contact when requested.
C. Configure each customer journey to only process contacts that have given a minimum-required level of consent.
D. Configure each lead-scoring model to only compute scores for leads associated with contacts that have given a minimum-required level of consent.
E. Find and update information about a specific contact only when a third-party notifies you of updates needed for a contact or lead record.
Answer: B,C,D
Explanation:
Explanation/Reference:
References:
https://docs.microsoft.com/en-gb/dynamics365/customer-engagement/marketing/gdpr

NEW QUESTION: 2
ソリューションアーキテクトは、インターネットに接続された2,000のセンサーからデータを収集して保存するシステムを設計しています。各センサーは毎秒1 KBのデータを生成します。データは、システムに送信され、分析のために無期限に保存されてから数秒以内に分析に使用できる必要があります。
データを収集して保存するための最も費用対効果の高いソリューションはどれですか？
A. 各レコードをAmazon Kinesis Data Streamsに入れます。 AWS Lambda関数を使用して、時間ごとにレコードを整理し、レコードのキーをハッシュするプレフィックスを使用して、Amazon S3のオブジェクトに各レコードを書き込みます。
Kinesis Data Streamsの最近のデータとAmazon S3の履歴データを分析します。
B. 各レコードをAmazon DynamoDBテーブルに入れます。テーブルにクエリを実行して、最近のデータを分析します。 DynamoDBストリームに接続されたAWS Lambda関数を使用してレコードをグループ化し、それらをAmazon S3のオブジェクトに書き込み、DynamoDBテーブルからレコードを削除します。 DynamoDBテーブルの最近のデータとAmazon S3の履歴データを分析する
C. 各レコードをAmazon Kinesis Data Streamsに入れます。 Amazon Kinesis Data Firehouseをセットアップして、ストリームからレコードを読み取り、それらをAmazon S3のオブジェクトにグループ化します。 Kinesis Data Streamsの最近のデータとAmazon S3の履歴データを分析します。
D. 時間ごとにレコードを整理し、レコードのキーをハッシュするプレフィックスを持つAmazon S3のオブジェクトに各レコードを入れます。 S3ライフサイクル管理を使用して、オブジェクトをS3低頻度アクセスストレージに移行し、ストレージコストを削減します。 Amazon S3のデータにアクセスして、最近および過去のデータを分析する
Answer: C

NEW QUESTION: 3
A company has a High Performance Computing (HPC) cluster in its on-premises data center which runs thousands of jobs in parallel for one week every month, processing petabytes of images. The images are stored on a network file server, which is replicated to a disaster recovery site. The on-premises data center has reached capacity and has started to spread the jobs out over the course of month in order to better utilize the cluster, causing a delay in the job completion.
The company has asked its Solutions Architect to design a cost-effective solution on AWS to scale beyond the current capacity of 5,000 cores and 10 petabytes of data. The solution must require the least amount of management overhead and maintain the current level of durability.
Which solution will meet the company's requirements?
A. Submit the list of jobs to be processed to an Amazon SQS to queue the jobs that need to be processed. Create a diversified cluster of Amazon EC2 worker instances using Spot Fleet that will automatically scale based on the queue depth. Use Amazon EFS to store all the data sharing it across all instances in the cluster.
B. Store the raw data in Amazon S3, and use AWS Batch with Managed Compute Environments to create Spot Fleets. Submit jobs to AWS Batch Job Queues to pull down objects from Amazon S3 onto Amazon EBS volumes for temporary storage to be processed, and then write the results back to Amazon S3.
C. Create an Amazon EMR cluster with a combination of On Demand and Reserved Instance Task Nodes that will use Spark to pull data from Amazon S3. Use Amazon DynamoDB to maintain a list of jobs that need to be processed by the Amazon EMR cluster.
D. Create a container in the Amazon Elastic Container Registry with the executable file for the job.
Use Amazon ECS with Spot Fleet in Auto Scaling groups. Store the raw data in Amazon EBS SC1 volumes and write the output to Amazon S3.
Answer: C
Explanation:
A: EBS cannot store so much data.
C\D: Spot fleet are not guaranteed and hence not suitable. Batch is not well suited for Big data compared to EMR. EC2 is also not considered least management overhead.

NEW QUESTION: 4

グラフのバックログメトリックに基づいて、反復4の終わりのジャンプインポイントを説明できるものは何ですか？
A. チームは、以前に承認された作業が大幅に改善され、その作業に関連するストーリーポイントを追加できることを発見しました
B. 一部のストーリーは他の石に比べて過小評価され、必要に応じて再推定されていることにチームは気づきました
C. 製品所有者は次のリリースで出力を増やす必要があることをチームは学びました
D. サポートされている他の製品に関連するサポートとメンテナンスの費用をチームが考慮しなかった
Answer: C