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NEW QUESTION: 1
A business analyst (BA) elicits requirements for the sales order processing of multiple product lines. Elicitation reveals that the business processes for the sales orders of most products follow similar activity patterns that have been established over a number of years. Some of the new proposed seasonal products, however, will necessitate major variations in the process flow of some departments. The seasonal products are likely to be different every year. The business needs to carefully adapt its business practices so that the significant but seasonal variations in some of the business processes for the new products are handled adequately without disrupting the processes for the other established products.
Which of the following approaches must the BA take to manage the requirements for sales order processing in the long term?
A. Reference specific departments in the requirements for the established products
B. Reference specific departments in the requirements for the seasonal products
C. Use a high level of abstraction for the seasonal products to make them less subject to revision during a change
D. Use a high level of abstraction for the established products to make them less subject to revision during a change
Answer: D
NEW QUESTION: 2
ネットワークにcontoso.comという名前のActive Directoryドメインが含まれています。 ドメインには、Windows Server 2016を実行するHyper-VホストServer1が含まれています。
Server1はドメインのメンバーである4台のマシンをホストします。 仮想マシンは、次の表に示すように構成されています。
PowerShell Directを使用して管理できる仮想マシンはどれですか？
A. only VM4
B. Only VM2
C. VM1, VM2, and VM3
D. VM1, VM2, and VM4
Answer: D
Explanation:
Explanation
https://www.iperiusbackup.net/en/powershell-direct-a-new-way-to-manage-your-vm/
NEW QUESTION: 3
A transportation company uses IoT sensors attached to trucks to collect vehicle data for its global delivery fleet. The company currently sends the sensor data in small .csv files to Amazon S3. The files are then loaded into a 10-node Amazon Redshift cluster with two slices per node and queried using both Amazon Athena and Amazon Redshift. The company wants to optimize the files to reduce the cost of querying and also improve the speed of data loading into the Amazon Redshift cluster.
Which solution meets these requirements?
A. Use AWS Glue to convert all the files from .csv to a single large Apache Parquet file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.
B. Use AWS Glue to convert the files from .csv to a single large Apache ORC file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.
C. Use Amazon EMR to convert each .csv file to Apache Avro. COPY the files into Amazon Redshift and query the file with Athena from Amazon S3.
D. Use AWS Glue to convert the files from .csv to Apache Parquet to create 20 Parquet files. COPY the files into Amazon Redshift and query the files with Athena from Amazon S3.
Answer: D
NEW QUESTION: 4
組織がELBでAuto Scalingを設定しています。インスタンスのヘルスチェックの1つは、Auto Scalingに障害としてステータスを返します。このシナリオでAuto Scalingは何をしますか？
A. インスタンスが失敗したことを宣言する前に、クールダウンするまでヘルスチェックを実行します
B. SNSを使用して失敗状態をユーザーに通知します
C. 障害のあるインスタンスへのトラフィックの送信を停止するようにELBに通知します
D. インスタンスを終了し、新しいインスタンスを起動します
Answer: D
Explanation:
Explanation
The Auto Scaling group determines the health state of each instance periodically by checking the results of the Amazon EC2 instance status checks. If the instance status description shows any other state other than
"running" or the system status description shows impaired, Auto Scaling considers the instance to be unhealthy. Thus, it terminates the instance and launches a replacement.