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NEW QUESTION: 1
A company has an application that scans millions of connected devices for security threats and pushes the scan logs to an Amazon S3 bucket. A total of 70 GB of data is generated each week, and the company needs to store 3 years of data for historical reporting.
The company must process, aggregate, and enrich the data from Amazon S3 by performing complex analytical queries and joins in the least amount of time. The aggregated dataset is visualized on an Amazon QuickSight dashboard.
What should a solutions architect recommend to meet these requirements?
A. Use AWS Lambda functions based on S3 PutObject event triggers to copy the incremental changes to Amazon DynamoDB. Perform the aggregation queries on DynamoDB.
B. Use AWS Glue to catalog the data in Amazon S3. Perform the aggregation queries on the cataloged tables by using Amazon Athena. Query the data directly from Amazon S3.
C. Create and run an ETL job in AWS Glue to process the data from Amazon S3 and load it into Amazon Redshift. Perform the aggregation queries on Amazon Redshift.
D. Use AWS Lambda functions based on S3 PutObject event triggers to copy the incremental changes to Amazon Aurora MySQL Perform the aggregation queries on Aurora MySQL
Answer: C
NEW QUESTION: 2
To ensure that the Preferred Name field is always filled, you have created a rule to copy the First Name field to the Preferred Name field if the user leaves the Preferred Name field blank.
What changes do you make to the Succession Data Model to define the trigger rules?
A. <hris-element id="personalInfo"> <label>Personal Information</label> <trigger-rule event="onInit" rule="CopyName"/>
B. <hris-element id="personalInfo"> <label>Personal Information</label> <trigger-rule event="onSave" rule="CopyName"/>
C. <hris-field id="preferred-name" visibility="both"> <label>Preferred Name</label> <trigger-rule event="onInit" rule="CopyName"/>
D. <hris-field id="first-name" visibility="both" required="true"> <label>Legal First Name</label> <trigger-rule event="onSave" rule="CopyName"/>
Answer: B
NEW QUESTION: 3
Statement 1: An ICT infrastructure should be built with high end equipment and be located in one site.
Statement 2: A server is a rackmounted enterprise version of a desktop computer and typically has more than one hard disk installed.
A. Statement 1 and statement 2 are both True
B. Statement 1 and statement 2 are both false
C. Statement 1 is false; statement 2 is true
D. Statement 1 is true; statement 2 is false
Answer: C
NEW QUESTION: 4
Azureでソリューションを管理します。
解決策はうまく機能していません。
パフォーマンスの問題の原因を特定するためのツールを推奨する必要があります。
何をお勧めですか？ 答えるには、適切なモニタリングソリューションを正しいシナリオにドラッグします。
各監視ソリューションは、1回、複数回、またはまったく使用しないことができます。 コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要があります。
注：それぞれ正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: Azure Monitor
Metrics in Azure Monitor are stored in a time-series database which is optimized for analyzing time-stamped data. This makes metrics particularly suited for alerting and fast detection of issues.
Box 2: Azure Log Analytics
Log data collected by Azure Monitor is stored in a Log Analytics workspace, which is based on Azure Data Explorer. Logs in Azure Monitor are especially useful for performing complex analysis across data from a variety of sources.
Box 3: Azure Log Analytics
References:
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/data-platform
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/data-platform-logs