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NEW QUESTION: 1
You have a mix of FAS8200s and AFF A700s in your environment.
In this scenario, which two statements are true? (Choose two.)
A. Inline data compaction is disabled by default on FAS systems.
B. Inline aggregate-level deduplication is enabled by default on AFF systems.
C. Inline aggregate-level deduplication is enabled by default on FAS systems.
D. Inline data compaction is disabled by default on AFF systems.
Answer: A,B

NEW QUESTION: 2
暗号化されたAmazon Elastic Block Store（EBS）ボリュームに関して正しいのはどれですか？
2つの答えを選んでください
A. すべてのインスタンスタイプで利用可能
B. 共有ボリュームを暗号化できます
C. すべてのAmazon EBSボリュームタイプでサポートされています
D. 既存のボリュームを暗号化できます
E. スナップショットは自動的に暗号化されます
Answer: C,E
Explanation:
This feature is supported on all Amazon EBS volume types (General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic). You can access encrypted Amazon EBS volumes the same way you access existing volumes; encryption and decryption are handled transparently and they require no additional action from you, your Amazon EC2 instance, or your application. Snapshots of encrypted Amazon EBS volumes are automatically encrypted, and volumes that are created from encrypted Amazon EBS snapshots are also automatically encrypted. Reference:
http://docs.aws.amazon.com/kms/latest/developerguide/services-ebs.html

NEW QUESTION: 3
Your company has thousands of Internet-connected sensors.
You need to recommend a computing solution to perform a real-time analysis of the date generated by the sensors.
Which computing solution should you include in the recommendation?
A. Microsoft Azure Notification Hubs
B. Microsoft Azure Cognitive Services
C. Microsoft Azure Stream Analytics
D. Microsoft Azure HDInsight HBase cluster
Answer: D
Explanation:
Explanation/Reference:
Explanation:
HDInsight HBase is offered as a managed cluster that is integrated into the Azure environment. The clusters are configured to store data directly in Azure Storage or Azure Data Lake Store, which provides low latency and increased elasticity in performance and cost choices. This enables customers to build interactive websites that work with large datasets, to build services that store sensor and telemetry data from millions of end points, and to analyze this data with Hadoop jobs. HBase and Hadoop are good starting points for big data project in Azure; in particular, they can enable real-time applications to work with large datasets.
Reference:
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hbase-overview
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-introduction

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