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NEW QUESTION: 1
You are designing a solution based on the lambda architecture.
You need to recommend which technology to use for the serving layer.
What should you recommend?
A. Kafka
B. Microsoft Azure DocumentDB
C. Apache Storm
D. Apache Hadoop
Answer: A

NEW QUESTION: 2
ユーザーは、VPCウィザードを使用して、プライベートサブネットとVPN接続のみを持つCIDR 20.0.0.0/16でVPCを作成しました。ユーザーは、SSH経由でプライベートサブネットのインスタンスに接続したいと考えています。ユーザーはSSHのセキュリティルールをどのように定義する必要がありますか?
A. ユーザーのネットワークからのポート22での受信トラフィックを許可します
B. ユーザーはNATインスタンスを使用してプライベートサブネット内のインスタンスに接続できます
C. ユーザーはEC2 ClassicでエラスティックIPを使用してインスタンスを作成し、そのエラスティックIPからのSSHを許可するようにプライベートサブネットのセキュリティグループを構成する必要があります
D. ユーザーがインターネット経由でプライベートサブネットに接続できるように、ポート80および22で受信トラフィックを許可します
Answer: A
Explanation:
説明
ユーザーはVPC内の要件に従ってサブネットを作成できます。ユーザーが自分のデータセンターからVPCに接続したい場合、ユーザーはVPNのみのサブネット(プライベート。VPNアクセスを使用してデータセンターに接続することでケースをセットアップできます。ユーザーがウィザードでこのセットアップを構成すると、すべてのネットワークサブネット内のインスタンスへの接続は、データセンターから行われます。ユーザーは、SSHでのインバウンドトラフィックを許可するプライベートサブネットのセキュリティグループを構成する必要があります(データセンターのネットワーク範囲からのポート22。

NEW QUESTION: 3
Which of the following types of data would fall under data rights management (DRM) rather than information rights management (IRM)?
A. Personnel data
B. Financial records
C. Security profiles
D. Publications
Answer: D
Explanation:
Whereas IRM is used to protect a broad range of data, DRM is focused specifically on the protection of consumer media, such as publications, music, movies, and so on. IRM is used to protect general institution data, so financial records, personnel data, and security profiles would all fall under the auspices of IRM.

NEW QUESTION: 4
The client is trying to create a SAQL step to predict sales in each sales region. They cannot get the query to return any results, but have identified that the error is in the time series statement. They have asked an Einstein Consultant to review the following query and fix any errors.

Which timeseries statement will fix the query'
A. q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year',
'Date_Month". "Y-M"), partition='Region');
B. q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter',
"Y-Q"), partition='Region', seasonality=4);
C. q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter',
"Y-Q"), partition=Region', ignoreLast=true);
D. q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter',
"Y-Q"), partition='Region');
Answer: A