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NEW QUESTION: 1
次の3つのバージョンのAzureSQLデータベースがあります。
*テスト
*生産
*開発
開発データベースをデータソースとして使用するデータセットがあります。
powerbi.comから開発、テスト、本番データベースサーバー間でデータソースを簡単に変更できるように、データセットを構成する必要があります。
あなたはどちらをすべきですか？
A. データベースサーバー名を含むJSONファイルを作成します。 JSONファイルをデータセットにインポートします。
B. データベースサーバーごとにクエリを作成し、開発テーブルを非表示にします。
C. データソースのプライバシーレベルを組織に設定し、ReplaceValue Power QueryM関数を使用します。
D. パラメータを作成し、そのパラメータを使用するようにクエリを更新します。
Answer: C
Explanation:
Explanation
With privacy level settings, you can specify an isolation level that defines the degree that one data source must be isolated from other data sources.
An Organizational data source limits the visibility of a data source to a trusted group of people. An Organizational data source is isolated from all Public data sources, but is visible to other Organizational data sources.
Reference:
https://docs.microsoft.com/en-us/power-bi/admin/desktop-privacy-levels
NEW QUESTION: 2
A. Option B
B. Option D
C. Option C
D. Option A
Answer: A
Explanation:
A virtual fibre channel SAN will group physical HBA ports together so that you can add a
virtual fibre channel adapter to a virtual machine that can be connected to a virtual SAN.
NEW QUESTION: 3
注：この質問は同じシナリオを提示する一連の質問の一部です。連載の各質問には、記載されている目標を達成できる可能性のある固有の解決策が含まれています。他の人が正しい解決策を持っていないかもしれない間、いくつかの質問セットは複数の正しい解決策を持つかもしれません。
このシナリオで質問に答えた後は、それに戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
あなたの会社はMicrosoft 365サブスクリプションを持っています。
同社の財務部門の何人かのユーザーは最近、電子メールメッセージ内のリンクをクリックして危険なWebサイトにアクセスしています。
同社のマーケティング部門のユーザーは、電子メールメッセージに埋め込まれているすべてのリンクにアクセスできる必要があると報告しています。
財務部のユーザーが危険なWebサイトにアクセスする可能性を減らす必要があります。解決策は財務部門のユーザーのみに影響を与える必要があります。
解決方法：新しいセーフリンクポリシーを作成します。
これは目標を達成していますか？
A. いいえ
B. はい
Answer: A
Explanation:
説明
参考文献：
https://blog.netwrix.com/2019/01/24/make-the-most-of-exchange-online-advanced-threat-protection/
NEW QUESTION: 4
会社のデータエンジニアリングソリューションを開発します。
プロジェクトでは、リアルタイムのTwitterフィードの分析が必要です。特定のキーワードを含む投稿は、Microsoft Azureで保存および処理され、Microsoft Power BIを使用して表示される必要があります。ソリューションを実装する必要があります。
どの5つのアクションを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。
Answer:
Explanation:
Explanation
Step 1: Create an HDInisght cluster with the Spark cluster type
Step 2: Create a Jyputer Notebook
Step 3: Create a table
The Jupyter Notebook that you created in the previous step includes code to create an hvac table.
Step 4: Run a job that uses the Spark Streaming API to ingest data from Twitter Step 5: Load the hvac table into Power BI Desktop You use Power BI to create visualizations, reports, and dashboards from the Spark cluster data.
References:
https://acadgild.com/blog/streaming-twitter-data-using-spark
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-use-with-data-lake-store
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