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NEW QUESTION: 1
Ihr Netzwerk enthält eine Active Directory-Domäne mit dem Namen contoso.com.
Einige Benutzerkonten in der Domäne verfügen über die Postfachadresse. Box Attribut gesetzt.
Sie planen, den Wert des Postfachs zu entfernen. Feldattribut für alle Benutzer mithilfe von Ldifde.
Sie haben einen Benutzer mit dem Namen Benutzer1, der sich im Container Benutzer befindet.
Wie sollten Sie die LDIF-Datei konfigurieren, um den Wert des Postfachs zu entfernen? Boxattribut für Benutzer1? Wählen Sie zum Beantworten die entsprechenden Optionen im Antwortbereich aus.
Answer:
Explanation:
Explanation
NEW QUESTION: 2
マルチテナントコンテナデータベース(CDB)のCDB $ ROOTで、共通のユーザーC ## A_ADMINを作成して、次のコマンドを実行します。
どちらの陳述が正しい?
A. システム特権が共通のユーザーに付与されないため、コマンドは失敗します。
B. コマンドは正常に実行され、C ## A_ADMINユーザーは、プラッガブル・データベース(PDB)と同様にルート・データベースに表領域を作成できます。
C. CONTAINER句が使用されていないため、コマンドは失敗します。
D. コマンドは正常に実行され、C ## A_ADMINユーザーはルートデータベースにのみ表領域を作成できます。
Answer: D
NEW QUESTION: 3
Which is a key benefit of using oracle cloud infrastructure autonomous data warehouse?
A. Maintain root level acress to the underlying operating system
B. Scale both CPU and Storage without downtime
C. Apply database patches as they become available
D. No username and password required
Answer: B
Explanation:
Explanation
Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse and securing data. It automates provisioning, configuring, securing, tuning, scaling, patching, backing up, and repairing of the data warehouse. Unlike other "fully managed" cloud data warehouse solutions that only patch and update the service, it also features elastic, automated scaling, performance tuning, security, and a broad set of built-in capabilities that enable machine learning analysis, simple data loading, and data visualizations.
Data Warehouse uses continuous query optimization, table indexing, data summaries, and auto-tuning to ensure consistent high performance even as data volume and number of users grows. Autonomous scaling can temporarily increase compute and I/O by a factor of three to maintain performance. Unlike other cloud services which require downtime to scale, Autonomous Data Warehouse scales while the service continues to run.