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NEW QUESTION: 1
Which three statements are true regarding persistent lightweight jobs? (Choose three.)
A. The use of a template is mandatory to create persistent lightweight jobs.
B. Persistent lightweight jobs modify several tables in the data dictionary to generate a lot of redo.
C. The user cannot set privileges on persistent lightweight jobs.
D. Persistent lightweight jobs are useful when users need to create a small number of jobs that run infrequently.
E. Persistent lightweight jobs are useful when users need to create a large number of jobs in a short time.
Answer: A,C,E
Explanation:
Topic 20, Globalization

NEW QUESTION: 2
Sie haben ein Azure-Abonnement mit dem Namen Abonnement1.
Sie haben eine Virtualisierungsumgebung, die die Virtualisierungsserver in der folgenden Tabelle enthält.

Die virtuellen Maschinen werden wie in der folgenden Tabelle gezeigt konfiguriert.

Alle virtuellen Maschinen verwenden Basisdatenträger. VM1 ist mithilfe der BitLocker-Laufwerkverschlüsselung (BitLocker) geschützt.
Sie möchten Azure Site Recovery verwenden, um die virtuellen Maschinen nach Azure zu migrieren.
Welche virtuellen Maschinen können Sie migrieren? Wählen Sie zum Beantworten die entsprechenden Optionen im Antwortbereich aus.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.

Answer:
Explanation:

Explanation

References:
https://docs.microsoft.com/en-us/azure/site-recovery/hyper-v-azure-support-matrix#azure-vm-requirements

NEW QUESTION: 3
You need to replace the missing data in the AccessibilityToHighway columns.
How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Replace using MICE
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or "Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Scenario: The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.
Box 2: Propagate
Cols with all missing values indicate if columns of all missing values should be preserved in the output.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

NEW QUESTION: 4
予測でクォータをインポートする方法2を選択
A. インポートウィザードの使用
B. ユーザー情報/レコード関連リスト
C. 予測タブの使用
D. CHangesetの使用
E. データローダーとAPI
Answer: B,E

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