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NEW QUESTION: 1
You have recently collected statistics on certain objects of a schema in your database. But you observe suboptimal execution plans for the queries on these objects after two days of statistics collection. The optimizer statistics retention period is set to its default value.
Which action would help to use the previous set of statistics on the objects?
A. Reduce the Automatic Workload Repository (AWR) retention period by 2 days.
B. Reduce the optimizer statistics retention period by 2 days.
C. Set the OPTIMIZER_PENDING_STATISTICS parameter to TRUE.
D. Restore statistics from statistics history.
Answer: D

NEW QUESTION: 2
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。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
このセクションの質問に回答すると、その質問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。
複数の列に欠損値を含む数値データセットを分析しています。
機能セットの次元に影響を与えることなく、適切な操作を使用して欠損値を消去する必要があります。
すべての値を含めるには、完全なデータセットを分析する必要があります。
解決策：連鎖方程式による多重代入（MICE）メソッドを使用して、各欠損値を置き換えます。
ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
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.
Note: Multivariate imputation by chained equations (MICE), sometimes called "fully conditional specification" or "sequential regression multiple imputation" has emerged in the statistical literature as one principled method of addressing missing data. Creating multiple imputations, as opposed to single imputations, accounts for the statistical uncertainty in the imputations. In addition, the chained equations approach is very flexible and can handle variables of varying types (e.g., continuous or binary) as well as complexities such as bounds or survey skip patterns.
References:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3074241/
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data

NEW QUESTION: 3

A. Depends on if it is in VPC or not
B. No
C. Yes
Answer: B

NEW QUESTION: 4
次の各ステートメントについて、ステートメントがtrueの場合は[はい]を選択します。それ以外の場合は、[いいえ]を選択します。
注：それぞれの正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Explanation:
ボックス1：はい
SAP Azure拡張監視拡張機能は、指定したAzureストレージアカウントにデータを格納するAzure診断拡張機能の上に構築されます。
ボックス2：はい
Set-AzVMAEMExtensionコマンドレットは、仮想マシンの構成を更新して、仮想マシンにインストールされているSAPシステムの監視のサポートを有効または更新します。コマンドレットは、パフォーマンスデータを収集してSAPシステムで検出可能にするAzure Enhanced Monitoring（AEM）拡張機能をインストールします。
-OSTypeはOSを指定します。 WindowsまたはLinuxのいずれか。
ボックス3：はい
参照：
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/diagnostics-extension-overview
https://docs.microsoft.com/en-us/powershell/module/az.compute/set-azvmaemextension