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NEW QUESTION: 1

Customer_CRMSystem

Customer_HRSystem





A. Option C
B. Option F
C. Option G
D. Option E
E. Option B
F. Option D
G. Option A
H. Option H
Answer: D
Explanation:
UNION combines the results of two or more queries into a single result set that includes all the rows that belong to all queries in the union. The UNION operation is different from using joins that combine columns from two tables.

NEW QUESTION: 2
Which two of the following are valid routing rule actions? Each correct answer presents part of the solution.
A. Route to Queue
B. Send Email
C. Cancel Case
D. Assign to User/Team
Answer: B,D

NEW QUESTION: 3
Azure Machine Learning Studioを使用してデータセットを分析しています。
各機能列のp値と一意の値カウントを含む統計サマリーを生成する必要があります。
ユーザーはどちらのモジュールを使用できますか？それぞれの正解は完全な解決策を提示します。
注：それぞれの正しい選択には1ポイントの価値があります。
A. インジケーター値に変換
B. Pythonスクリプトの実行
C. カウントテーブルのエクスポート
D. データの要約
E. 線形相関の計算
Answer: C,E
Explanation:
The Export Count Table module is provided for backward compatibility with experiments that use the Build Count Table (deprecated) and Count Featurizer (deprecated) modules.
E: Summarize Data statistics are useful when you want to understand the characteristics of the complete dataset. For example, you might need to know:
How many missing values are there in each column?
How many unique values are there in a feature column?
What is the mean and standard deviation for each column?
The module calculates the important scores for each column, and returns a row of summary statistics for each variable (data column) provided as input.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-count-table
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/summarize-data