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NEW QUESTION: 1
あなたは、Azure Synapse Analyticsでエンタープライズデータウェアハウスを設計しています。このエンタープライズデータウェアハウスは、ウェブサイトのトラフィック分析をスタースキーマに格納します。
あなたはウェブサイト訪問のためのファクトテーブルを持つことを計画しています。テーブルは約5 GBになります。
テーブルに使用する分散タイプとインデックスタイプを推奨する必要があります。ソリューションは、最速のクエリパフォーマンスを提供する必要があります。
何を勧めますか？回答するには、回答領域で適切なオプションを選択してください注：正しい選択はそれぞれ1点の価値があります。

Answer:
Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-index

NEW QUESTION: 2
In the FATF 40 recommendations, the focus of AML efforts has been expanded beyond Financial Institutions. Which three businesses and/or professions are covered? Choose 3 answers
A. casinos, when customers engage in financial transactions equal to or above a designated Threshold
B. Dealers in art, when they engage in any cash transaction with a customer at or above a designated threshold
C. Trust and company service providers
D. Real estate agents when they are involved in transactions for clients concerning buying and selling properties
Answer: B,C,D

NEW QUESTION: 3
指定された各項目について、ドロップダウンの選択肢から適切な認証カテゴリを選択します。
次の項目に適切な認証タイプを選択します。

Answer:
Explanation:

NEW QUESTION: 4
You have a model with a large difference between the training and validation error values.
You must create a new model and perform cross-validation.
You need to identify a parameter set for the new model using Azure Machine Learning Studio.
Which module you should use for each step? To answer, drag the appropriate modules to the correct steps. Each module may be used once or more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Split data
Box 2: Partition and Sample
Box 3: Two-Class Boosted Decision Tree
Box 4: Tune Model Hyperparameters
Integrated train and tune: You configure a set of parameters to use, and then let the module iterate over multiple combinations, measuring accuracy until it finds a "best" model. With most learner modules, you can choose which parameters should be changed during the training process, and which should remain fixed.
We recommend that you use Cross-Validate Model to establish the goodness of the model given the specified parameters. Use Tune Model Hyperparameters to identify the optimal parameters.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/partition-and-sample