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NEW QUESTION: 1
A. Option A
B. Option D
C. Option C
D. Option B
Answer: D
NEW QUESTION: 2
通信会社は、顧客の解約を予測する必要があります（つまり、顧客がコンピューターを切り替えることを決定します）。同社には、毎月の消費パターン、顧客サービスへの電話、顧客が最終的にサービスを終了したかどうかなど、各顧客の履歴記録があります。このデータはすべてAmazon S3に保存されます。会社は、忠誠心を取り戻すために、どの顧客がすぐに解約する可能性があるかを知る必要があります。
これらの要件を満たす最適なアプローチは何ですか？
A. Redshiftクラスターを使用して、Amazon S3からデータをコピーします。解約の可能性をコンピューター化するユーザー定義関数をRedshiftで作成する
B. Amazon Machine Learningサービスを使用して、Amazon S3に保存されているデータセットに基づいてバイナリ分類モデルを構築します。モデルは、既存の顧客の解約属性を予測するために定期的に使用されます
C. AWS QuickSightを使用してAmazon S3に保存されたデータに接続し、必要なビジネス洞察を取得します。解約傾向グラフをプロットして、既存の顧客の解約可能性を推定します
D. EMRを使用してHiveクエリを実行し、顧客のプロファイルを作成します。プロファイルを既存の顧客に適用して、解約の可能性を判断する
Answer: B
Explanation:
説明
https://aws.amazon.com/blogs/machine-learning/predicting-customer-churn-with-amazon-machine-learning/
NEW QUESTION: 3
In CA Performance Center, groups are organized in the Groups Tree. Which features characterize the Groups Tree? (Choose two)
A. It is used when an administrator manages groups.
B. It includes the Defined Tenants sub-tree for groups in a tenant space.
C. Its root level is called the Root Group node.
D. It includes a sub-node in the Defined Tenants sub-tree for Default Space groups.
Answer: A,B
