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NEW QUESTION: 1
クラウドコンピューティングが資本コストを変動コストにシフトするのはなぜですか？
A. サーバーの利用効率が向上
B. スタッフは顧客に雇用されなくなりました
C. IT資産は顧客が所有していません
D. クラウドコンピューティングの方が費用効率が高い
Answer: C

NEW QUESTION: 2
展示を表示し、CUSTOMERSテーブルの説明を調べます。

CUST_ID 2360の顧客のCUST_INCOME_LEVELおよびCUST_CREDIT_LIMIT列を更新します。CUST_INCOME_LEVELの値は、CUST_ID 2560の顧客と同じ値にし、CUST_CREDIT_LIMITは、CUST_CREDIT_LIMITと同じ値にします。 CUST_IDの顧客
2566。
どのUPDATEステートメントがタスクを実行しますか？
A. UPDATE customersSET (cust_income_level, cust_credit_limit)
(SELECTcust_income_level, cust_credit_limitFROM customersWHERE cust_id=2560 OR cust_id=2566)WHERE cust_id=2360;
B. UPDATE customersSET (cust_income_level, cust_credit_limit)
(SELECTcust_income_level, cust_credit_limitFROM customersWHERE cust_id IN(2560,
2 566)WHERE cust_id=2360;
C. UPDATE customersSET cust_income_level = (SELECT cust_income_levelFROM customersWHERE cust_id = 2560),cust_credit_limit = (SELECT cust_credit_limitFROM customersWHERE cust_id = 2566)WHERE cust_id=2360;
D. UPDATE customersSET (cust_income_level, cust_credit_limit)
(SELECTcust_income_level, cust_credit_limitFROM customersWHERE cust_id=2560 AND cust_id=2566)WHERE cust_id=2360;
Answer: C
Explanation:
Updating Two Columns with a Subquery
You can update multiple columns in the SET clause of an UPDATE statement by writing multiple subqueries. The syntax is as follows:
UPDATE table
SET column
(SELECT column
FROM table
WHERE condition)
[ ,
column
(SELECT column
FROM table
WHERE condition)]
[WHERE condition ] ;

NEW QUESTION: 3
A ClearPass deployment needs to be designed to determine which department the employee is in on the Active Directory Server and whether the user's device is a computer or smart device.
Which Policy Manager components will the network administrator need to use? (Choose three.)
A. Authentication
B. Authorization
C. Enforcement
D. Posture
E. Profiler
F. Onboard
Answer: A,E,F

NEW QUESTION: 4
ソリューションアーキテクトは、顧客の活動に関するデータを保存するAmazon DynamoDBテーブルを設計する必要があります。このデータは、最近の顧客の行動を分析するために使用されるため、1週間以内のデータは頻繁にアクセスされ、古いデータはまれにしかアクセスされません。 1か月以上前のデータをアプリケーションで参照する必要はありませんが、年末の分析のためにアーカイブする必要があります。
これらの要件を満たす最もコスト効率の高い方法は何ですか？ （2つ選択してください。）
A. 各週のデータに対して個別のテーブルを作成し、現在の週のスループットを高めます。
B. データを前処理して複数のレコードを統合し、書き込み操作を最小限にします。
C. より高い書き込み容量ユニットをプロビジョニングして、パーティションの数を最小限にします。
D. DynamoDBの有効期間設定を使用して、特定の期間後にアイテムを期限切れにします。
E. AWS Data Pipelineを使用して、DynamoDBからAmazon S3に古いテーブルデータをエクスポートし、古いテーブルを削除します。
Answer: A,E
Explanation:
AWS Data Pipeline is a web service that you can use to automate the movement and transformation of data. With AWS Data Pipeline, you can define data-driven workflows, so that tasks can be dependent on the successful completion of previous tasks. You define the parameters of your data transformations and AWS Data Pipeline enforces the logic that you've set up.
https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/what-is-datapipeline.html
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/best-practices.html