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NEW QUESTION: 1
Welcher der folgenden Paneltypen würde den THINNEST möglichen Anzeigemonitor zulassen?
A. LED
B. DLP
C. CRT
D. Plasma
Answer: A

NEW QUESTION: 2
Which of the following is not a characteristic of the Project Life Cycle?
A. Cost and staffing levels are low at the start, higher towards the end and drop rapidly as the project draws to a conclusion.
B. Risk and uncertainty is highest at start of the project.
C. Ability of the stakeholders to influence final characteristics of the projects product increases as the project continues.
D. The project life cycle definition determines which transitional actions at the beginning and end of the project are included - so, the project life cycle definition can be a link to the ongoing operations of the performing organization.
Answer: C

NEW QUESTION: 3
会社は、数ペタバイトのデータセットをクラウドに移行することを計画しています。データセットは24時間利用可能でなければなりません。ビジネスアナリストは、SQLインターフェイスを使用した経験しかありません。分析を容易にするために、データをどのように保存して最適化する必要がありますか？
A. データをGoogle Cloud Datastoreにストリーミングします。
B. データをGoogle BigQueryにロードします。
C. データをGoogle Cloud SQLに挿入します。
D. フラットファイルをGoogle Cloud Storageに配置します。
Answer: B
Explanation:
説明
Google Big Queryは、マルチペタバイトストレージ、HA（高可用性）、つまり24時間、SQLインターフェイス用です
。
https://medium.com/google-cloud/the-12-components-of-google-bigquery-c2b49829a7c7
https://cloud.google.com/solutions/bigquery-data-warehouse
https://cloud.google.com/bigquery/
BigQueryは、すべてのデータアナリストの生産性を高めるように設計された、Googleのサーバーレスで拡張性の高い低コストのエンタープライズデータウェアハウスです。管理するインフラストラクチャがないため、使い慣れたSQLを使用してデータの分析に集中して有意義な洞察を見つけることができ、データベース管理者は必要ありません。
BigQueryを使用すると、オブジェクトストレージやスプレッドシートからのデータだけでなく、管理された円柱状のストレージ上に論理データウェアハウスを作成することにより、すべてのデータを分析できます。
参照：https://cloud.google.com/bigquery/