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NEW QUESTION: 1
FIUが他のFIUにとって有用な情報を持っている場合、FIUはどのアクションを検討すべきですか？
A. ヴォルフスブルクのガイドラインに従って、書面で他のFIUに情報を送信します
B. 情報の共有の関連性が確認されるとすぐに、他のFIUに自発的に情報を提供します
C. 他のFIUから連絡されるまで何もしません
D. 他のFIUと情報を共有する前に、エグモントグループに承認を要求します
Answer: B
NEW QUESTION: 2
Which of the following statements pertaining to packet switching is incorrect?
A. Messages are divided into packets.
B. All packets from a message travel through the same route.
C. Each network node or point examines each packet for routing.
D. Most data sent today uses digital signals over network employing packet switching.
Answer: B
Explanation:
When using packet switching, messages are broken down into packets. Source and destination address are added to each packet so that when passing through a network node, they can be examined and eventually rerouted through different paths as conditions change. All message packets may travel different paths and not arrive in the same order as sent. Packets need to be collected and reassembled into the original message at destination.
Source: TIPTON, Hal, (ISC)2, Introduction to the CISSP Exam presentation.
NEW QUESTION: 3
What is Administration Console for Content Platform Engine (ACCE) replacing?
A. FileNet Enterprise Manager
B. System Manager
C. Deployment Manager
D. Configuration Manager
Answer: A
NEW QUESTION: 4
What are two of the benefits of using denormalized data structures in BigQuery?
A. Reduces the amount of data processed, increases query speed
B. Increases query speed, makes queries simpler
C. Reduces the amount of data processed, reduces the amount of storage required
D. Reduces the amount of storage required, increases query speed
Answer: B
Explanation:
Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data structure, you don't have to use JOINs, since all of the data has been combined into one table. Denormalization also makes queries simpler because you do not have to use JOIN clauses. Denormalization increases the amount of data processed and the amount of storage required because it creates redundant data.
https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data