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NEW QUESTION: 1
Are the following execution methods of Stream operator?
A. Gather
B. Broadcast
C. Hashed
D. Sorted
Answer: A,B

NEW QUESTION: 2
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You create a table by running the following Transact-SQL statement:

You need to return normalized data for all customers that were added in the year 2014.
Which Transact-SQL statement should you run?
A：

B：

C：

D：

E：

F：

G：

H：

A. Option E
B. Option F
C. Option D
D. Option G
E. Option H
F. Option B
G. Option A
H. Option C
Answer: D
Explanation:
Explanation/Reference:
Explanation:
The following query searches for row versions for Employee row with EmployeeID = 1000 that were active at least for a portion of period between 1st January of 2014 and 1st January 2015 (including the upper boundary):
SELECT * FROM Employee
FOR SYSTEM_TIME
BETWEEN '2014-01-01 00:00:00.0000000' AND '2015-01-01 00:00:00.0000000' WHERE EmployeeID = 1000ORDER BY ValidFrom; References: https://msdn.microsoft.com/en-us/library/dn935015.aspx

NEW QUESTION: 3
企業のネットワーク管理者が大規模なデータリークを報告しました。侵害された1台のサーバーを使用して、いくつかの重要なアプリケーションサーバーからのデータを集約し、HTTPSを使用してインターネットに送信しました。調査の結果、先週はユーザーがログインしておらず、エンドポイント保護ソフトウェアは問題を報告していません。侵害されたサーバーがどこで情報を収集したかについての洞察を提供するBESTは次のうちどれですか？
A. すべてのサーバー通信を収集するために、ファイアウォールでパケットキャプチャをセットアップします。
B. 各サーバーのベースライン通信プロファイルに対してフローデータを確認します。
C. 失敗したログインや再起動されたサービスなどの異常なアクティビティを収集するようにサーバーログを構成します。
D. サーバーからの異常な通信のデータ損失防止ログを関連付けます。
Answer: B
Explanation:
Network logging tools such as Syslog, DNS, NetFlow, behavior analytics, IP reputation, honeypots, and DLP solutions provide visibility into the entire infrastructure. This visibility is important because signature-based systems are no longer sufficient for identifying the advanced attacker that relies heavily on custom malware and zero-day exploits. Having knowledge of each host's communications, protocols, and traffic volumes as well as the content of the data in question is key to identifying zero-day and APT (advance persistent threat) malware and agents.
Data intelligence allows forensic analysis to identify anomalous or suspicious communications by comparing suspected traffic patterns against normal data communication behavioral baselines.
Automated network intelligence and next-generation live forensics provide insight into network events and rely on analytical decisions based on known vs. unknown behavior taking place within a corporate network.