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NEW QUESTION: 1

A. Option B
B. Option A
Answer: B

NEW QUESTION: 2
実際のデータを暗号化せずに、エンティティ認証、データの整合性、および通信の信頼性を検証できる方法は次のうちどれですか？
A. 両方の当事者は、メッセージに付随するデータの認証済みMD5ハッシュ値を計算します。一方の当事者は秘密鍵を使用し、他方の当事者は公開鍵を使用します。
B. 両当事者は、メッセージの送信の前後にデータのCRC32を計算します。
C. 両当事者は、メッセージの送信の前後にXORと既知のキーでデータを難読化します。
D. 通信の両当事者は、同じ秘密鍵を使用して、メッセージに付随するメッセージ認証コードを生成します。
Answer: D

NEW QUESTION: 3
You are designing a solution for a company. The solution will use model training for objective classification.
You need to design the solution.
What should you recommend?
A. Power BI models
B. a Spark Streaming job
C. interactive Spark queries
D. an Azure Cognitive Services application
E. a Spark application that uses Spark MLib.
Answer: E
Explanation:
Spark in SQL Server big data cluster enables AI and machine learning.
You can use Apache Spark MLlib to create a machine learning application to do simple predictive analysis on an open dataset.
MLlib is a core Spark library that provides many utilities useful for machine learning tasks, including utilities that are suitable for:
* Classification
* Regression
* Clustering
* Topic modeling
* Singular value decomposition (SVD) and principal component analysis (PCA)
* Hypothesis testing and calculating sample statistics
References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython