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NEW QUESTION: 1

A. Option C
B. Option A
C. Option B
D. Option D
Answer: A

NEW QUESTION: 2
セキュリティコンテキストでは、どのアクションが、コンプライアンスに対応するために取られることができますか？
A. 脆弱性を防ぐためのルールを実装します。
B. 修正する、または脆弱性を打ち消します。
C. 脆弱性を修正するために、セキュリティアプライアンスの製造元からの指示に従ってください。
D. 脆弱性の深刻度を低くします。
Answer: A
Explanation:
Explanation
In general, compliance means conforming to a rule, such as a specification, policy, standard or law.
Source: https://en.wikipedia.org/wiki/Regulatory_compliance

NEW QUESTION: 3
Ein Mitglied des Verwaltungsrates ist der Sponsor eines Projekts, das für die Organisation wichtig ist. Dieser Stakeholder hat viele andere Prioritäten und ist derzeit nicht an den Projektaktivitäten beteiligt. Wie sollte der Stakeholder an dem Projekt beteiligt sein?
A. Der Stakeholder muss über den Projektfortschritt informiert werden
B. Halten Sie die Stakeholder auf dem Laufenden und konsultieren Sie sie entsprechend ihren Bedürfnissen
C. Konsultieren Sie die Stakeholder und erhöhen Sie deren Interesse
D. Beziehen Sie die Stakeholder in Governance und Entscheidungsfindung ein
Answer: B

NEW QUESTION: 4
HOTSPOT
You are designing an Azure infrastructure to support an Azure Machine Learning solution that will have multiple phases. The solution must meet the following requirements:
* Securely query an on-premises database once a week to update product lists.
* Access the data without using a gateway.
* Orchestrate the separate phases.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: Azure App Service Hybrid Connections
With Hybrid Connections, Azure websites and mobile services can access on-premises resources as if they were located on the same private network. Application admins thus have the flexibility to simply lift-and-shift specific most front-end tiers to Azure with minimal configuration changes, extending their enterprise apps for hybrid scenarios.
IncorrectAnswer: The VPN connection solution both use gateways.
Box 2: Machine Learning pipelines
Typically when running machine learning algorithms, it involves a sequence of tasks including pre- processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and cleaning, extracting features, and training a classification model with cross-validation. Though there are many libraries we can use for each stage, connecting the dots is not as easy as it may look, especially with large-scale datasets. Most ML libraries are not designed for distributed computation or they do not provide native support for pipeline creation and tuning.
Box 3: Azure Databricks
References:
https://azure.microsoft.com/is-is/blog/hybrid-connections-preview/
https://databricks.com/glossary/what-are-ml-pipelines