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NEW QUESTION # 39
- For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Microsoft 365 Copilot can amplify existing data governance challenges.
The answer: Yes
Implementing Microsoft 365 Copilot reduces data management costs.
The answer: No
Microsoft 365 Copilot can help IT teams manage data risks.
The answer: Yes
Yes - Copilot relies on the permissions, sharing links, and content exposure that already exist in Microsoft
365. If an organization has oversharing (for example, broadly accessible SharePoint sites, poorly scoped Teams, unmanaged external sharing, or excessive access rights), Copilot can surface that content more easily through natural-language querying. In other words, Copilot doesn't create new permissions, but it can increase visibility of governance gaps and make the impact of weak information architecture more apparent.
No - It is not accurate to claim that implementing Copilot inherently reduces data management costs.
Adoption often requires up-front investment in data hygiene, sensitivity labeling, retention, permission cleanup, DLP, and change management. Some organizations may realize productivity gains or reduced effort over time, but "reduces costs" is not a guaranteed outcome and depends heavily on the current state of governance, the scale of remediation needed, and how Copilot is rolled out.
Yes - Copilot can support IT risk management when deployed with the right controls: identity and access governance, sensitivity labels, DLP policies, retention, auditing, and compliance tooling. Because Copilot operates within the Microsoft 365 security/compliance boundary and honors existing access controls, IT can apply centralized policies to reduce leakage risk and improve overall control of how organizational data is accessed and used.
NEW QUESTION # 40
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Yes
Yes - Microsoft 365 Copilot can amplify existing data governance challenges.
Microsoft 365 Copilot significantly amplifies existing data governance, security, and compliance challenges within organizations, primarily because it operates by accessing data based on a user's existing permissions. If an organization has weak data hygiene or "permission sprawl"- where employees have access to more information than necessary-Copilot can instantly surface sensitive, confidential, or obsolete data, making oversharing a critical, high-speed risk.
Box 2: Yes
Yes - Implementing Microsoft 365 Copilot reduces data management costs.
Implementing Microsoft 365 Copilot can significantly reduce data management and operational costs by streamlining workflows, automating routine tasks, and improving data hygiene.
Organizations, such as Kantar, have used it to reduce storage costs by identifying and archiving inactive data while enhancing the relevance of information Copilot accesses.
Box 3: Yes
Yes - Microsoft 365 Copilot can help IT teams manage data risks.
Microsoft 365 Copilot includes built-in security, privacy, and compliance capabilities that empower IT teams to manage data risks, particularly by enforcing existing data access policies and integrating with Microsoft Purview. It ensures that Copilot only accesses data that a user is authorized to view based on their existing Microsoft 365 permissions, thereby preventing unauthorized data exposure.
Reference:
https://securiti.ai/copilot-governance-best-practices
https://techcommunity.microsoft.com/blog/microsoft_365blog/kantar-reduces-storage-costs-with- microsoft-365-archive/4494597
https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-ai-security
NEW QUESTION # 41
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 42
In which scenario is Azure Machine Learning most likely to deliver strategic value for an organization?
Answer: C
Explanation:
Azure Machine Learning delivers the most strategic value when an organization needs to build, train, evaluate, and operationalize predictive models that improve decisions at scale. Option A is a classic predictive analytics use case: forecasting demand using historical sales across product categories. This typically involves time-series forecasting, feature engineering (seasonality, promotions, macro signals), model training
/validation, deployment, and continuous monitoring-exactly the lifecycle Azure Machine Learning is designed to support (ML pipelines, model management, deployment endpoints, and MLOps). Forecasting demand can materially improve inventory optimization, supply chain planning, and revenue outcomes, which is why it's strategic.
B (digitizing paper processes) is more aligned to workflow automation and document processing (often Document Intelligence + Power Automate), not primarily Azure ML. C is sentiment analysis, which can be solved with prebuilt language services and doesn't necessarily require custom ML training unless you need a highly specialized classifier. D (location-based personalization) is commonly rules-based or CRM/marketing automation; it may use AI, but it doesn't inherently require building a custom ML model-unless you're doing advanced propensity modeling.
NEW QUESTION # 43
Your company deploys an AI-powered loan approval solution that enables applicants to request an explanation as to why their loan application was denied.
Which Microsoft responsible AI principle is this an example of?
Answer: B
Explanation:
According to Microsoft's guidelines, transparency means that AI systems should be understandable, and users should be able to understand the system's decisions or recommendations. Providing an explanation for a loan denial allows applicants to understand how the AI arrived at its decision.
Reference:
https://www.linkedin.com/pulse/deep-dive-responsible-ai-digitalbricksai-typie
NEW QUESTION # 44
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