弊社のIT業で経験豊富な専門家たちが正確で、合理的なMicrosoft AB-100認証問題集を作り上げました。 弊社の勉強の商品を選んで、多くの時間とエネルギーを節約こともできます。
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
私たちのAB-100学習教材を使用した人々は、私たちのAB-100学習教材が非常にいいと考えていました。 あなたが私たちのAB-100学習教材を購入すれば、真剣に検討してみると、試験に合格するだけで、簡単にAB-100認定試験資格証明書を得ることができます。では、今すぐAB-100の学習教材で試してみてください。 私たちのAB-100学習教材を利用したら、後悔することはありません。
質問 # 33
A company has an Al agent that automates the review of customer feedback stored in a cloud database.
You plan to generate monthly reports from the agent's output to provide insights into customer sentiment and guide product development and marketing.
You need to ensure that the data ingested by the agent is clean and suitable for the intended use.
What should you do to prepare the data?
正解：B
解説：
The requirement is to make sure the data ingested by the agent is clean and suitable for the intended use, which is producing monthly sentiment insights to guide product development and marketing.
The best answer is C. Identify and address biased data.
Why C is correct:
For sentiment analysis and reporting, biased data can distort conclusions and produce misleading recommendations Data preparation should include checking for skew, unfair representation, missing segments, and other quality issues that affect downstream decisions This aligns with responsible AI and sound analytics practice
質問 # 34
A company is designing a Microsoft Power Platform solution to reduce the manual steps of a business process by deploying an existing Al model. You need to calculate the return on Al investment (ROAI) by identifying the metadata and telemetry of the solution. What should you use?
正解：C
解説：
The Business Value Toolkit (part of Microsoft's Power Platform and AI transformation guidance) is the only option that:
* Helps calculate Return on AI Investment (ROAI)
* Uses metadata, telemetry, and usage analytics
* Provides structured templates for value tracking , effort reduction , automation impact , and financial justification It is explicitly designed to quantify the business impact of AI and automation solutions.
質問 # 35
A company has a Microsoft Copilot Studio prompt-and-response agent.
You need to ensure that the agent meets the following requirements:
Provides effective and relevant responses
Provides conversational outcomes
Which metric should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Provides effective and relevant responses # Generated answer rate and quality Provides conversational outcomes # Topics by outcome Why "Generated answer rate and quality" is correct The requirement says the agent must provide effective and relevant responses. In Microsoft Copilot Studio, the metric that most directly evaluates whether the agent is successfully generating useful answers is Generated answer rate and quality.
This metric helps assess whether the prompt-and-response agent is:
returning answers consistently
producing responses that are useful
generating content of acceptable quality
handling user requests with enough relevance
From an AI business solutions perspective, response effectiveness is not just about whether the agent says something. It is about whether the generated output is meaningful, accurate enough for the scenario, and valuable to the user. That is exactly what generated answer rate and quality is designed to measure.
This metric is especially important in prompt-and-response solutions because these agents depend heavily on the quality of generated outputs rather than only predefined topic flows.
Why "Topics by outcome" is correct
The second requirement says the agent must provide conversational outcomes. The best metric for understanding whether conversations are reaching meaningful end states is Topics by outcome.
This metric helps evaluate what happens to conversations, such as whether they:
are resolved successfully
escalate
fail
abandon
complete a desired path
In enterprise AI and conversational business solutions, outcomes matter because stakeholders want to know whether the agent is actually driving the intended business result, not just generating text. A conversation can sound good but still fail operationally. Topics by outcome reveals whether the conversation reached a useful business conclusion.
For example, in a support or business-process scenario, leadership often wants to know:
how many conversations were resolved
how many required escalation
which flows underperform
where users get stuck
That is outcome measurement, and this metric aligns directly with that requirement.
Why the other metrics are not the best fit
Reactions
Reactions can provide feedback signals such as likes or dislikes, but they are not the strongest primary metric for determining whether responses are effective and relevant at a system level.
Satisfaction
Satisfaction is useful as a user sentiment metric, but it does not directly measure conversational outcomes. A user may be satisfied with tone but still not complete the intended business process.
Tool use
Tool use measures whether tools or actions are invoked, but it does not directly tell you whether responses are effective or whether conversations ended in successful outcomes.
質問 # 36
A company has an AI solution that uses a Microsoft Copilot Studio agent.
You need to monitor the agent ' s performance. The solution must meet the following requirements:
Monitor the agent ' s telemetry in near-real-time (NRT).
Download transcripts of full conversations.
Monitor the agent ' s usage and performance.
What should you use for each requirement? To answer, drag the appropriate options to the correct requirements. Each option may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Monitor telemetry in NRT # Application Insights; Download transcripts of full conversations # Copilot Studio; Monitor usage and performance # Copilot Studio The correct mapping is:
Monitor the agent ' s telemetry in near-real-time (NRT) # Application Insights Download transcripts of full conversations # Copilot Studio Monitor the agent ' s usage and performance # Copilot Studio Why Application Insights is correct for NRT telemetry Application Insights is the right choice for near-real-time telemetry because it is built for operational monitoring of application events, traces, failures, latency, and runtime behavior.
For a Copilot Studio agent, Application Insights is used when you want fast visibility into:
request activity
errors and exceptions
latency trends
runtime traces
telemetry streaming for troubleshooting
From an AI business solutions perspective, this is essential for early detection of issues in production, especially when the agent supports customer or employee workflows.
Why Copilot Studio is correct for full conversation transcripts
Copilot Studio provides access to conversation/session-level analysis, including the ability to review and download full conversation transcripts.
This is the correct place to inspect:
what the user asked
how the agent responded
where the conversation failed
whether escalation occurred
what happened across the whole interaction
That makes it the best tool for transcript retrieval and investigation.
Why Copilot Studio is also correct for usage and performance
Copilot Studio includes built-in analytics for monitoring agent usage and performance, such as:
conversation volume
engagement
resolution trends
escalation behavior
answer quality and outcomes
This supports business-level performance monitoring and continuous improvement.
Why the other options are incorrect
Log Analytics
Log Analytics is useful for querying centralized logs, but it is not the best direct answer here for near-real- time Copilot telemetry or full conversation transcript download in this scenario.
Microsoft Power Apps
Power Apps is not the monitoring platform for Copilot Studio telemetry, transcripts, or usage/performance analytics.
Expert reasoning
Use this exam shortcut:
Near-real-time telemetry and operational tracing # Application Insights Conversation transcripts # Copilot Studio Agent usage and performance analytics # Copilot Studio
質問 # 37
A company has a Microsoft Power Platform solution that contains the following components:
* Microsoft Dataverse tables
* A Microsoft Power Bl workspace named WS1
* A canvas app named App1 that uses Dataverse
* A Power Bl semantic model that connects to Dataverse by using DirectQuery You plan to use generative Al to provide answers to queries based on a subset of corporate data. You need to ensure that the data is available as a grounding data source for Al systems. What should you do?
正解：A
解説：
The goal is to use generative AI to answer questions based on a subset of corporate data, and to ensure that this data is available as a grounding data source.
The solution includes:
Dataverse tables
a Power BI workspace
a canvas app
a Power BI semantic model using DirectQuery to Dataverse
The best action is D. Endorse the semantic model.
Why D is correct:
Endorsing a semantic model makes it a trusted, discoverable enterprise data asset It is the appropriate step when you want approved corporate data to be used reliably by downstream AI and analytics experiences It fits the requirement of exposing a curated subset of data as a grounding source rather than duplicating or manually exporting it Why the other options are not correct:
A). Export the semantic modelExporting does not make it a governed grounding source.
B). Share WS1Sharing the workspace grants access, but it does not establish the semantic model itself as the trusted data source for grounding.
C). Populate a Dataverse tableThe data already exists and is modeled through the semantic layer; creating another table is unnecessary for this requirement.
質問 # 38
......
MicrosoftのAB-100の初心者なので、悩んでいますか？ It-Passportsは君の困難を解決できます。It-Passportsの学習教材はいろいろな狙いを含まれていますし、カバー率が高いですから、初心者にしても簡単に身に付けられます。それを利用したら、君はMicrosoftのAB-100試験に合格する鍵を持つことができますし、今までも持っていない自信を持つこともできます。まだ何を待っているのでしょうか？
AB-100資格関連題: https://www.it-passports.com/AB-100.html