Microsoft AB-100 Exam Dumps - Actual Questions Answers

" Computer use is a tool in Copilot Studio that lets your agent interact with and automate tasks on a Windows computer. It works with websites and desktop apps by selecting buttons, choosing menus, and entering text into fields on the screen. Describe in natural language what you want computer use to do, and it performs the task on a computer you set up by using a virtual mouse and keyboard. By using computer use, agents can complete tasks even when there ' s no API to connect directly to the system. If a person can use an app or website, computer use can too. You can use computer use for tasks like automated data entry, invoice processing, and data extraction. " Reference: https://learn.microsoft.com/en-us/microsoft-copilot-studio/computer-use

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

Why the other options are not correct:

A. Ensure that the size of the database does not exceed 100 GB is unrelated to data quality or suitability

B. Translate the data into a single language might help in some implementations, but it is not universally required and is not the primary data-quality action here

D. Sort the database by customer last name has no relevance to model readiness or report quality

In a proper ALM deployment for Microsoft Copilot Studio across development, staging, and production, you should package the agent in a way that is portable across environments while avoiding hardcoded endpoints, indexes, table targets, or credentials.

Here, Agent1 uses:

a Dataverse table: CustomerOrders

an Azure AI Search index: customer-knowledge

Because each environment has its own Dataverse tables and Azure AI Search index, the deployment package should not carry over the development environment’s live connections as fixed production settings. Instead, it should carry the agent and the references needed so the target environment can bind to its own production resources.

That is why the correct recommendation is:

Deployment package: Agent1 and references to the data sources

After deployment: Reconfigure the environment variables

Why this is correct:

Environment variables are the standard ALM-friendly way to externalize settings like:

endpoints

index names

table references

connection-related values

This supports secure handling of credentials and endpoints

It also helps minimize downtime, because production values can be switched cleanly after import without rebuilding the agent

Why the other choices are weaker:

Agent1 only would omit needed source references

The data sources only would not deploy the actual agent

Agent1 and the data source connections risks carrying environment-specific connection bindings

Agent1, the data sources, and the data source connections is too tightly coupled to the source environment and is not the best ALM design for secure cross-environment deployment

Reconfiguring only Dataverse or only Azure AI Search is incomplete because both can vary by environment

Reconfiguring Agent1 configuration is broader and less precise than using environment variables