Microsoft AI-102 Exam With Confidence Using Practice Dumps

a tabular form of rows and columns

Relational data is, by definition, data that adheres to the relational model.

In the relational model, data is organized into tables, which consist of rows (records or tuples) and columns (fields or attributes). This is known as the tabular form.

The other options are incorrect:

Unstructured data is the opposite of relational data.

A hierarchical folder structure is used for file organization, not the logical structure of relational data.

Comma-separated value (CSV) files can contain relational data, but the core definition of relational data is the tabular structure, not the file format itself.

Rationale

Data visualization’s primary purpose is to make data understandable and meaningful through visuals such as charts, dashboards, and graphs.

It helps to communicate significance (option A) and show patterns, correlations, and trends over time (option B).

C. Implement machine learning to predict future values → Not visualization, but rather ML/AI.

D. Enforce business logic across reports → Business logic is handled in data modeling or ETL, not visualization.

Correct Answers: A and B

Comprehensive Detailed ExplanationThe question focuses on monitoring a public-facing sales system that processes video and text, ensuring that the system provides equitable results regardless of user location or background.

Two Microsoft Responsible AI principles apply directly here:

Fairness

AI systems should treat all people fairly and avoid bias.

Monitoring ensures that outcomes do not disadvantage people based on location, background, or demographics.

This directly addresses the requirement for equitable results.

Inclusiveness

AI systems should empower everyone and engage people of all backgrounds.

Monitoring for inclusiveness ensures that the system works well across different regions, languages, and cultures, making the system accessible and beneficial for all users.

A. Transparency

Important for explaining how AI systems work, but does not directly address equitable results across demographics.

D. Reliability and safety

Focuses on consistent and safe system operation, not equity across users.

E. Privacy and security

Critical for data protection, but not related to equitable treatment of users.

Why not the other options?

Correct Answer:

B. fairness

C. inclusiveness

Microsoft Responsible AI Principles

Fairness in AI systems

Inclusiveness in AI systems

Microsoft References