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AI Lifecycle Risk ManagementmediumMultiple SelectObjective-mapped

AAIR AI Lifecycle Risk Management Practice Question

Which TWO of the following scenarios represent 'Data Quality Risk'?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Training data is from a 5-year-old dataset that is no longer representative.

Inconsistent formatting and lack of temporal relevance are clear data quality issues.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Training data is from a 5-year-old dataset that is no longer representative.

    Why this is correct

    Lack of temporal relevance renders the data low-quality for current needs.

  • The model is deployed on a slow network.

    Why it's wrong here

    This is an infrastructure performance issue.

  • The model is written in a new programming language.

    Why it's wrong here

    Not a quality risk.

  • Training data features have inconsistent units (e.g., mixed meters and feet).

    Why this is correct

    This is a fundamental data quality error.

  • The model uses a popular open-source library.

    Why it's wrong here

    Not a quality risk.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official ISACA exam blueprint

This AAIR practice question is part of Courseiva's free ISACA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AAIR exam.