1.3Standard
Explain which transformations produced a model.
Reprocess data when a source is wrong.
Choose two practices.
× Incorrect
Link source, extraction, transformation, labeling, splitting, features, model, and deployment with versions, owners, schemas, approvals, and quality results.
Detailed explanation
CorrectLink source, extraction, transformation, labels, splits, features, model, and deployment
Impact and reproducibility are visible.
IncorrectKeep only the final model
Root cause and impact cannot be traced.
CorrectTrack data versions, schemas, transform code, owners, approvals, and quality results
Changed assets and reprocessing scope are identifiable.
IncorrectChange data without updating model relationships
Affected models are unknown.
Check official documentation
Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 1.3のデータ系譜、MLOps、モデル再現性を確認する。
Official references
What to confirm
モデルへ至るデータ変換と責任・版を追跡し、問題データの影響を特定できる。
Key points
- Lineage
- Impact
- Reprocessing
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Data lineage
A trace of where data came from and how it changed through processing.
Impact analysis
An assessment of downstream assets and results affected by a change.
Question IDAWS-AIF-411
EnvironmentAWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
Last technical review2026-08-20
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