PDE Preparing and Using Data for Analysis Practice Question
A data engineer is using Vertex AI Workbench to develop a custom ML model. They want to store and version datasets, track experiments, and register models. Which three Vertex AI services should they use? (Choose THREE)
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
✓
Vertex AI Model Registry
Vertex AI Dataset stores and manages datasets. Vertex AI Experiments tracks ML experiments. Vertex AI Model Registry stores and versions trained models.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Vertex AI Model Registry
Why this is correct
For registering and versioning models.
- ✓
Vertex AI Dataset
Why this is correct
For storing and managing datasets.
- ✗
Vertex AI Feature Store
Why it's wrong here
Feature Store is for feature management, not dataset/experiment tracking.
- ✗
Vertex AI Matching Engine
Why it's wrong here
Matching Engine is for vector similarity search, not for experiment tracking.
- ✓
Vertex AI Experiments
Why this is correct
For tracking experiment runs and parameters.
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Written by Johnson Ajibi, MSc IT Security
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This PDE practice question is part of Courseiva's free Google Cloud 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 PDE exam.