AI Associate AI Fundamentals Practice Question
Which TWO actions are recommended when preparing data for an Einstein Prediction Builder model?
⚠ Common exam trap
Salesforce often tests the misconception that more data (all fields) or recent data only is always better, but the trap here is that Einstein Prediction Builder requires a minimum record threshold and logically relevant features to avoid noise and ensure model validity.
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
✓
Ensure the data set contains at least 500 records with the outcome field populated.
Einstein Prediction Builder requires a minimum of 500 records with the outcome field populated to ensure statistical significance and reliable model training. Fewer records can lead to overfitting or insufficient pattern recognition, making the model less accurate.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Ensure the data set contains at least 500 records with the outcome field populated.
Why this is correct
Minimum sample size is required for model training.
- ✗
Include all available fields on the object, even if unrelated.
Why it's wrong here
Unrelated fields add noise and can degrade accuracy.
- ✗
Use external data sources and upload CSV files without any preprocessing.
Why it's wrong here
Data should be cleaned and mapped to standard objects.
- ✓
Select fields that are logically related to the prediction outcome.
Why this is correct
Relevant fields improve model accuracy.
- ✗
Include data from the last two days only for the most current trends.
Why it's wrong here
Two days is insufficient; need longer history (e.g., 6 months).
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This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.