AI Associate Data for AI Practice Question
A Salesforce admin wants to use Einstein Prediction Builder to predict case resolution time. What type of data is most critical for training this model?
⚠ Common exam trap
A common mix-up: candidates confuse factors that influence resolution time (like employee schedules or inventory) with the actual labeled outcome data required to train a supervised prediction model.
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
✓
Historical case records including resolution time
Einstein Prediction Builder requires historical data with known outcomes to train a supervised machine learning model. Historical case records containing actual resolution times provide the labeled examples needed for the model to learn patterns and predict future case resolution times. Without this ground truth data, the model cannot be trained to make accurate predictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Customer satisfaction survey responses
Why it's wrong here
Surveys measure satisfaction, not resolution time.
- ✓
Historical case records including resolution time
Why this is correct
Historical data is essential for training.
- ✗
Product inventory levels
Why it's wrong here
Inventory does not directly affect resolution time.
- ✗
Employee work schedules
Why it's wrong here
Schedules may be a feature but not the most critical.
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