AI Associate Data for AI Practice Question
Exhibit
{
"fieldMapping": [
{"sourceField": "Id", "targetType": "Text"},
{"sourceField": "AccountName", "targetType": "Text"},
{"sourceField": "CloseDate", "targetType": "Date"},
{"sourceField": "Amount", "targetType": "Number"},
{"sourceField": "LeadSource", "targetType": "Category"}
]
}Refer to the exhibit. A data analyst has defined this field mapping for Einstein Prediction Builder. Which data issue would most likely arise from this mapping?
⚠ Common exam trap
Salesforce often tests the concept of data leakage by including a seemingly harmless field like 'Id', tricking candidates into thinking all fields should be mapped, when in fact unique identifiers must be excluded to prevent overfitting.
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
✓
The 'Id' field should be excluded as it can cause data leakage and overfitting
Including the 'Id' field in Einstein Prediction Builder can cause data leakage and overfitting. The 'Id' field is a unique identifier that has no predictive value for the target outcome, but the model could learn to memorize specific records based on it, leading to poor generalization on unseen data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The 'LeadSource' field should be mapped to 'Text' instead of 'Category' to preserve verbatim values
Why it's wrong here
LeadSource is typically a fixed set of values, so Category is appropriate.
- ✗
The 'Amount' field should be mapped to 'Category' to discretize the values
Why it's wrong here
Amount is numeric and should be used as Number.
- ✓
The 'Id' field should be excluded as it can cause data leakage and overfitting
Why this is correct
Unique identifiers act as keys and should not be used as predictors.
- ✗
The 'CloseDate' field should be mapped to 'Text' to avoid date parsing issues
Why it's wrong here
Date type allows Einstein to extract temporal patterns.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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