AI Associate Data for AI Practice Question
A data analyst is troubleshooting Einstein Article Recommendations that are not showing up on the site. Which TWO checks should be performed first? (Choose 2)
⚠ Common exam trap
Salesforce often tests the misconception that increasing data volume or frequency (Options A and D) will fix recommendation issues, when in fact the core problem is usually missing event data or an inactive 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
✓
Check that article view events are being captured in the data
Einstein Article Recommendations rely on user interaction data, specifically article view events, to generate personalized recommendations. If these events are not being captured, the model has no input to learn from, and recommendations will not appear. Checking event capture is a fundamental first step in troubleshooting data pipeline issues.
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 at least 100 articles are in the knowledge base
Why it's wrong here
No strict minimum; even fewer articles can work if views exist.
- ✗
Confirm that article authors have the correct profile permissions
Why it's wrong here
Author permissions do not affect recommendation display.
- ✓
Check that article view events are being captured in the data
Why this is correct
Without view data, the model has no basis to recommend.
- ✗
Increase the recommendation frequency from daily to hourly
Why it's wrong here
Frequency is not usually the cause of missing recommendations.
- ✓
Verify that the recommendation model is published and active
Why this is correct
An unpublished model will not serve recommendations.
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