AI Associate Data for AI Practice Question
Which three practices help maintain data quality for AI models in Salesforce? (Choose three.)
⚠ Common exam trap
Test-takers frequently think disabling duplicate rules speeds up data loading, but they overlook that duplicate records severely degrade AI model performance by introducing bias and noise.
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
✓
Monitor data freshness with Data Check
Data Check in Salesforce monitors data freshness by tracking when records were last updated, ensuring that AI models use current data. Stale data can degrade model accuracy, so this practice directly supports data quality for AI.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Monitor data freshness with Data Check
Why this is correct
Data Check alerts on stale or outdated data that could affect model accuracy.
- ✗
Disable duplicate matching rules for faster load
Why it's wrong here
Disabling duplicate rules can lead to redundant records.
- ✗
Use Excel for manual data updates
Why it's wrong here
Manual updates introduce human error and lack auditing.
- ✓
Schedule regular data audits
Why this is correct
Audits check for consistency, completeness, and accuracy over time.
- ✓
Implement validation rules on critical fields
Why this is correct
Validation rules prevent invalid data from being entered.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.