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Data for AI practice questions

Practise Salesforce AI Associate AI Associate Data for AI practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security
20 questionsDomain: Data for AI

What the exam tests

What to know about Data for AI

Data for AI questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

Watch out for

Common Data for AI exam traps

  • Answering from memory before reading the full scenario.
  • Missing a constraint such as cost, availability, security, scope or command context.
  • Choosing a broad answer when the question asks for the most specific fix.
  • Ignoring why the wrong options are tempting.

Practice set

Data for AI questions

20 questions · select your answer, then reveal the explanation

Question 1mediummultiple choice
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A company uses Einstein Discovery to identify factors that increase case resolution time. After training, the model shows that 'Case_Origin__c' has high importance. What action should the company take?

Question 2hardmultiple choice
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A company has set up Einstein Next Best Action with a recommendation strategy. They want to ensure that recommendations are personalized based on the customer's recent behavior. What data should be used?

Question 3mediummulti select
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Which TWO actions are required to prepare data for an Einstein Discovery model?

Question 4mediummultiple choice
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A Salesforce admin is troubleshooting an Einstein Prediction Builder model that is not generating predictions. The model was created with a custom object 'Feedback__c'. The admin notices that the model's data source includes records with status 'In Progress' and 'Closed'. What is the most likely cause of the model not generating predictions?

Question 5mediummultiple choice
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An admin is configuring Einstein Vision and wants to train a model to identify product defects from images. The admin has uploaded 500 images of defective products and 500 images of non-defective products. However, the model training fails with an error about data quality. What is the most likely cause?

Question 6easymultiple choice
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You are a Salesforce admin at a nonprofit organization. The organization uses Einstein Engagement Scoring to prioritize donors for outreach. The model is based on donation history and event attendance. Recently, the model stopped generating new scores for recently added donors. You check the data source and see that the model's data includes the 'Contact' and 'Opportunity' objects. The data refresh is scheduled daily. The model status is 'Active'. What should you investigate first to resolve the issue?

Question 7hardmultiple choice
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A global company needs to ensure that customer data used for AI models complies with multiple regional regulations (GDPR, CCPA, LGPD). Which data governance practice is most effective?

Question 8mediummultiple choice
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Refer to the exhibit. A data access policy is defined for a customer data set. Which statement best describes this policy?

Exhibit

{
  "policy": {
    "resource": "customer_data",
    "action": "read",
    "conditions": [
      {"field": "region", "operator": "eq", "value": "EU"}
    ],
    "masking": {
      "fields": ["email", "phone"],
      "method": "partial"
    }
  }
}
Question 9hardmultiple choice
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Refer to the exhibit. The data pipeline is failing. What is the most likely cause?

Exhibit

2023-10-01 12:00:01 ERROR [DataPipeline] com.salesforce.datalake.pipeline.TransformException: Field 'account_id' not found in schema. Expected String, got null.
2023-10-01 12:00:02 INFO [DataPipeline] Retrying task 3/3 after 5000ms.
Question 10hardmultiple choice
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Refer to the exhibit. What is the most likely cause of this error?

Exhibit

2025-03-01 14:32:15 ERROR [DataTransformRunner] Transform failed: java.lang.ArithmeticException: / by zero
at com.salesforce.dc.datatransform.FormulaEvaluator.processField(FormulaEvaluator.java:256)
Question 11easymultiple choice
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A company wants to build a sentiment analysis model using customer feedback. What is the best practice for labeling the training data?

Question 12easymultiple choice
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A Salesforce admin wants to use Einstein Recommendations to suggest products. What is a key requirement for the data used to train the recommendation model?

Question 13mediummultiple choice
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A data scientist needs to feed customer interaction data into Einstein Discovery for predictive analysis. Which data format is required?

Question 14hardmultiple choice
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A company uses Salesforce Data Cloud to unify customer data from multiple sources for AI model training. After adding a new data source, model performance degrades significantly. What is the most likely cause?

Question 15easymultiple choice
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Which data type is most commonly used for image recognition AI models?

Question 16mediummultiple choice
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A team has limited labeled data for a Salesforce predictive model but wants to leverage a pre-trained model from a related task. Which machine learning approach should they use?

Question 17hardmultiple choice
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After deploying an AI model in Salesforce, the data scientist notices high accuracy on the training set but poor accuracy on new incoming data. What is this phenomenon called?

Question 18easymultiple choice
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To ensure AI model fairness and avoid biased outcomes, which practice is most critical when preparing training data?

Question 19mediummultiple choice
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A company wants to integrate external customer behavior data into Salesforce to enhance AI predictions. Which Salesforce Data Cloud feature is specifically designed to ingest and map external data?

Question 20mediummulti select
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Which TWO are best practices for data labeling in AI projects? (Choose two.)

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Frequently asked questions

What does the AI Associate exam test about Data for AI?
Data for AI questions test whether you can apply the concept in context, not just recognise a definition.
How should I use these practice questions?
Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Data for AI questions in a focused session?
Yes — the session launcher on this page draws every question from the Data for AI domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
Where can I practise other AI Associate topics?
Use the topic links above to move to related areas, or go back to the AI Associate question bank to see all topics.
Are these real exam questions or dumps?
These are original practice questions written to test the same concepts the AI Associate exam covers. They are not copied from any real exam or dump site.