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AI Associate AI Fundamentals Practice Question

A company wants to use Einstein Discovery to analyze sales data and automatically uncover key drivers of deal closure. What must the admin provide to create a story?

⚠ Common exam trap

Salesforce often tests the misconception that Einstein Discovery requires a date field for time series or a foreign key for relational data, when in fact the core requirement is a numeric field to define the prediction target.

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

At least one numeric field to predict

Einstein Discovery requires at least one numeric field as the prediction target (e.g., deal amount, probability score) to train its regression or classification model. Without a numeric field to predict, the story cannot define what outcome the AI should analyze or uncover key drivers for.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • At least one numeric field to predict

    Why this is correct

    Discovery predicts numeric values or binary outcomes; a numeric target is required.

  • A date field for time series analysis

    Why it's wrong here

    Date fields are optional for time-based trends but not mandatory.

  • A foreign key to relate objects

    Why it's wrong here

    Foreign keys are not required; Discovery works on a single dataset.

  • A text field for sentiment analysis

    Why it's wrong here

    Sentiment analysis is not part of Discovery stories.

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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.