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Part 7 - Salesforce AI Associate

Authored by quizizz psocial

Information Technology (IT)

KG

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Part 7 - Salesforce AI Associate
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9 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior. What is a crucial factor that the developer should consider during selection?

Size of dataset

Number of variables in the dataset

Age of dataset

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an implication of user consent in regard to AI data privacy?

AI ensures complete data privacy by automatically obtaining user consent.

AI operates independently of user privacy and consent.

AI infringes on privacy when user consent is not obtained.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Cloud Kicks learns of complaints from customers who are receiving too many sales calls and emails. Which data quality dimension should be assessed to reduce these communication inefficiencies?

Usage

Duplication

Consent

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Cloud Kicks wants to ensure that multiple records for the same customer are removed from Salesforce. Which feature should be used to accomplish this?

Duplicate management

Trigger deletion of old records

Standardized field names

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Cloud Kicks wants to develop a solution to predict customers' product interests based on historical data. The company found that employees from one region use a text field to capture the product category, while employees from other locations use a picklist. Which data quality dimension is affected in this scenario?

Completeness

Consistency

Accuracy

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a key benefit of effective interaction between humans and AI systems?

Leads to more informed and balanced decision-making

Reduces the need for human involvement

Alerts humans to the presence of biased data

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does data quality impact the trustworthiness of AI-driven decisions?

High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users.

The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.

Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.

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