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Salesforce Exam Salesforce AI Associate Topic 4 Question 35 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 35
Topic #: 4
[All Salesforce AI Associate Questions]

Cloud Kicks wants to develop a solution to predict customers product interests based on historical dat

a. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst.

Which data quality dimension is affected in this scenario?

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Suggested Answer: A

A technique to mitigate bias and ensure fairness in AI applications is ongoing auditing and monitoring of the data used in AI applications. Regular audits help identify and address any biases that may exist in the data, ensuring that AI models function fairly and without prejudice. Monitoring involves continuously checking the performance of AI systems to safeguard against discriminatory outcomes. Salesforce emphasizes the importance of ethical AI practices, including transparency and fairness, which can be further explored through Salesforce's AI ethics guidelines at Salesforce AI Ethics.


by Rosendo at Dec 11, 2024, 06:43 AM

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Jeannine
Wait, did someone really use a 'plckllst' instead of a proper dropdown? That's a whole new level of data shenanigans right there. Talk about consistency challenges!
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Jarvis
2 days ago
C) Consistency is the correct answer here. Inconsistent data capture methods across regions are bound to introduce issues with the integrity and reliability of the data.
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Annamaria
6 days ago
Consistency is key when it comes to data quality. If the employees can't even agree on how to capture product categories, how can the company trust the insights they're getting?
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Darrin
19 days ago
Oof, the plckllst? Looks like someone had a bit too much fun with the keyboard. But seriously, this is a textbook case of consistency issues. Gotta get that data aligned, folks!
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Rosenda
3 days ago
Yeah, definitely a consistency issue. Need to standardize that data input.
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Jacinta
24 days ago
But could it also be accuracy, since the text field may not accurately capture the product category?
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Lynelle
25 days ago
The lack of consistency in data capture definitely affects the overall data quality. A standardized approach across all locations is crucial for reliable analysis.
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Pearly
3 days ago
A: I think the lack of consistency in data capture is a big issue.
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Corinne
29 days ago
I agree with Glory, because the data is not consistent across regions.
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Glory
1 months ago
I think the data quality dimension affected is consistency.
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