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Salesforce Exam Salesforce AI Associate Topic 1 Question 34 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 34
Topic #: 1
[All Salesforce AI Associate Questions]

Cloud Kicks prepares a dataset for an AI model and identifies some inconsistencies in the data.

What is the most appropriate action the company should take?

Show Suggested Answer Hide Answer
Suggested Answer: C

When inconsistencies in data are identified, the most appropriate action is to investigate these inconsistencies and apply data quality techniques. Adjusting the AI model to accommodate poor quality data or simply increasing the quantity of data without addressing the underlying issues does not solve the problem and can lead to less reliable AI outputs. Proper data cleaning, normalization, and validation are necessary steps to ensure that the data fed into an AI model is accurate and reliable, thus enhancing the model's performance. Salesforce provides guidelines on how to manage and improve data quality, including practical steps for addressing data inconsistencies, detailed at Improving Data Quality in Salesforce.


by Teddy at Nov 15, 2024, 07:16 AM

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Nada
2 days ago
B? Really? Quantity over quality? What is this, a fast food restaurant? No, no, C is the way to go. Gotta clean up that data first before you can even think about training the model.
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Tori
3 days ago
A, for sure. Just let the AI model figure it out. That's what machine learning is all about, right? Adjusting and adapting to whatever data you throw at it.
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Derick
4 days ago
Oh, I bet the data is a real mess. Probably just a bunch of cat photos labeled as 'dog' or something. Time to get our data cleaning hats on!
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Viva
15 days ago
I believe adjusting the AI model to account for the data inconsistencies is also important.
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Catarina
17 days ago
C'mon, the obvious choice here is C. Data quality is key for any AI model. You can't just slap some extra data on it and hope for the best.
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Rosina
1 days ago
User 2: Definitely, without addressing the data inconsistencies, the model won't be accurate.
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Genevieve
9 days ago
User 1: I agree, data quality is crucial for the success of the AI model.
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Tamesha
18 days ago
I agree with Yvonne. Applying data quality techniques is crucial for accurate results.
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Yvonne
24 days ago
I think the company should investigate the data inconsistencies.
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