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Salesforce AI Associate Exam - Topic 1 Question 13 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam

Question #: 13
Topic #: 1

[All Salesforce AI Associate Questions]

What is the rile of data quality in achieving AI business Objectives?

AData quality is unnecessary because AI can work with all data types.

BData quality is required to create accurate AI data insights.

CData quality is important for maintain Ai data storage limits

Show Suggested Answer

Suggested Answer: B

''Data quality is required to create accurate AI data insights. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data quality can also affect the accuracy and validity of AI data insights, as they reflect the quality of the data used or generated by AI systems.''

by James at Mar 07, 2024, 08:48 AM

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Lindsey

9 months ago

I’m not convinced that data quality is always necessary.

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Darrel

10 months ago

Data quality definitely impacts AI performance, no doubt about it.

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Nakisha

10 months ago

Wait, can AI really work with all data types? That sounds off.

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Frankie

10 months ago

Totally agree, without good data, AI is just guessing.

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Terrilyn

10 months ago

Data quality is super important for accurate insights!

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Honey

10 months ago

I vaguely recall that poor data quality can lead to misleading insights, which could hurt business decisions. So, B seems right to me too.

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Noah

11 months ago

I feel like we had a practice question about data storage limits, but I'm not sure if that relates directly to achieving business objectives.

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Arlene

11 months ago

I'm a bit unsure, but I think I read somewhere that data quality isn't just about insights; it also affects how AI learns over time.

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Isaac

11 months ago

I remember we discussed how data quality impacts the accuracy of AI models, so I think option B makes the most sense.

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Cherry

11 months ago

Data quality for AI storage limits? That doesn't sound right. I'm leaning towards option B, but I'll have to think this through a bit more.

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Lashon

11 months ago

I think the key here is understanding the role of data quality in achieving business objectives with AI. Option B seems to capture that best, so that's my pick.

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Gwen

11 months ago

This question seems straightforward - data quality is clearly important for accurate AI insights, so I'll go with option B.

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Karma

11 months ago

Hmm, I'm a bit confused. Isn't the whole point of AI that it can work with any data, even messy or incomplete data? Option A seems plausible to me.

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Marlon

11 months ago

I think I can handle this. The key is to update the nosql Deployment to request 160M of memory and limit it to half the maximum memory constraint set for the crayfah namespace.

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Delmy

11 months ago

I remember discussing collusion with external parties—it's a common issue. I'm uncertain about the “stationary” option; it feels minor compared to the others.

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Blondell

11 months ago

Okay, let's see here. I think the key is to understand the difference between full data updates and change-only updates. That should help me narrow down the correct answer.

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Charolette

11 months ago

I remember practicing a similar question about decentralized control—it complicates accountability, which could be critical for regulations.

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Bok

2 years ago

Yes, AI can process different data types, but quality ensures reliable outcomes.

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Shelton

2 years ago

But doesn't AI have the ability to work with all data types?

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Adolph

2 years ago

I agree, without good data quality, AI results can be unreliable.

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Levi

2 years ago

Option B is spot on. High-quality data is the foundation for any successful AI implementation. Gotta get that data squeaky clean!

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Ben

2 years ago

C) Without good data quality, AI results can be unreliable.

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Celeste

2 years ago

B) Absolutely, clean data is essential for AI to provide accurate insights.

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Cecil

2 years ago

A) Data quality is required to create accurate AI data insights.

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Janey

2 years ago

I think data quality is necessary for accurate AI insights.

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Jennifer

2 years ago

Yes, AI can process different data types, but quality ensures reliable outcomes.

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Rasheeda

2 years ago

Maintaining AI data storage limits? That's the least of my concerns. I'm more worried about my storage limits after that big cheese dip incident last weekend.

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Xuan

2 years ago

I hear you, accuracy is key when it comes to data quality.

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Graciela

2 years ago

Data quality is required to create accurate AI data insights.

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Tracie

2 years ago

But doesn't AI have the ability to work with all data types?

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Ammie

2 years ago

I agree, without good data quality, AI results can be unreliable.

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Irma

2 years ago

I don't know, I think AI can just magic its way through any data, no matter how messy. Who needs data quality when you have AI, am I right?

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Rashida

2 years ago

Data quality is definitely required for accurate AI insights. Without clean, reliable data, AI models will be garbage in, garbage out.

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Altha

2 years ago

B) Data quality is required to create accurate AI data insights.

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Silvana

2 years ago

A) Data quality is unnecessary because AI can work with all data types.

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Margot

2 years ago

B) Data quality is required to create accurate AI data insights.

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Evelynn

2 years ago

I think data quality is necessary for accurate AI insights.

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