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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 3 Question 1 Discussion

When deploying a model to an existing Prediction, w number should be considered"1
B) 10: Limit of number of models under a Prediction Definition.
A) 5: Limit of total number of Prediction Definitions.
C) 20: Limit of number of models under a Prediction Definition.
D) 3: Limit of total number of Models.

Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 3 Question 1 Discussion

Actual exam question for Salesforce's Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam
Question #: 1
Topic #: 3
[All Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Questions]

When deploying a model to an existing Prediction, w number should be considered"1

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Suggested Answer: B

by Evette at Aug 02, 2024, 05:34 PM

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Delsie
8 months ago
5 Prediction Definitions? That’s a weird limit!
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Marion
8 months ago
I heard it's actually 20 models allowed, not 10.
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Corazon
8 months ago
Wait, is it really only 3 total models? That seems low.
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Felicidad
9 months ago
Definitely agree with that, 10 sounds right!
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Estrella
9 months ago
I think it's 10 models max under a Prediction Definition.
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Carmelina
9 months ago
I vaguely recall that there’s a limit of 3 total models, but I can't remember if that's right.
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Tamra
9 months ago
I’m a bit confused; I thought there was a total limit of 5 Prediction Definitions overall.
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Marge
9 months ago
I feel like I practiced a question similar to this, and I think the limit for models was 10.
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Malcom
9 months ago
I think I remember something about limits on models, but I'm not sure if it's 10 or 20 under a Prediction Definition.
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Josphine
9 months ago
Okay, let me see if I can work this out. When deploying a model, the number that needs to be considered is the limit on the number of models under a Prediction Definition. I believe that's 10, so the answer is B.
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Devora
9 months ago
Hmm, I'm not totally sure about this one. I know there are limits on Prediction Definitions and Models, but I can't remember the exact numbers. I'll have to think this through carefully.
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Cammy
9 months ago
This question seems straightforward, I think the answer is B - the limit of number of models under a Prediction Definition is 10.
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Phuong
10 months ago
I'm a bit confused by this question. Is it asking about the limit on Prediction Definitions or the limit on Models? I want to make sure I understand the difference before I select an answer.
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Mollie
10 months ago
I'm a bit confused by all the numbers and calculations here. Can someone walk me through this step-by-step? I want to make sure I understand it fully before answering.
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Mable
10 months ago
I've got a good feeling about this one. The exhibits provide a lot of useful information, and I think I can use that to identify the correct issue preventing direct access to the application servers.
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Elfrieda
2 years ago
I think D) 3: Limit of total number of Models is too restrictive, we need more options for deploying models.
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Jesusa
2 years ago
I believe the answer is C) 20: Limit of number of models under a Prediction Definition, as it allows for more flexibility.
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Talia
2 years ago
I agree with Barrett, having too many models under one Prediction Definition could lead to confusion.
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Barrett
2 years ago
I think the answer is B) 10: Limit of number of models under a Prediction Definition.
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Dean
2 years ago
I think D) 3: Limit of total number of Models is too restrictive, we should have more options for deploying models.
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Floyd
2 years ago
I believe the answer is C) 20: Limit of number of models under a Prediction Definition, as it allows for more flexibility.
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Moon
2 years ago
Woah, this is a tricky one. I'm gonna go with C) 20: Limit of number of models under a Prediction Definition. It just seems more logical to me.
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Louvenia
2 years ago
I agree with you, User2. B) 10: Limit of number of models under a Prediction Definition sounds right.
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Annmarie
2 years ago
I'm leaning towards B) 10: Limit of number of models under a Prediction Definition.
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Orville
2 years ago
I think I'll go with A) 5: Limit of total number of Prediction Definitions.
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Camellia
2 years ago
I agree with Nobuko, having too many models under a Prediction Definition could cause performance issues.
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Azalee
2 years ago
Haha, this question is a piece of cake! The answer is obviously B) 10: Limit of number of models under a Prediction Definition. I could answer this in my sleep.
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Franklyn
2 years ago
Hmm, I'm not sure about this one. Let me think... Ah, I got it! The answer must be D) 3: Limit of total number of Models. That's gotta be it!
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Adell
2 years ago
Hmm, I'm not sure about this one. Let me think... Ah, I got it! The answer must be D) 3: Limit of total number of Models. That's gotta be it!
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Veronika
2 years ago
Actually, I'm pretty sure it's C) 20: Limit of number of models under a Prediction Definition.
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Reta
2 years ago
No, I believe it's B) 10: Limit of number of models under a Prediction Definition.
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Roxane
2 years ago
I think the answer is A) 5: Limit of total number of Prediction Definitions.
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Basilia
2 years ago
I think the answer is C) 20: Limit of number of models under a Prediction Definition. That seems more reasonable than just 10, don't you think?
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Phyliss
2 years ago
The answer is clearly B) 10: Limit of number of models under a Prediction Definition. I learned this in my training and it's crucial to know when deploying models.
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Leota
2 years ago
Yes, having a clear understanding of the limits can help avoid any issues during deployment.
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Adela
2 years ago
I agree, it's important to keep in mind the limit of models when deploying.
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Tamesha
2 years ago
I always double check the number of models before deploying to avoid any issues.
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Reynalda
2 years ago
Yes, having a limit of 10 models under a Prediction Definition is crucial for successful deployment.
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Alex
2 years ago
I agree, it's important to keep in mind the limit of models when deploying.
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Nobuko
2 years ago
I think the answer is B) 10: Limit of number of models under a Prediction Definition.
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