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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 6 Question 33 Discussion

After the initial creation of a model, the first model insight explains93% of the variation of the outcome variable. This is unusually high.What is the most likely reason for this?
C) The outcome variable may be causing data leakage.
A) The dataset contains multiple dominant values.
B) The model contains too many outlier values.

Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 6 Question 33 Discussion

Actual exam question for Salesforce's Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam
Question #: 33
Topic #: 6
[All Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Questions]

After the initial creation of a model, the first model insight explains

93% of the variation of the outcome variable. This is unusually high.

What is the most likely reason for this?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Francoise at Mar 07, 2026, 02:00 AM

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Thomasena
3 days ago
A could be the reason too. Dominant values can mislead.
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Lindsey
8 days ago
I agree, C makes sense. High variation is suspicious.
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Aleisha
13 days ago
I think it's C. Data leakage can skew results.
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Francesco
18 days ago
True, but I still lean towards C. It explains the anomaly well.
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Kirk
24 days ago
A could be a reason too. Dominant values can affect the model.
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Jeffrey
29 days ago
Agreed, C makes sense. Too high of a variation is suspicious.
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Malissa
1 month ago
I think it's C. Data leakage can skew results.
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Karima
1 month ago
Multiple dominant values could skew the results too.
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Jeniffer
1 month ago
I disagree, it could just be a well-structured dataset.
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Francine
2 months ago
I thought models usually explain less than that?
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Allene
2 months ago
Definitely sounds like data leakage to me.
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Genevieve
2 months ago
That's a crazy high percentage!
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Wynell
2 months ago
I disagree, outliers could be the real issue here.
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Julieta
2 months ago
I think it could be the dominant values messing things up.
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Carin
4 months ago
Wait, 93%? That seems too good to be true!
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Yuriko
4 months ago
Definitely sounds like data leakage to me.
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Yong
4 months ago
That's a crazy high percentage!
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Marylyn
4 months ago
Really? 93%? I’m not buying it without more info.
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Mariko
5 months ago
A) seems plausible, but I lean towards C).
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Vannessa
5 months ago
I thought models usually explain less than that?
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Ivory
5 months ago
Definitely sounds like data leakage to me.
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Kiley
5 months ago
That's a crazy high percentage!
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Armando
5 months ago
I really can't decide between C and B. Both seem plausible, but I lean towards C because of the data leakage concept we practiced.
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Arminda
5 months ago
I feel like we went over a similar question where dominant values affected the model's performance. Could it be A?
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Lashaun
6 months ago
I'm not entirely sure, but I think having too many outliers could skew the results too. Maybe option B is also a possibility?
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Shaquana
6 months ago
I remember discussing data leakage in class, and it seems like option C could be the right answer since it would explain such a high percentage of variation.
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