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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 1 Question 21 Discussion

A team of CRM Analytics developers has been working on an existing recipe to add new derived fields. The edited version has been failing ever since, and management is requesting that the dashboard show refreshed data while they work on the edits.How can the developers add new fields while keeping the dataset refreshed?
A) A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.
B) Clone the existing recipe to add fields and roll back the original recipe to the last working version.
C) Refresh the dataset after working hours to avoid the edited version from failing.

Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam - Topic 1 Question 21 Discussion

Actual exam question for Salesforce's Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam
Question #: 21
Topic #: 1
[All Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Questions]

A team of CRM Analytics developers has been working on an existing recipe to add new derived fields. The edited version has been failing ever since, and management is requesting that the dashboard show refreshed data while they work on the edits.

How can the developers add new fields while keeping the dataset refreshed?

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Suggested Answer: A

by Leonard at Mar 18, 2025, 03:55 AM

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Malinda
9 months ago
I think they should definitely try Option A first.
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Daron
9 months ago
I disagree, refreshing after hours (Option C) won't solve the underlying issue.
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Colby
9 months ago
Wait, can they really just roll back like that? Sounds too easy!
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Johnetta
9 months ago
A new recipe as a join node (Option A) could work too, but it sounds complicated.
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Vallie
10 months ago
Option B seems like the safest bet. Roll back and work on a clone.
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Barrett
10 months ago
I practiced a similar question where we had to manage edits without downtime. I think the join node option could work, but I'm not entirely confident.
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Erinn
10 months ago
I feel like refreshing the dataset after hours might just be a temporary fix. We need a more permanent solution.
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Mari
10 months ago
Cloning the existing recipe sounds familiar; I think it could help avoid issues with the original version failing.
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Willard
10 months ago
I remember something about using a join node, but I'm not sure if that's the best approach here.
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Dorethea
11 months ago
Okay, I think I've got a handle on this. Option A sounds like the way to go. Create a separate recipe for the new fields, test it out, and then add it in as a join. That way we can keep the core recipe working while we iterate on the new stuff. Shouldn't be too much extra work, and it's the safest approach.
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Delila
11 months ago
Hmm, I'm not sure any of these options are perfect. I think I'd want to dig into the details a bit more to understand exactly what's going on with the failing edited version. Maybe we could try option A, but also see if we can figure out what's causing the issues with the edited recipe.
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Merlyn
11 months ago
I'm a bit confused on this one. Should we really be cloning the entire recipe just to add some new fields? That seems like a lot of extra work. I'm leaning more towards option C - just refreshing the dataset after hours to avoid the failing edited version.
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Merissa
11 months ago
This seems like a tricky one. I'm thinking option A might be the best approach - create a separate recipe for the new fields and then add it as a join node to the existing recipe. That way we can keep the existing recipe working while we test out the new fields.
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Linwood
1 year ago
Option A sounds like a good compromise. Add the new fields in a separate recipe and then integrate it into the existing one. That way, the dashboard can stay refreshed while the changes are being made.
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Sharee
1 year ago
I agree. It's crucial to have a smooth transition when adding new fields to avoid any disruptions in the dataset refreshment.
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Yesenia
1 year ago
That's a good point. It's important to ensure that the dashboard continues to show updated data even during the development process.
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Shawnda
1 year ago
Option A sounds like a good compromise. Add the new fields in a separate recipe and then integrate it into the existing one. That way, the dashboard can stay refreshed while the changes are being made.
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Thersa
1 year ago
I agree. It's crucial to have a smooth transition when adding new fields to avoid disruptions in the dataset refresh process.
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Crista
1 year ago
That's a good point. It's important to ensure that the dashboard continues to show updated data even during the development process.
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Herminia
1 year ago
Option A sounds like a good compromise. Add the new fields in a separate recipe and then integrate it into the existing one. That way, the dashboard can stay refreshed while the changes are being made.
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Wilda
1 year ago
Ha! I bet the developers are wishing they had a 'refresh' button for themselves right about now. Option B sounds like the best way to keep the dashboard running while they figure this out.
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Edward
1 year ago
I agree, it's important to keep the dashboard running while they work on the edits. Cloning the recipe seems like the best solution.
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Blondell
1 year ago
Yeah, rolling back to the last working version is a smart move. It will prevent any further issues with the edited version.
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Nikita
1 year ago
Option B sounds like a good plan. They can clone the existing recipe to add fields and keep the dashboard running smoothly.
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Gracia
1 year ago
I'm not sure I agree with Option C. Refreshing the dataset after working hours doesn't really solve the problem, it just delays it. The new fields need to be added in a way that doesn't cause the whole recipe to fail.
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Ciara
1 year ago
A) A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.
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Erick
1 year ago
I'm not sure about rolling back the original recipe, that could cause data loss.
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Kimi
1 year ago
B) Clone the existing recipe to add fields and roll back the original recipe to the last working version.
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Cory
1 year ago
A) A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.
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Ariel
1 year ago
I agree, adding the new fields separately and then integrating them into the existing recipe seems like the best approach.
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Beatriz
1 year ago
A) A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.
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Walton
1 year ago
Option B seems the most logical approach. Cloning the existing recipe and rolling back the original will ensure the dashboard stays refreshed while the new fields are being added.
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Arthur
1 year ago
I see both points, but I think option C could also work. Refreshing the dataset after working hours can minimize disruptions during the editing process.
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Tyisha
1 year ago
I disagree, I believe option B is more practical. Cloning the existing recipe ensures that the original version can be easily restored if the edits fail.
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Nidia
1 year ago
I think option A is the best choice. It allows for testing the new fields separately before adding them to the existing recipe.
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