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Tableau-CRM-and-Einstein-Discovery-Consultant Dumps - Salesforce Tableau CRM Einstein Discovery Consultant (SP25) Practice Exam Questions

Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant - Salesforce Tableau CRM Einstein Discovery Consultant (SP25) Braindumps

Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant - Tableau-CRM-and-Einstein-Discovery-Consultant Practice Exam

  • Certification Provider:Salesforce
  • Exam Code:Tableau-CRM-and-Einstein-Discovery-Consultant
  • Exam Name:Salesforce Tableau CRM Einstein Discovery Consultant (SP25)
  • Certification Name:Tableau-CRM-and-Einstein-Discovery-Consultant
  • Total Questions:239 Questions and Answers With Detailed Explanations
  • Updated on:Based on the current Tableau-CRM-and-Einstein-Discovery-Consultant exam blueprint. Updated on Dec 1, 2025
  • Product Format: PDF (Portable) & Test Engine (Interactive) .
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  • Valid For: Worldwide - Valid In All Countries
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  • Delivery: PDF/Test Engine are Instantly Available for Download
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Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant This Week Results

Tableau-CRM-and-Einstein-Discovery-Consultant Question and Answers

Question # 1

Refer to the graphic.

Question # 1

Which conclusion can be made regarding the strength of the model shown?

Options:

A.  

The model is very strong. A GINI coefficient of .535 shows that this model is very effective.

B.  

The model is pretty good; the accuracy rating of .7597 means we can predict both wins and losses at a fairly high rate.

C.  

The strength of the model cannot be determined with the metrics shown.

D.  

The model is very weak and doesn't provide useful predictions due to the low threshold.

Discussion 0
Question # 2

A training dataset Is being prepared for a Einstein Discovery story. One skewed with outliers. at action should the Einstein consultant take?

Options:

A.  

Remove the outlier rows.

B.  

Nothing, because the field is not the outcome variable.

C.  

Change the method of binning to fixed width.

D.  

Remove the field because it has bad data

Discussion 0
Question # 3

A consultant built a very useful Einstein Analytics app for the corporate Sales Operations team of a company that has multiple Salesforce Ogrs, Each Org has similar models and would like to review their data the way that the corporate Sales Operations team does. The app has been packaged and needs to be installed on the other production orgs.

What is the recommended practice to install the custom template app?

Options:

A.  

Rest API

B.  

Salesforce Managed Package

C.  

Change Sets

D.  

Metadata API

Discussion 0

PDF vs Software Version

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Tableau-CRM-and-Einstein-Discovery-Consultant FAQs

Expect a mix of multiple-choice questions and scenario-based questions in the Salesforce Tableau CRM Einstein Discovery Consultant exam. This means you'll be answering direct questions and also applying your knowledge to specific situations.

To prepare for the exam, divide your time between theoretical study and hands-on practice. Ensure you understand Salesforce Tableau CRM's key concepts and also get practical experience using the platform.

If you need to retake the exam, Salesforce typically allows it, usually with a waiting period and an additional fee. It's important to check their specific policies for details on the number of attempts allowed and any associated costs.

The cost of the Salesforce Tableau CRM Einstein Discovery Consultant exam can vary. It's best to check Salesforce's official website for the most current information regarding the exam fee.

Holding the Salesforce Tableau CRM Einstein Discovery Consultant certification can open up various roles like Salesforce Analyst, Tableau CRM Consultant, and positions in business intelligence and data analytics. This certification is valuable in the Salesforce ecosystem.

Yes, this certification is globally recognized and holds significant value in different regions and markets. It demonstrates expertise in Salesforce Tableau CRM and is respected in the field of business and data analysis.

It measures your skill in building predictive models and insights using Einstein Discovery workflows.

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