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Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant Exam With Confidence Using Practice Dumps

Exam Code:
Tableau-CRM-and-Einstein-Discovery-Consultant
Exam Name:
Salesforce Tableau CRM Einstein Discovery Consultant (SU24)
Certification:
Salesforce Consultant
Vendor:
Salesforce
Questions:
239
Last Updated:
Dec 5, 2025
Exam Status:
Stable
Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant

Tableau-CRM-and-Einstein-Discovery-Consultant: Salesforce Consultant Exam 2025 Study Guide Pdf and Test Engine

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Salesforce Tableau CRM Einstein Discovery Consultant (SU24) Questions and Answers

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Question 1

A company used Einstein Analytics to create two datasets:

1. "Opportunity With Account- dataset, which contains data from the Opportunity standard object augmented by the Account data.

2. "Case with Account" dataset. which contains data from the Case standard object augmented by the Account data.

The company wants to build a lens showing the total number of Opportunities and Cases per Account. How can a consultant help them build this lens'

Options:

A.

Create a recipe to generate a new dataset from the "OpportunityWithAccount" and "CaseWithAccount" datasets aggregated by Account, and use the generated dataset in a lens.

B.

Use "Compare Table" to join the "OpportunityWithAccount" and "CaseWithAccount" datasets using the "Accountld" and then aggregate by Account.

C.

Set up Connect Data Sources in the UI between the "OpportunityWithAccount" and "CaseWithAccount" datasets.

D.

Use a SAQL query to group and join the "OpportunityWithAccount" and "CaseWithAccount" datasets then generate the results.

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Question 2

An Einstein Analytics consultant is asked to add a new SalesTax field to a Product Sales dataset. The formula to calculate SalesTax is (SubTotal'CountyTax).

Which node should the consultant use in a Dataflow to calculate and insert SalesTax to the dataset?

Options:

A.

append

B.

computeExpression

C.

augment

D.

computeRelative

Question 3

The Universal Containers company used Einstein Analytics to create two datasets:

Dataset A: contains a list of activities with an "activitylD" dimension and a "userlD" dimension Dataset B: contains a list of users with a "userlD" dimension

The team wants to delete from Dataset A all activities related to users in Dataset B.

How can an Einstein Consultant help them achieve this?

Options:

A.

Use the dataflow transformation "delete" and set "userlD" as the deletion ID.

B.

Use a combination of dataflow transformations: "augment" and "filter."

C.

Use an external ETL tool to extract both datasets and delete records.

D, Use the recipe operation "delete" and set "userlD" as the deletion ID.

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