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Tableau-CRM-and-Einstein-Discovery-Consultant Exam Dumps - Salesforce Consultant Questions and Answers

Question # 64

An Einstein Analytics team wants to create a dashboard using two standard Salesforce objects. The dashboard should display data from the Case object, along with related data from the Account object. Which two processes can achieve this?

Options:

A.

Extract data from the case and account objects using "sfdcDigest" transformation, Q use "append" transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset

B.

Extract data from the case and account objects using an ETL tool, use the ETL tool to y/ Q join account and case data, and then upload the data to Einstein Analytics. Build a dashboard using the ETL generated dataset

C.

Extract data from the case and account objects using "sfdcDigest" transformation, y/ Q use "augment" transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset

D.

Extract data from the case and account objects using "dataloader", create a CSV file Q with account and case data, and then upload the CSV as a dataset to Einstein Analytics. Build a dashboard using that dataset

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Question # 65

A consultant is asked to configure a user to view a dashboard, within a designated app, without the ability to create and save lenses. After adding the user to the app, which action should the consultant take to implement this requirement?

Options:

A.

Assign the Editor role to the user.

B.

Assign the Viewer role to the user.

C.

Ensure the user has the Use Analytics permission.

D.

Assign the Manager role to the user.

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Question # 66

The Universal Containers Einstein Analytics team built a dashboard with two widgets:

1. List widget associated to the step "Type_2" and grouped by the dimension "Type" (multi-selection)

2. Pie chart widget associated to the step "Step_pie_3" and grouped by the dimension "Type"

The team wants to use bindings so any selection in the List widget will filter the Pie chart.

Additional notes:

* The steps use different datasets.

* Users should be able to choose more than one Type (multi-selection).

What is the right syntax for the binding?

A)

B)

C)

D)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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Question # 67

Refer to the graphic.

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.

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Question # 68

A customer is reviewing a story that is set to maximize the daily sales quantity of consumer products in stores, and the customer sees chart related to promotional activities and to San Francisco specifically.

What conclusion can be drawn from this insight?

What conclusion can be drawn from this Insight?

Options:

A.

Of all promotions types in San Francisco, sales were the highest using Display promotion.

B.

Promotions increase sales stronger in San Francisco than they do in other cities.

C.

The best promotion type is Display.

D.

The Other stores (visualized with the gray bars) show no significant data for the sales promotions.

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Question # 69

Which of these is not a method for controlling record-level access?

Options:

A.

Profiles

B.

Sharing Rules

C.

Organization-Wide Defaults

D.

Role Hierarchy

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Question # 70

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

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Question # 71

In a story investigating margin, large variations between product groups are dominating the story. Which action might an Einstein Consultant take to resolve this?

Options:

A.

Add more data to the dataset.

B.

Normalize the margin by product group.

C.

Eliminate extreme values in the dataset.

D.

Run separate stories for each region.

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Question # 72

A story has been deployed to the Opportunity object with a prediction field, Predicted Amount.

How can all the Opportunity records be predictions written back to the Predicted Amount field?

Options:

A.

Mass edit all the records by populating the Predicted Amount field.

B.

Use the Prediction Service API to get the prediction and populate the Predicted Amount field.

C.

Enable a Bulk Scoring Job under the Prediction Definition.

D.

Open all Opportunity records.

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Question # 73

The Universal Containers company plans to upload target data from an external tool to Einstein Analytics so they can calculate the Sales team target attainments.

The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales representative, the target amount, and the month of the target. For each sales representative, the file contains a target for every month of the current year as well as all previous years.

Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?

Options:

A.

Update

B.

Append

C.

Overwrite

D.

Upsert

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Exam Name: Salesforce Tableau CRM Einstein Discovery Consultant (SU24)
Last Update: Feb 20, 2025
Questions: 239
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