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Salesforce Certified Tableau CRM and Einstein Discovery Consultant Practice Test - Questions Answers, Page 22

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A Tableau CRM consultant decides to use a recipe to create a new dataset.

Which two source types can be used for the recipe?

Choose 2 answers

A.
Existing datasets
A.
Existing datasets
Answers
B.
Records from a Salesforce object
B.
Records from a Salesforce object
Answers
C.
Dataset lens
C.
Dataset lens
Answers
D.
Connected data(Synced)
D.
Connected data(Synced)
Answers
Suggested answer: A, D

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?

A.
Rest API
A.
Rest API
Answers
B.
Salesforce Managed Package
B.
Salesforce Managed Package
Answers
C.
Change Sets
C.
Change Sets
Answers
D.
Metadata API
D.
Metadata API
Answers
Suggested answer: B

A story created has an AUC of .62.

What two things could be done to possible improve this AUC score?

Choose 2 answers

A.
Segment the training set.
A.
Segment the training set.
Answers
B.
Change the order of the story insights to descending.
B.
Change the order of the story insights to descending.
Answers
C.
Run detect sentiment on the dataflow before creating the story.
C.
Run detect sentiment on the dataflow before creating the story.
Answers
D.
Add more rows of relevant data.
D.
Add more rows of relevant data.
Answers
Suggested answer: B, C

An Einstein Analytics Consultant is working with a subscriptions based company to build a dashboard to understand customer renewals. Each subscription is captured as a Closed Won Opportunity within Salesforce Unfortunately the Opportunity record does not specify whether it is a renewal or a net new subscription.

Which data transformation should be used to determine if a subscription is new or a renewal?

A.
ComputeRelative
A.
ComputeRelative
Answers
B.
ComputeExpression
B.
ComputeExpression
Answers
C.
Augment
C.
Augment
Answers
D.
flatten
D.
flatten
Answers
Suggested answer: D

A Tableau CRM consultant has created three recipes that each produce a dataset.

Recipe1 creates Dataset1.

Recipe2 created Dataset2.

Recipe2 created Dataset3.

Recipe3 is dependent on Dataset1, while Recipe1 and Recipe2 have no dependencies.

How should the consultant implement the recipe schedule?

A.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when Recipe1 has successfully completed.
A.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when Recipe1 has successfully completed.
Answers
B.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when Recipe1 and Recipe2 have successfully completed.
B.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when Recipe1 and Recipe2 have successfully completed.
Answers
C.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when the local Salesforce connector has completed.
C.
Make Recipe1 and Recipe2 time based, but make Recipe3 event based when the local Salesforce connector has completed.
Answers
D.
Make all three recipe time based and schedule all of them at the same time, the data manage will automatically run them in the correct order.
D.
Make all three recipe time based and schedule all of them at the same time, the data manage will automatically run them in the correct order.
Answers
Suggested answer: A

A Tableau CRM 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 recipe to calculate and insert SalesTax to the dataset?

A.
Update
A.
Update
Answers
B.
Transform
B.
Transform
Answers
C.
Append
C.
Append
Answers
D.
join
D.
join
Answers
Suggested answer: B

A consultant has created a story to maximize the daily sales quantity of consumer products in stores. After creating a story, the consulting is presented with this data alert by Einstein Discovery (see graphic).

What are two appropriate actions to take?

Choose 2 answers

A.
Remove the outliers as suggested by Einstein and deploy the model.
A.
Remove the outliers as suggested by Einstein and deploy the model.
Answers
B.
Remove the outliers as suggested by Einstein, and verify using model metrics and story insights if the quality improved.
B.
Remove the outliers as suggested by Einstein, and verify using model metrics and story insights if the quality improved.
Answers
C.
Discuss with the client if values below 0 and above 2,489 are so uncommon that they should perhaps be left out of the story.
C.
Discuss with the client if values below 0 and above 2,489 are so uncommon that they should perhaps be left out of the story.
Answers
D.
Manually remove the sales bellow 0 (negative sales must be a data issue), but keep the large value (the more data, the better the model will be).
D.
Manually remove the sales bellow 0 (negative sales must be a data issue), but keep the large value (the more data, the better the model will be).
Answers
Suggested answer: A, C

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?

A.
Of all promotions types in San Francisco, sales were the highest using Display promotion.
A.
Of all promotions types in San Francisco, sales were the highest using Display promotion.
Answers
B.
Promotions increase sales stronger in San Francisco than they do in other cities.
B.
Promotions increase sales stronger in San Francisco than they do in other cities.
Answers
C.
The best promotion type is Display.
C.
The best promotion type is Display.
Answers
D.
The Other stores (visualized with the gray bars) show no significant data for the sales promotions.
D.
The Other stores (visualized with the gray bars) show no significant data for the sales promotions.
Answers
Suggested answer: B

Your sales team requests that datasets for their dashboards are refreshed every hour. You agree to investigate if this is possible and find that the dashboards use A datasets created from two recipes. The first recipe takes 43 min to run and the second recipe takes 25 min to run.

Is it possible to refresh data every hour?

A.
Yes, the number of recipe runs does not exceed the limit of 60 in a 24 hour rolling period.
A.
Yes, the number of recipe runs does not exceed the limit of 60 in a 24 hour rolling period.
Answers
B.
No, the number of recipe runs exceed the limit of 40 in a 24 hour rolling period.
B.
No, the number of recipe runs exceed the limit of 40 in a 24 hour rolling period.
Answers
C.
No, the total duration of the recipe jobs exceeds one hour.
C.
No, the total duration of the recipe jobs exceeds one hour.
Answers
D.
Yes, with the concurrent recipe runs the duration is less than hour.
D.
Yes, with the concurrent recipe runs the duration is less than hour.
Answers
Suggested answer: B

A consultant is creating a Churn Prediction model to identify customers who are not likely to renew their contract.

What is the appropriate action to take?

A.
Replace nulls in the Churn Reason filed as 'No reason given'',
A.
Replace nulls in the Churn Reason filed as 'No reason given'',
Answers
B.
Exclude active customers (customer who have not churned) from the training dataset since their Churned) from the training dataset since their Churn Reason field are nulls.
B.
Exclude active customers (customer who have not churned) from the training dataset since their Churned) from the training dataset since their Churn Reason field are nulls.
Answers
C.
For the Churn Reason field, enable the ''This variable contains sensitive data'' box because it may contain sensitive customer behavior.
C.
For the Churn Reason field, enable the ''This variable contains sensitive data'' box because it may contain sensitive customer behavior.
Answers
D.
Exclude the Churn reason field from the dataset.
D.
Exclude the Churn reason field from the dataset.
Answers
Suggested answer: C
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