Salesforce CRM Analytics and Einstein Discovery Consultant Quiz 1 Topic 4 Questions 1-5

Question: 1

Refer to the graphic.

q1_CRM Analytics and Einstein Discovery Consultant

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

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

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

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

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

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Question: 2

What is another name for the type of insight that examines how one variable explains variation of the outcome variable?

AThird-order analysis

BObject-oriented analysis

CSecond-order analysis

DFirst-order analysis

ESpectrum analysis

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Question: 3

A consultant wants to understand what the important predictors are in the story.

What are two places where this information can be found?

Choose 2 answers

AIn the Einstein Recommendations for story improvement. If there are no recommendation to remove strongest predictors, the story doesn't hold any Important predictors but only weak (probably unrelated) terms.

BIn the Story Settings, where the strength of predictor fields is calculated and visualized. The consultant can sort the list of predictor fields accordingly.

CIn the Model Deployment Wizard while selecting the actionable fields

DIn the Model Metrics section, where the top predictors are listed

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Question: 4

Default rows in values table

A100

B200

C50

D75

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Question: 5

The client is trying to create a SAQL step to predict sales in each sales region. They cannot get the query to return any results, but have identified that the error is in the time series statement. They have asked an Einstein Consultant to review the following query and fix any errors.

q5_CRM Analytics and Einstein Discovery Consultant

Which timeseries statement will fix the query'

Aq = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter', 'Y-Q'), partition=Region', ignoreLast=true);

Bq = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year', 'Date_Month'. 'Y-M'), partition='Region');

Cq = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', 'Y-Q'), partition='Region', seasonality=4);

Dq = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', 'Y-Q'), partition='Region');

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Salesforce CRM Analytics and Einstein Discovery Consultant Quiz:1 Topic:4 Questions:1-5