Online Access Free Salesforce.CRM-Analytics-and-Einstein-Discovery-Consultant.v2025-09-25.q109 Practice Test (Page 22)

CRM-Analytics-and-Einstein-Discovery-Consultant Exam Question 101

A CRM Analytics consultant is working on Sales dashboards with multiple datasets and advanced queries in the Sales Analytics app.
Sales managers in the organization have been given Editor/Manager access to the app, whereas sales reps have been given Viewer access.
Some dashboards that are in progress are not ready to be rolled out to sales reps and should only be viewable by sales managers.
How should the consultant accomplish this?

A.Remove the dashboard from the 'Run App' navigation list so the sales reps cannot navigate to these dashboards.

B.Leverage the CRM Analytics asset visibility feature to hide the assets from the users.

C.Duplicate the dashboards and their respective datasets, and move the assets to a separate app for the sales rep.

CRM-Analytics-and-Einstein-Discovery-Consultant Exam Question 102

The Vice President of Sales wants to create a "Pipeline Trending" dashboard in Einstein Analytics that displays specific colors depending on the values of the fields.
Which two techniques can a consultant use to help address this requirement? Choose 2 answers

A.Use SAQL queries to calculate a color field and assign it to each field value.

B.Use a compute Expression to calculate a color field and assign it to each field value.

C.Use the "fields" menu when exploring the dataset and assign colors to each field value.

D.Use an XMD file and assign colors to each field value.

CRM-Analytics-and-Einstein-Discovery-Consultant Exam Question 103

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.

B.Remove the outliers as suggested by Einstein, and verify using model metrics and story insights if the quality improved.

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.

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).

CRM-Analytics-and-Einstein-Discovery-Consultant Exam Question 104

Which timeseries statement will fix the query?

A.q= timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols= ('Date_Year', 'Date Quarter', "Y-Q"), partition='Region', seasonality=4);

B.q = timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols= ('Date_Quarter', 'Date_Month', "Q-M"), partition='Region', ignoreLast=true);

C.q = timeserles q generate 'sum_Sales' as 'Forecasted_Sales' with (length=12, dateCols=("Date_Year', 'Date_Month', "Y-M"), partition='Region');

CRM-Analytics-and-Einstein-Discovery-Consultant Exam Question 105

To model customer value, a consultant decided to aggregate the amount ($) individual customers spent over a 2-year span.
With reference to the outcome variable, which action should the consultant take?

A.Select to minimize the outcome variable.

B.Create five bins or revenue, ranging from very high Value, High Value, Average Value, Low Value, and Very Low Value in data prep.

C.Create five bins of revenues, ranging from Very High Value, high Value, average Value, Low Value, and very Low Value in dataflow.

D.Select the option: Are you expecting a whole number greater than or equal to 0?

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