Salesforce exams4sure complete Analytics-con-201 Materials by Liana q104 vce pdf

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Salesforce Analytics-Con-201 Exam Overview :

Exam Name:	Salesforce Certified CRM Analytics and Einstein Discovery Consultant
Exam Code:	Analytics-Con-201 Dumps
Vendor:	Salesforce	Certification:	Salesforce Consultant
Questions:	116 Q&A's	Shared By:	liana

Question 32

After getting approval for the dashboard layout design for a desktop, the CRM Analytics consultant is ready to start the design process for a mobile layout.

Which consideration should the consultant keep in mind?

Options:

Create a layout with the property “phone” to show the dashboard on the mobile app similar to creating a layout with the property “dashboard”to show on the desktop for thesame dashboard,

If no layouts are eligible for the mobile device, an error message will be displayed but the dashboard will still be visible on the desktop without errors.

“Tablet” or “Phone” layout—where only minWidth and maxWidth have been set—may be displayed on a desktop if the dashboard is embedded in asmall frame, or if the browserwindow is small.

Discussion

Question 33

Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.

How should CK achieve this?

Options:

An SAQL query with a timeseries statement specifying Opportunity Name as the partition and Y-M-W as the Date Cols

An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W as the Date Cols

An SAQL query with @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols

Discussion

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Question 34

A consultant is preparing a dataset to predict customer lifetime value and is collecting data from a questionnaire that asks for demographic information. A very small number of respondents fill in the Income box, but the consultant thinks that it is an informative column even though it only represents 1% of respondents.

What should the consultant do?

Options:

Fill in the missing data with an average of all incomes.

Apply the predict missing values transformation in recipe nodes.

Drop the field as it will be difficult to get future respondents.