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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:

Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

1. A consultant is working with the client to define goals and metrics for an app that will be built. The consultant decides to base the dashboards on personas and is in the design phase prior to starting the actual build.
Which two design considerations should be determined at this time? Choose 2 answers

A) Which colors to use and how to use them
B) Which charts to use to best support the defined goal
C) Which fonts to use for headers and body text
D) How many charts should be allowed on a single dashboard

2. 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
B) flatten
C) ComputeExpression
D) Augment

3. What do Analytics apps do?

A) Use ready-made dashboards to tell easy-to-follow stories about your data
B) Let you create configuration wizards to make Analytics setup easier
C) Let you add new types of charts to Salesforce
D) Alert you when you need a visa for an upcoming trip

4. 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.

Which timeseries statement will fix the query'

A) q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region', seasonality=4);
B) q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year', 'Date_Month". "Y-M"), partition='Region');
C) q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region');
D) q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter', "Y-Q"), partition=Region', ignoreLast=true);

5. Number of queries per user per day

A) 50,000
B) 20,000
C) 1,000
D) 10,000

Solutions: