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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions:

1. Universal Containers has a dashboard for sales managers that want to visualize their win rate.
Which chart type should the consultant use to keep track of targets?

A) Gauge
B) Metric Radar
C) Line

2. A model created with a GLM algorithm produced unsatisfactory results.
When re-running the model, which type of algorithm should the consultant use to improve the results?

A) Support Vector Machines
B) XGBoost
C) K-Nearest Neighbors

3. consultant is reviewing a model that is set to maximize the daily sales quantity of consumer products in stores, and they see this recommendation.

Which action should the consultant take?

A) Remove the Store field from the model definition, because that is the recommended action.
B) Ignore alert; the explanation of variation is only 35%, which is below 50%,
C) Verifyclient expectations that Store is a strong predictor for daily sales quantity.

4. Which capability can a consultant use if "Deploy without connecting to a Salesforce Object" is selected while deploying the model?

A) Predict Function in Salesforce flows
B) Einstein Predictions Component score
C) No-Code Writeback to SFDC objects

5. Universal Containers (UC) is rolling out CRM Analytics to its field sales that include dashboards withorder data from an external source.
UC has a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy. In addition, the order data has a reference to a Salesforce opportunity.
An individual sales rep should be able to view all orders that they own or as part of the account team or opportunity team. The sales manager should be able to view all orders for the entire sales team. Similarly, the VP of sales should be able to view orders for everyone who rolls up in that hierarchy.
The dataset has a field called Ownerld which represents the order owner.
Given this information, how should a CRM Analytics consultant implement the above requirements?

A) As part of the recipe, use the flatten operation on the role hierarchy, create a multi-value attribute called
'ParentRoleIDs' on the dataset, and apply the following security predicate: 'ParentRoleIDs' == "$User.
UserRoleld" || 'TeamMember.Id' '$User, Id" || 'Ownerld' == "$User.Id".
B) As part of the recipe, use a multi row formula on the Roleld field to create an attribute called
'ParentRoleIDs' on the dataset, and apply the following security predicate:"$User.UserRoleld" ||
'Ownerld' == "$User.Id".
C) As part of the recipe, use a formula on the Roleid fildto create an attribute called 'ParentRolelDs' on the dataset, and apply the following security predicate: 'ParentRolelDs' ==''$UserRoleId'' || Owned\ ==
'$User,id\\,

Solutions: