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Latest CRM-Analytics-and-Einstein-Discovery-Consultant Exam Cram - Positive CRM-Analytics-and-Einstein-Discovery-Consultant Feedback

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Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant Exam Syllabus Topics:

Topic
Details

Topic 1

Security: Consultants stepping into this section will showcase their prowess in implementing necessary security settings. It covers critical aspects such as suitable dataset security settings, and the ability to implement app sharing.

Topic 2

Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.

Topic 3

Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.

Topic 4

Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.

Topic 5

Admin
Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync
dataflows
recipe limits.

>> Latest CRM-Analytics-and-Einstein-Discovery-Consultant Exam Cram <<

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q28-Q33):

NEW QUESTION # 28
Universal Containers has a well-defined role hierarchy in Salesforce where everyone is assigned to an appropriate node. The accounts within their instance are categorized by their demography.
An individual sales rep should be able to view all accounts that they own. In addition, sales reps should be able to see any accounts where the value of the account demography matches the demography defined on their user record. A user could have more than one demography defined on their user record.
To meet this requirement, the CRM Analytics consultant has set up a security predicate of the existing
'Account' dataset as follows:

This, however, does not seem to be working as expected.
What is causing the issue?

A. The security predicate needs to be updated as 'Ownerld' == "sUser.id" || 'Demography' = "$User.
Demographic__c'.
B. The Sales Rep is not provided access permission on custom field Demographic__c on the User object.
C. The Analytics Security User is not provided access permission on custom field Demographic_c on the User object.

Answer: B

Explanation:
The issue with the security predicate not functioning as expected likely stems from a permissions issue related to the custom field Demographic__c on the User object. Here's a detailed explanation:
* Field-Level Security: If the sales reps do not have access to the Demographic__c field, the security predicate which references this field cannot execute properly as the system cannot evaluate the predicate without accessing the field.
* Permission Settings: Ensuring that the sales reps have the necessary permissions to view and use the Demographic__c field is crucial for the security predicate to function correctly.
* Data Visibility: The security model in CRM Analytics relies heavily on the underlying data permissions in Salesforce. If these permissions are not correctly configured, the expected data visibility through CRM Analytics will not be achieved.

NEW QUESTION # 29
A team of CRM Analytics developers has been working on an existing recipe to add new derived fields. The edited version has been failing ever since, and management is requesting that the dashboard show refreshed data while they work on the edits.
How can the developers add new fields while keeping the dataset refreshed?

A. A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.
B. Refresh the dataset after working hours to avoid the edited version from failing.
C. Clone the existing recipe to add fields and roll back the original recipe to the last working version.

Answer: C

Explanation:
When faced with the need to continue refreshing data while developing new features in a recipe, the best practice is:
Clone the Existing Recipe: By cloning the recipe, developers can experiment with adding new fields and transformations without affecting the production data flow. This allows for testing and development in a sandbox-like environment.
Roll Back to a Stable Version: Rolling back the original recipe to the last stable version ensures that the production dashboards continue to receive refreshed data, maintaining business operations without disruption.
This approach not only ensures data continuity but also provides a safe environment to address any issues that may arise from new developments.

NEW QUESTION # 30
A customer is reviewing a story that is set to maximize the daily sales quantity of consumer products in stores, and the customer sees chart related to promotional activities and to San Francisco specifically.
What conclusion can be drawn from this insight?
What conclusion can be drawn from this Insight?

A. Promotions increase sales stronger in San Francisco than they do in other cities.
B. The best promotion type is Display.
C. Of all promotions types in San Francisco, sales were the highest using Display promotion.
D. The Other stores (visualized with the gray bars) show no significant data for the sales promotions.

Answer: A

NEW QUESTION # 31
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 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,
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 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".

Answer: C

Explanation:
In addressing the requirements of Universal Containers to ensure proper visibility of order data across different levels of the sales hierarchy, the use of a security predicate based on role hierarchies is paramount.
Here's why Option B is the ideal approach:
* Flatten Operation on Role Hierarchy: This operation is essential as it allows for the creation of a simplified or "flattened" view of the hierarchical relationships within the organization. This flattened view enables the dataset to understand and respect the hierarchical structure in security implementations.
* Creating a Multi-value Attribute ('ParentRoleIDs'): By creating this attribute, the recipe can hold multiple role IDs that a particular user has visibility permissions for. This is crucial in a hierarchical organization like UC where data visibility needs to cascade down the hierarchy.
* Security Predicate: The predicate ('ParentRoleIDs' == "$User.UserRoleld" || 'TeamMember.Id' ==
'$User.Id' || 'Ownerld' == "$User.Id") effectively enforces that:
* A user can see all orders where their role matches any of the role IDs in the 'ParentRoleIDs' list (hierarchical visibility).
* A user can see all orders where they are specifically listed as a team member.
* A user can see all orders where they are the owner.
This approach aligns with best practices for implementing row-level security in CRM Analytics, ensuring data visibility is managed correctly according to the defined organizational hierarchy and individual data ownership.

NEW QUESTION # 32
Cloud Kicks uses CRM Analytics for its sales reporting. A new manager needs access to CRM Analytics to see specific dashboards.
How should the system administrator give access to the Analytics
Studio app in the App Launcher?

A. Assign the CRM Analytics User permission set to the manager's user.
B. Change the profile of the user to one that has access to the Analytics Studio.
C. Share the Analytics Studio app to the user's profile.

Answer: A

NEW QUESTION # 33
......

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