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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Layer	23%	- Data Management & Optimization 1. Implement data modeling and relationships 2. Optimize dataset performance 3. Resolve data sync and refresh issues - Data Sources & Integration 1. Use Dataflows and Recipes for transformation 2. Define datasets and map Salesforce objects 3. Extract, load, and prepare data using Data Manager
Topic 2: Einstein Discovery	22%	- Deployment & Usage 1. Interpret results and recommendations 2. Monitor and maintain model performance 3. Embed predictions in dashboards and Lightning pages - Model Building & Configuration 1. Select prediction type: numeric, binary, multi-class 2. Prepare and assess data for modeling 3. Train, evaluate, and refine models
Topic 3: Dashboard Design & Development	25%	- Design Principles 1. Apply best practices for usability and performance 2. Design for mobile and Lightning compatibility - Build & Configure Dashboards 1. Create lenses, steps, and visualizations 2. Implement bindings, filters, and interactions 3. Use SAQL for advanced queries
Topic 4: Security & Access	12%	- Sharing & Permissions 1. Manage user and group access 2. Implement row-level security and inheritance 3. Configure app, dataset, and field-level security
Topic 5: Analytics Administration & Deployment	18%	- Implementation & Maintenance 1. Manage versioning and deployment 2. Monitor and optimize query performance 3. Use Dashboard Inspector and Publisher

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q16-Q21):

NEW QUESTION # 16
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 Analytics Security User is not provided access permission on custom field Demographic_c on the User object.
C. The Sales Rep is not provided access permission on custom field Demographic__c on the User object.

Answer: C

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 # 17
The CRM Analytics consultant at Universal Containers notices that some users have access to sensitive data and dashboards they should not have access to in the Manager's app.
How should the consultant fix the problem?

A. Develop separate dashboards and datasets and put them in the Manager's app.
B. Create separate apps, datasets, and dashboards, and share them with the proper users.
C. Apply data encryption using Salesforce Shield.

Answer: B

Explanation:
Reference:Managing Data Access and Sharing in CRM Analytics

NEW QUESTION # 18
A CRM Analytics consultant is asked to make changes to the current sales dashboard at Cloud Kicks. The dashboard is crucial to track the daily sales performance of the company and needs to be available for other users while the consultant works on the changes.
How should the consultant proceed to update the dashboard?

A. Self assign as a dashboard publisher and make the changes to the dashboard in draft mode while maintaining a previous version live.
B. Clone the dashboard to a new one, apply the changes, share the new dashboard with the users, and delete the old one.
C. Wait for a period of least usability or the dashboard to edit it.

Answer: A

NEW QUESTION # 19
What is a benefit of introducing a second local connector?

A. Better deployment management between sandboxes and production environment
B. Better performance by syncing data according to the refresh necessities
C. Better maintenance by having a connector per recipe

Answer: B

Explanation:
Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.
Reference: Best practices for managing connectors and optimizing data sync performance can be found in theCRM Analyticsperformance optimization guides.

NEW QUESTION # 20
After the initial creation of a model, the first model insight explains
93% of the variation of the outcome variable. This is unusually high.
What is the most likely reason for this?

A. The dataset contains multiple dominant values.
B. The outcome variable may be causing data leakage.
C. The model contains too many outlier values.

Answer: B

NEW QUESTION # 21
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