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Salesforce Analytics-Con-201 Exam Syllabus Topics:

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

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q113-Q118):

NEW QUESTION # 113
A consultant wants to understand what the important predictors are in a model.
Where is this information found?

A. Model Settings
B. Einstein Recommendations
C. Model Deployment Wizard

Answer: A

Explanation:
The important predictors of a model in CRM Analytics can typically be found under theModel Settings. This area provides detailed information about the configuration and the inputs (predictors) used to train the model.
Insights into which predictors have the most significant impact on the model's outcomes can be gleaned from this section, enabling a deeper understanding of the model's internal workings and the factors driving predictions.

NEW QUESTION # 114
A consultant has been asked to build and embed a dashboard in a Lightning page. Users should only be able to change the dashboard contrast and open Analytics Studio from the header of the dashboard.
How should the consultant achieve this?

A. Deselect the "Show Share Icon" and "Enable Subscriptions" buttons.
B. Deselect the "Enable Notifications" and "Enable Subscriptions" buttons.
C. Deselect the "Enable Notifications" and "Enable Email" buttons.

Answer: B

NEW QUESTION # 115
A system administrator and a CRM Analytics consultant are working together on deploying arecipe/dataflow and a dataset to another org. Prior to this deployment, a package was deployed with all the custom fields used in the dataflow and dataset.
While running the recipe/dataflow in the target environment, the consultant encounters multiple errors related to these custom fields.
How should this be resolved?

A. Check whether the Analytics Integration user has been provided access to these custom fields on the target org.
B. Check whether the system administrator has been provided access to these custom fields on the target org.
C. Check whether the consultant has been provided access to these custom fields on the target org.

Answer: A

NEW QUESTION # 116
For a story created using multiple data sources (Salesforce, CSV, and external data), what is a possible fix for the issue shown in the prediction?

A. Deploying without connecting to a Salesforce object.
B. Adding actionable variables to the model.
C. Creating a supplementary dataset and utilizing dataset joins.

Answer: C

Explanation:
A supplemental dataset is appropriate when an Einstein Discovery model requires predictor information that is not available directly on the Salesforce object used for scoring. During model deployment, CRM Analytics allows supplemental datasets to provide external data, computed fields, or other required model variables. The supplemental dataset is associated with the Salesforce object through corresponding record-ID fields, allowing the additional predictor values to be supplied when predictions are generated. This directly addresses the missing-field situation shown in the exhibit. Deploying without connecting to a Salesforce object is intended primarily when the model does not depend on a Salesforce object, while actionable variables determine which variables Einstein can recommend changing to improve an outcome; they do not supply missing predictor data. Therefore, creating and associating a supplemental dataset is the appropriate solution.

NEW QUESTION # 117
A system administrator at Cloud Kicks creates a joined report to showcase the new business deals closing in the current quarter, which was well received by the business stakeholders. A manager wants to visualize this report on CRM Analytics.
The CRM Analytics consultant determines the report can be trended on CRM Analytics, but it's not working as expected.
What is causing the issue?

A. Trending dashboards cannot be created from joined reports.
B. The Analytics Integration user did not have permission to view the report on Salesforce.
C. The Salesforce report was filtered on quarterly data which meant it did not have enough data to trend on CRM Analytics.

Answer: A

NEW QUESTION # 118
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