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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Dashboard Design & Development25%- Build & Configure Dashboards
  • 1. Implement bindings, filters, and interactions
  • 2. Create lenses, steps, and visualizations
  • 3. Use SAQL for advanced queries
- Design Principles
  • 1. Design for mobile and Lightning compatibility
  • 2. Apply best practices for usability and performance
Data Layer23%- Data Management & Optimization
  • 1. Implement data modeling and relationships
  • 2. Resolve data sync and refresh issues
  • 3. Optimize dataset performance
- Data Sources & Integration
  • 1. Extract, load, and prepare data using Data Manager
  • 2. Use Dataflows and Recipes for transformation
  • 3. Define datasets and map Salesforce objects
Security & Access12%- Sharing & Permissions
  • 1. Manage user and group access
  • 2. Implement row-level security and inheritance
  • 3. Configure app, dataset, and field-level security
Einstein Discovery22%- Model Building & Configuration
  • 1. Select prediction type: numeric, binary, multi-class
  • 2. Prepare and assess data for modeling
  • 3. Train, evaluate, and refine models
- Deployment & Usage
  • 1. Embed predictions in dashboards and Lightning pages
  • 2. Interpret results and recommendations
  • 3. Monitor and maintain model performance
Analytics Administration & Deployment18%- 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 (Q29-Q34):

NEW QUESTION # 29
Universal Containers has a single dataset that contains the attainment and commission fields for all sales reps.
Each sales rep should be able view the attainment data for each rep in their division. Each repshould only be able to see their own commission data.
Which option should a CRM Analytics consultant use to enforce this requirement?

Answer: A


NEW QUESTION # 30
A CRM Analytics consultant has been asked to refactor a dashboard so that it loads quicker. After some analysis, the consultant found that most of the dashboard queries run in less than 5 seconds; however, the Opportunities Table takes more time to load when scrolled down from its initial view.
How should the consultant improve the performance of this dashboard?

Answer: B

Explanation:
Reference:CRM Analytics Dashboard Optimization


NEW QUESTION # 31
AW Computing will start using Tableau Online to report on some of its Salesforce data to users who do NOT have an SFDC license.
What is the first step the CRM Analytics consultant should take?

Answer: C


NEW QUESTION # 32
A CRM Analytics consultant has been tasked with providing access to CRM Analytics for a few users. They should be able to view the data but unable to export it.
Which permission should the consultant make sure to NOT include?

Answer: B


NEW QUESTION # 33
The below image shows a numeric outcome being deployed (Regression).

Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?
The below image shows a numeric outcome being deployed (Regression).
Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?

Answer: B

Explanation:
In the context of a regression model being deployed, the performance metrics used to evaluate its effectiveness in production typically include:
* Root Mean Square Error (RMSE): This metric provides a measure of the average magnitude of the errors between predicted values by the model and the actual values, giving a sense of how accurately the model predicts the outcome.
* Minimum Square Error: While less commonly referenced as "Minimum Square Error", metrics like Mean Squared Error (MSE) are often used to quantify the average of the squares of the errors- essentially, the average squared difference between the estimated values and what is estimated.
These metrics are crucial for assessing the performance of regression models in CRM Analytics, as they directly reflect the accuracy and reliability of the model's predictions in real-world applications.


NEW QUESTION # 34
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