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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Analytics Dashboard Design20%- Design and build CRM Analytics dashboards
  • 1. Apply design best practices
  • 2. Use Lenses and Dashboards
  • 3. Describe the use cases for Visualforce and Lightning components
Topic 2: Analytics Dashboard Configuration25%- Configure dashboards
  • 1. Set up dynamic dashboards
  • 2. Apply query filters
  • 3. Configure bindings
Topic 3: Einstein Discovery20%- Describe Einstein Discovery concepts
  • 1. Identify the use cases for Einstein Discovery
  • 2. Explain the model building process
  • 3. Interpret model results
- Implement Einstein Discovery
  • 1. Configure and deploy Einstein Discovery models
  • 2. Integrate predictions into CRM Analytics dashboards
Topic 4: Data Layer25%- Implement and configure the right data transformations
  • 1. Use Data Prep actions
  • 2. Identify and resolve data sync issues
- Identify the right data sources and data flows for CRM Analytics
  • 1. Define datasets
  • 2. Describe how Salesforce objects map to CRM Analytics
  • 3. Describe use cases for Data Prep (Dataflows and Recipes)
Topic 5: Security10%- Determine security and sharing settings
  • 1. Describe how Salesforce security is applied in CRM Analytics
  • 2. Implement row-level security

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

NEW QUESTION # 113
CRM Analytics consultant receives a new project from a client that wants to implement CRM Analytics. They do not currently have CRM Analytics but want guidance on how to ensure their users have the correct access.
They have 1,000 users with a small team of three people who will build both datasets and dashboards. An additional 15 people should be able to only create dashboards. The remaining users should only be able to view dashboards.
Which recommendation should the consultant give the client?
Which recommendation should the consultant give the client?

Answer: C

Explanation:
For a client implementing CRM Analytics with a variety of user roles, creating and assigning Salesforce permission sets is the most flexible and scalable solution. Here's why:
* Flexibility and Customization: Permission sets allow for specific access rights to be compiled and assigned based on user roles without altering their existing profiles.
* Scalability: As the organization grows or roles change, permission sets can be easily adjusted or reassigned to accommodate new requirements or users.
* Simplified Management: Managing access via permission sets simplifies the administration of user rights, making it easier to ensure that each group has the appropriate level of access.


NEW QUESTION # 114
The marketing team at Cloud Kicks has five dashboards in an app. Four widgets are replicas of each other in three of the dashboards.
What is the best way to maintain these widgets?

Answer: B

Explanation:
To maintain consistency and ease of updates across multiple dashboards, creating or editing a component for the widgets is the most effective method. This approach:
Efficiency in Updates: Allows changes to be made in one place, which automatically propagates to all instances where the component is used across dashboards.
Consistency: Ensures uniformity in the appearance and functionality of the widgets across different dashboards.
Simplicity: Reduces the need for redundant work, where each widget would otherwise need to be updated individually.


NEW QUESTION # 115
CRM Analytics uses permissions of the Integration User to extract data from Salesforce objects and fields when a dataflow/recipe job runs.
Why should a consultant be cautious while syncing objects and fields containing sensitive data?

Answer: B


NEW QUESTION # 116
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?

Answer: B

Explanation:
Upon reviewing the data model and noticing the high correlation alert between 'Store' and daily sales quantity, the appropriate action is to verify with the client their expectations regarding the influence of the Store field on daily sales. Here's the rationale:
* Understanding the Role of 'Store' in the Model: Before making any changes to the model, it's crucial to understand whether the 'Store' field is expected to be a strong predictor based on the business context. If the client expects that different stores inherently have different sales volumes due to factors like location, size, or customer base, this correlation may be both meaningful and desired.
* Potential Data Leakage: High correlation warnings can sometimes indicate data leakage, where a predictor (like 'Store') might inadvertently include information about the outcome variable (daily sales quantity). It's essential to verify whether this correlation makes sense logically or if it's skewing the model predictions.
* Client Consultation: Consulting with the client helps ensure that any modeling decisions align with their business knowledge and expectations. It's about validating the model against real-world expectations and ensuring it remains a useful tool for decision-making.
By taking these steps, the consultant not only adheres to best practices in data science by validating model inputs and their implications but also ensures that the model aligns with the client's business strategies and operational realities.


NEW QUESTION # 117
A CRM Analytics consultant is updating an existing recipe.
They are looking to add a few additional fields onto the Account dataset. One of the fields to be added is a multi-select picklist field that needs to be shown as text on the dashboard.
What should the consultant do to accomplish this?

Answer: A


NEW QUESTION # 118
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