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Salesforce Analytics-Con-201 Exam Syllabus Topics:

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

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100% Pass Quiz 2026 Analytics-Con-201: Salesforce Certified CRM Analytics and Einstein Discovery Consultant Fantastic Complete Exam Dumps

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q57-Q62):

NEW QUESTION # 57
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?

A. Create/Edit a component for the widgets.
B. Create/Edit the widgets individually on each dashboard.
C. Create/Edit a lens and add each dashboard.

Answer: A

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 # 58
In a dataset, there are multiple boolean fields. When displayed on any dashboard, the boolean fields should all be displayed in the same way: a value of true should result in the display of the word "Yes" in green; a value of false should result in the display of the word "No" in red.
How should the consultant accomplish this?

A. Create an XMD node in the recipe to change the label and color of the values in the fields.
B. Select the boolean fields in the explorer's field panel, select the boolean fields, then create a derived dimension.
C. In the explorer's field panel, select the boolean fields and use the "edit values" option on the fields to change values and colors.

Answer: C

NEW QUESTION # 59
CRM Analytics team is asked to build a Service Analytics dashboard for the service agents.
What are the main "Deep Design Thinking" principles the team should keep in mind during the discovery sessions?

A. Clarity - Efficiency - Consistency
B. Purpose - Structure - Surface
C. Priority - Logic - Level of Granularity

Answer: B

NEW QUESTION # 60
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?

A. Root Mean Square Error, Minimum Square Error
B. Area Under Curve, Confusion Matrix
C. Area Under Curve, R2 (R-squared)

Answer: A

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 # 61
A CRM Analytics consultant is performing column profiling on dimension column in a recipe. Newly-added rows are not being considered in the Results tab of theprofile even though a sync wasrun for that specific object.
What is causing the issue?

A. Sync operation has not run properly with the new dimension column in the recipe.
B. The sample does not include changes to the connected object data within the last 24 hours.
C. Column profiling Is not applicable on a dimension column in a recipe.

Answer: B

NEW QUESTION # 62
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