Salesforce Analytics-Con-201 Latest Real Test | Exam Analytics-Con-201 Pass Guide

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Analytics Administration & Deployment18%- Implementation & Maintenance
  • 1. Use Dashboard Inspector and Publisher
  • 2. Manage versioning and deployment
  • 3. Monitor and optimize query performance
Topic 2: Dashboard Design & Development25%- Build & Configure Dashboards
  • 1. Create lenses, steps, and visualizations
  • 2. Use SAQL for advanced queries
  • 3. Implement bindings, filters, and interactions
- Design Principles
  • 1. Design for mobile and Lightning compatibility
  • 2. Apply best practices for usability and performance
Topic 3: Data Layer23%- Data Management & Optimization
  • 1. Optimize dataset performance
  • 2. Implement data modeling and relationships
  • 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 4: Security & Access12%- Sharing & Permissions
  • 1. Implement row-level security and inheritance
  • 2. Configure app, dataset, and field-level security
  • 3. Manage user and group access
Topic 5: Einstein Discovery22%- Model Building & Configuration
  • 1. Select prediction type: numeric, binary, multi-class
  • 2. Train, evaluate, and refine models
  • 3. Prepare and assess data for modeling
- Deployment & Usage
  • 1. Interpret results and recommendations
  • 2. Embed predictions in dashboards and Lightning pages
  • 3. Monitor and maintain model performance

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Exam Analytics-Con-201 Pass Guide - Analytics-Con-201 Latest Dumps Questions

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q70-Q75):

NEW QUESTION # 70
Cloud Kicks (CK) wants to use CRM Analytics to analyze trends of its sales pipeline in order to accelerate the company's sales process. To do so, CK needs to know the average time an opportunity spends in each stage. The data can be found in the Opportunity History object, but the value is not pre- calculated in Salesforce, so a consultant recommends using a recipe to calculate it.
How should the consultant use a recipe to calculate the average time an opportunity spends in each stage?

Answer: C


NEW QUESTION # 71
A user is able to access the dashboards, lenses, and datasets of a particular app but is unable to change the name of the specific app.
What is causing the issue?

Answer: B

Explanation:
In CRM Analytics, the ability to modify the name of an app or make other significant changes typically requires Manager access. This level of access is distinct from Editor or Viewer permissions, which may allow for modifications to contents within the app but not to the app's core properties like its name. Here's the reasoning:
* Access Restrictions: Manager access is specifically designed to control structural changes within the app, including renaming the app, which is considered a higher privilege operation.
* Role-Based Access Control: This ensures that only users with the necessary permissions can make significant changes, protecting the integrity and configuration of the app.
Ensuring users have the appropriate level of access based on their responsibilities is a fundamental aspect of managing security and functionality in CRM Analytics.


NEW QUESTION # 72
CRM Analytics users at Cloud Kicks are granted access to an app with specific dashboards. When trying to download a specific widget, they are unable to do so.

Answer: B

Explanation:
In CRM Analytics, even if users are granted access to view an app and its dashboards, their ability to download data is controlled by permissions assigned via permission sets. Specifically, users need the
"Download Data" permission to download data from widgets or dashboards. If this permission is missing from their permission set, they will be unable to download the specific widget, even though they can view the data.
Reference: The role of permission sets in granting access to data features, such as downloading data, is detailed in Salesforce'sCRM Analyticspermissions documentation and is emphasized in the module "Building Lenses, Dashboards, and Apps in CRM Analytics."


NEW QUESTION # 73
A CRM Analytics consultant has prepared a CSV file to be uploaded to CRM Analytics. By mistake, one of the column headers is modified as random non-alphanumeric characters "*&**(&*(%", which went unnoticed prior to uploading the file.
What is the expected behavior of the uploaded CSV column?

Answer: C

Explanation:
When uploading CSV files into CRM Analytics, column headers must follow certain formatting rules.
Headers containing non-alphanumeric characters, such as "&**(&(%", will automatically be adjusted.
Specifically, if the column header starts with non-alphanumeric characters or contains such characters, CRM Analytics will prefix the header with "X" to ensure compatibility with internal naming conventions. This behavior ensures that the column can be referenced in the platform without causing errors or conflicts.


NEW QUESTION # 74
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: 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 # 75
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