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Prep4pass has assembled a brief yet concise study material that will aid you in acing the Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam on the first attempt. This prep material has been compiled under the expert guidance of 90,000 experienced Salesforce professionals from around the globe. Prep4pass offers the complete package that includes all exam questions conforming to the syllabus for passing the Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) exam certificate in the first try.

Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Analytics Dashboard Configuration25%- Configure dashboards
  • 1. Configure bindings
  • 2. Set up dynamic dashboards
  • 3. Apply query filters
Topic 2: Analytics Dashboard Design20%- Design and build CRM Analytics dashboards
  • 1. Apply design best practices
  • 2. Describe the use cases for Visualforce and Lightning components
  • 3. Use Lenses and Dashboards
Topic 3: Einstein Discovery20%- Describe Einstein Discovery concepts
  • 1. Explain the model building process
  • 2. Interpret model results
  • 3. Identify the use cases for Einstein Discovery
- Implement Einstein Discovery
  • 1. Configure and deploy Einstein Discovery models
  • 2. Integrate predictions into CRM Analytics dashboards
Topic 4: Data Layer25%- 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)
- Implement and configure the right data transformations
  • 1. Identify and resolve data sync issues
  • 2. Use Data Prep actions
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 (Q48-Q53):

NEW QUESTION # 48
A company realizes it has a lot of rich information around its cases, but unfortunately, most of this isunstructured/textual data. Thecompany is exploring how to include some of this information in its case prioritization.
Which option within CRM Analytics should a consultant leverage?

Answer: A

Explanation:
For a company with a wealth of unstructured textual data in their cases, the "Detect Sentiment" transformation within CRM Analytics Recipes is a crucial tool. This transformation analyzes the sentiment of the text data- whether it's positive, neutral, or negative-and this insight can be highly valuable in case prioritization processes. Here's why this transformation is useful:
* Insight into Customer Sentiments: By detecting sentiment, the company can prioritize cases based on the urgency and emotional tone expressed in the text, which might indicate customer dissatisfaction or urgency.
* Automation and Efficiency: Automatically categorizing cases based on sentiment can streamline workflows and ensure that critical cases are handled promptly.
* Enhanced Customer Service: Responding to negative sentiments swiftly can improve customer satisfaction and potentially mitigate issues before they escalate.


NEW QUESTION # 49
The administrator at Cloud Kicks has been asked to sync data from an external object created in Salesforce into CRM Analytics.
What should the administrator keep in mind?

Answer: A


NEW QUESTION # 50
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: B

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 # 51
A consultant sets up a Sales Analytics templated app that is very useful for sales operations at Universal Containers (UC). UC wants to make sure all of the data assets associated with the app, including:
recipes, dataflows, connectors, Einstein Discovery models, and prediction definitions are refreshedeveryday at
6:00 AM EST.
How should the consultant proceed?

Answer: A


NEW QUESTION # 52
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 # 53
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