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First-rank CRM-Analytics-and-Einstein-Discovery-Consultant Exam Preparation: Salesforce Certified CRM Analytics and Einstein Discovery Consultant boosts the Most Efficient Training Dumps - Lead1Pass

First-rank CRM-Analytics-and-Einstein-Discovery-Consultant Exam Preparation: Salesforce Certified CRM Analytics and Einstein Discovery Consultant boosts the Most Efficient Training Dumps - Lead1Pass

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Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Admin
  • Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync
  • dataflows
  • recipes limits.
Topic 2
  • Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
Topic 3
  • Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
Topic 4
  • Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
Topic 5
  • Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.

Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q93-Q98):

NEW QUESTION # 93
Universal Containers has a well-defined role hierarchy in Salesforce where everyone is assigned to an appropriate node. The accounts within their instance are categorized by their demography.
An individual sales rep should be able to view all accounts that they own. In addition, sales reps should be able to see any accounts where the value of the account demography matches the demography defined on their user record. A user could have more than one demography defined on their user record.
To meet this requirement, the CRM Analytics consultant has set up a security predicate of the existing
'Account' dataset as follows:

This, however, does not seem to be working as expected.
What is causing the issue?

  • A. The security predicate needs to be updated as 'Ownerld' == "sUser.id" || 'Demography' = "$User.
    Demographic__c'.
  • B. The Analytics Security User is not provided access permission on custom field Demographic_c on the User object.
  • C. The Sales Rep is not provided access permission on custom field Demographic__c on the User object.

Answer: C

Explanation:
The issue with the security predicate not functioning as expected likely stems from a permissions issue related to the custom field Demographic__c on the User object. Here's a detailed explanation:
* Field-Level Security: If the sales reps do not have access to the Demographic__c field, the security predicate which references this field cannot execute properly as the system cannot evaluate the predicate without accessing the field.
* Permission Settings: Ensuring that the sales reps have the necessary permissions to view and use the Demographic__c field is crucial for the security predicate to function correctly.
* Data Visibility: The security model in CRM Analytics relies heavily on the underlying data permissions in Salesforce. If these permissions are not correctly configured, the expected data visibility through CRM Analytics will not be achieved.


NEW QUESTION # 94
Creating an Einstein Discovery story involves:

  • A. Entering notes about the data
  • B. Selecting a Dataset in Einstein Analytics, then clicking Create Story
  • C. Copying text from company reports and pasting into Einstein Discovery
  • D. Uploading a Microsoft PowerPoint presentation

Answer: B


NEW QUESTION # 95
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?

  • A. The column header is auto-updated to "Column" + column number.
  • B. The column header Is set to *&**(&*(%.
  • C. The columnheaderis prefixed with "X" upon upload.

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 # 96
Which widget property allows a consultant to restrict the view to a domain bounded by the values entered'

  • A. Add Custom Domain
  • B. Filter by Range
  • C. Add Custom Range
  • D. Add Filter

Answer: A


NEW QUESTION # 97
The model quality metrics of an Einstein Discovery story indicate that the GINI coefficient in the four folds are 0.82, 0.83, 0.84, and 0.75, respectively.
Which two actions should a consultant take? Choose 2 answers

  • A. Do not deploy the story immediately, and research why one fold is performing worse than the others.
  • B. Research and check the dataset for outliers in the target field and the main predictors that are shown on top of the story.
  • C. Deploy the story, because the variation in the metrics is within the normal range.
  • D. Confirm that the overall GINI coefficient is good prior to deploying the story.

Answer: A,D


NEW QUESTION # 98
......

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