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A CRM Analytics consultant is reviewing results from an Einstein Discovery story with a business user. They agree with the findings but notice that none of the fields used in the story have a correlation value greater than 4%. The client is now concerned that the model
may not be good enough to deploy.
Which action should the consultant take?
Which recommended technique should a CRM Analytics consultant
use to access CRM Analytics data from a remote app or website?
Which capability can a consultant use if ''Deploy without connecting to a Salesforce Object'' is selected while deploying the model?
When deploying a model with the option 'Deploy without connecting to a Salesforce Object', the suitable capabilities include:
Use of Predict Function in Salesforce Flows: This capability allows the deployed model to be used within Salesforce Flow as a predictive tool, enabling automation flows to include predictions without directly writing back to Salesforce objects.
Flexibility in Application: This method provides flexibility in how predictions are utilized across various Salesforce processes and workflows, without the need for direct data manipulation within Salesforce objects.
Enhanced Workflow Integration: By integrating predictive insights directly into flows, organizations can automate decision-making processes, enhance user interactions, and streamline operations based on predictive outcomes.
This setup aligns with Salesforce's best practices for leveraging CRM Analytics to enhance operational efficiency and decision accuracy across different business functions.
What is a benefit of introducing a second local connector?
Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.
Universal Containers intends to use a custom Salesforce big object in its org and visualize the data using CRM Analytics. As the number of rows to be synced is quite large, the CRM Analytics consultant is looking to set up an incremental sync with additional filters added as part of the data sync to improve performance.
What should the consultant keep in mind while implementing this?
