Salesforce Implement and Manage Tableau CRM ANC301 Dumps in PDF

Free Salesforce ANC301 Real Questions (page: 19)

A manager at Cloud Kicks asks for data in a dashboard to be refreshed after the sync of an external connection to Google BigQuery.
How should the consultant accomplish this?

  1. Schedule the recipe to run as event-based and check the Salesforce external connection syncs checkbox.
  2. Create 3 Salesforce flow to trigger the recipe to run once the connection sync has finished running.
  3. Check the scheduled date/time of the sync and schedule the recipe to run 15 minutes after the start time of the sync.

Answer(s): A

Explanation:

For Cloud Kicks' requirement to refresh dashboard data synchronously with the sync of an external connection to Google BigQuery, the most efficient method is:
Event-Based Triggers: Using CRM Analytics, you can set up recipes to run on an event-based trigger. This ensures that the recipe (which processes the data for the dashboard) only runs after the external data sync is completed.
Salesforce External Connection Syncs: By specifically targeting the synchronization event of the Salesforce external connection with Google BigQuery, the recipe ensures data consistency and timeliness without manual intervention.
Automation and Efficiency: This approach minimizes latency and maximizes data freshness, aligning data processing closely with data availability, thus enhancing dashboard accuracy.



Which capability can a consultant use if "Deploy without connecting to a Salesforce Object" is selected while deploying the model?

  1. Einstein Predictions Component score
  2. Predict Function in Salesforce flows
  3. No-Code Writeback to SFDC objects

Answer(s): B

Explanation:

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.



A CRM Analytics consultant has been asked to bring data from an external database as well as five external Salesforce environments into CRM Analytics. Twenty-five objects have been enabled from the local Salesforce connector.
The requirements are:
* 10 objects should be enabled from an external database
* 12 objects each from three of the external Salesforce environments
* 15 objects each from the remaining two external Salesforce environments The consultant estimates each connector will, per object, bring between 1,000 and 1 million rows of data.
Which limit will be exceeded?

  1. Total number of enabled objects
  2. Salesforce external connector number of synced rows
  3. Storage rows of data

Answer(s): A

Explanation:

In evaluating the scenario presented where multiple external sources and objects are being integrated into CRM Analytics, we need to consider the total number of enabled objects across all connections. Here's a breakdown:
10 objects from an external database
12 objects each from three external Salesforce environments, totaling 36 objects 15 objects each from two external Salesforce environments, totaling 30 objects 25 objects already enabled from the local Salesforce connector This brings us to a total of 101 objects enabled, which may exceed typical limits on the number of objects that can be enabled in a CRM Analytics environment, depending on the specific Salesforce licensing and platform limits.



A consultant wants to understand what the important predictors are in a model.
Where is this information found?

  1. Einstein Recommendations
  2. Model Settings
  3. Model Deployment Wizard

Answer(s): B

Explanation:

The important predictors of a model in CRM Analytics can typically be found under the Model

Settings. This area provides detailed information about the configuration and the inputs (predictors) used to train the model. Insights into which predictors have the most significant impact on the model's outcomes can be gleaned from this section, enabling a deeper understanding of the model's internal workings and the factors driving predictions.



After getting approval for the dashboard layout design for a desktop, the CRM Analytics consultant is ready to start the design process for a mobile layout.
Which consideration should the consultant keep in mind?

  1. Create a layout with the property "phone" to show the dashboard on the mobile app similar to creating a layout with the property "dashboard" to show on the desktop for the same dashboard,
  2. If no layouts are eligible for the mobile device, an error message will be displayed but the dashboard will still be visible on the desktop without errors.
  3. "Tablet" or "Phone" layout--where only minWidth and maxWidth have been set--may be displayed on a desktop if the dashboard is embedded in a small frame, or if the browser window is small.

Answer(s): C

Explanation:

When designing for different device types in CRM Analytics, particularly for mobile layouts, it's crucial to consider how the layout will respond not just on mobile devices but also under various display conditions on desktops. Here's the rationale for focusing on this consideration:
Responsiveness: Layouts designated for tablets or phones may also be triggered on desktop environments if conditions such as browser window size or embedded frame dimensions mimic those typical of smaller devices.
Design Flexibility: Understanding this behavior is essential for creating versatile dashboards that maintain functionality and visual integrity across all potential viewing scenarios. User Experience: Ensuring that the dashboard behaves predictably across device types and sizes enhances user engagement and effectiveness, as it provides a consistent experience regardless of the access point.
This approach ensures that the dashboard remains functional and accessible no matter how or where it is being viewed, aligning with best practices for responsive and adaptive design in modern analytics environments.



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