Pass the Salesforce Consultant Tableau-CRM-and-Einstein-Discovery-Consultant Questions and answers with ValidTests

Two benefits of designing using the "Progressive Disclosure" principle are:

A: Improved ease of use for end users. By only displaying essential information initially and allowing users to access more detailed data as needed, dashboards become less cluttered and more user-friendly.

D: Better dashboard performance. This design principle can also lead to better performance as less data isprocessed and rendered initially, speeding up load times and responsiveness.

The Service Analytics Overview dashboard in Tableau CRM is designed to provide comprehensive insights into various aspects of service operations. It includes:

Key metrics such as open cases, average time to close, first contact resolution, and customer satisfaction, offering a quick overview of service efficiency.

Drill-down capabilities into more detailed dashboards like agent performance, channel review, and telephony metrics, enabling deeper analysis.

Availability on both desktop and mobile platforms, ensuring accessibility across different devices.

It serves as an excellent starting point for serviceanalytics, providing a holistic view of the service department’s performance.

This dashboard is a central tool for managing and analyzing service operations effectively, helping organizations to optimize their customer service strategies.Reference: https://help.salesforce.com/s/articleView?id=sf.bi_service_analytics.htm&type=5

To convert the "CloseDate_Month" numerical field into a month name in the dataset, the consultant should use:

C: computeExpression. This Dataflow node allows the transformation of existing data fields using expressions, such as converting a month number into a month name. By applying a suitable expression, the 'CloseDate_Month' can be transformed into a string representing the month’s name, enhancing readability and usability in filters.

In Salesforce Tableau CRM Einstein Discovery:

B is correct because in the Story Settings, the consultant can view and evaluate the strength of each predictor field, helping to determine which fields are most influential in the model.

The best practice to ensure Einstein Analytics dashboards are easily used across both desktop and mobile devices is to create multiple layouts and ensure the layout selectors match the device. Additionally, resizing and hiding widgets as necessary helps ensure that the content is appropriately displayed and interacted with on the device screen size.

In Einstein Discovery stories, insights showhow different variables, or combinations of variables, explain the variation of the outcome variable. The outcome variable is the target variable whose behavior and influencing factors are being analyzed and predicted by the model. Insights in the story will help understand how each explanatory variable and their interactions impact the outcome, which is central to predictive analytics and machine learning in Einstein Discovery. Reference: Salesforce Help - Einstein Discovery Insights

When you configure the story, you tell Einstein Discovery to maximize/minimize the variable. The variable is 'outcome variable' in your story

When deploying a dashboard such asSalesPerformance_1 from a sandbox to production in Salesforce Tableau CRM using a package, the correct metadata reference in the XML file is typically formatted with a suffix that identifies the type of component. For dashboards in Tableau CRM, the suffix"waveDashboard" is used, hence the correct reference would be "SalesPerformance_1 waveDashboard."

On the Edit Field Attributes page when uploading a CSV file to Analytics (Tableau CRM), you can perform several modifications to ensure the data is properly formatted and structured for analysis:

Change a field's name: Adjust the names of fields to match your analytics schema or to make them more understandable.

Change a field's format: Modify the format especially for date, number, or any specific custom format required for your analysis.

Change a field's type: Alter the data type (e.g., from string to integer or vice versa) to suit the data operations you plan to perform. These capabilities allow for the customization and preparation of data directly within the platform, streamlining the process from data upload to insight generation. Reference: https://help.salesforce.com/s/articleView?id=sf.bi_datasets_upload.htm &type=5