Salesforce Exam 2024 Einstein-Analytics-and-Discovery-Consultant Dumps Updated Questions UPDATED Jan-2024 [Q62-Q76] : Free Exams Dumps Materials : http://exams.dumpsmaterials.com

NEW QUESTION 62
An Einstein Discovery team created a model to maximize the margin of their sales opportunities. They want to deploy the model to the Opportunity object in order to predict the outcome of every newly created or updated Opportunity.
What are the steps to accomplish this?

Create a trigger on Opportunity and use the Salesforce External Connector to get predictions from Einstein Discovery.

Create an Apex batch on Opportunity and use the REST API to get predictions from Einstein Discovery.

Create a trigger on Opportunity and install the Einstein Discovery Writeback managed package from the AppExchange.

Create a trigger on Opportunity and use the REST API to get predictions from Einstein Discovery.

NEW QUESTION 63
A consultant built an Einstein Analytics dashboard for a company. The company then requested an enhancement to the dashboard and provided additional data that needs to be displayed. As a result, the consultant decides to “augment” the dataflow.
Which phrase describes this transformation?

Add data based on the right-side grain

Join data similar to an SQL statement

Add data as a lookup relationship (left side is the lowest grain)

Join data based on a many-to-many relationship

NEW QUESTION 64
An Einstein Analytics consultant has been asked to refactor a dashboard so that it loads more quickly. After some analysis, the consultant found that most of the dashboard steps run in less than five seconds; however, the Opportunities Table takes 30 seconds to run.
How can the consultant improve the performance of this dashboard?

Create a second page on the dashboard and move the table to this new page.

Create a link to download the list of opportunities as an Excel file.

Create a Visualforce page and display a list view of the opportunities on this new page.

Create a second dashboard and move the table to this new dashboard.

NEW QUESTION 65
Which statement best describes how to ensure Einstein Analytics dashboards are easily used across both desktop and mobile devices?

Create multiple layouts, and reorder all the widgets so that they fit nicely within the new default width.

Create a single layout and allow Einstein Analytics to automatically organize dashboard contents to be optimal for the device type.

Create a single layout and reorder all the widgets so that they fit nicely when viewing on either device.

Create multiple layouts, ensure the layout selectors match the device, and resize/hide widgets as necessary to ensure the content is appropriate for the device screen size.

NEW QUESTION 66
Which of the following is true about the Service Analytics Overview dashboard?

It instantly provides key metrics on open cases, average time to close, first contact resolution, and customer satisfaction.

It lets you drill down to more detailed dashboards, like agent performance, channel review, and telephony metrics.

It’s available on desktop and mobile.

It’s a great place to start your analysis.

All of the above.

NEW QUESTION 67
Universal Containers reports that any selection in the List widget is not affecting the Pie chart in one of their Einstein Analytics dashboards. The step options associated with the List widget and Pie chart are shown in the graphic.

Given that the steps are using different datasets. which two changes can an Einstein Consultant make to solve this issue’ Choose 2 answers

Use ‘Connect Data Sources” and create a connection to connect the two datasets.

Use selection binding in the filters section of Che step “Step_pie_2.”

Use “Connect Data Sources” and create a connection to connect the two widgets.

Use selection binding in the filters section of the step “Type_l.”

NEW QUESTION 68
What kind of org should you use for checking challenges when you do Trailhead modules about Analytics?

An enterprise org, because that type of org is typically used by large companies

A trial org, because you don’t need to save anything

A Developer Edition org, because it’s a free, safe environment where you can try things out

A higher education org, because analytics requires advanced math

NEW QUESTION 69
A consultant built an Einstein Analytics app for the Sales Operations team. The Sales Operations team wants to share their app with other people at the company. The consultant recommends distributing the app as an Einstein Analytics template app.
A set of JSON files will be generated after a template is created from the Sales Operations app. What is the name of the JSON file that manages template metadata and all other template elements’

ui.json

template-to-app-rules.json

aster- info.j son

template-info.json

NEW QUESTION 70
What kind of insight is “What Is The Difference”?

Descriptive

Diagnostic

Predictive

Prescriptive

Selective

NEW QUESTION 71
A large company has a single dataset that contains the attainment and commission fields for all sales reps.
Each sales rep should be able to view the attainment data for each rep in their division. Each rep should only be able to see their own commission data.
Which option should be used to enforce this requirement?

Create separate datasets for attainment and commission and apply security predicates and/or sharing inheritance.

Apply a security predicate on the existing single dataset.

Use sharing inheritance.

Add the sales organization to the attainment dataset access list.

NEW QUESTION 72
Universal Containers has a dashboard for Sales Managers. They need the ability to visualize the number of Closed Won opportunities by month, quarter, or year, and then display the result in a single chart. An Einstein Consultant created a static step to display three values: ClosedDate_month, ClosedDate_quarter, and ClosedDate_year.
What should the consultant do next?

Use nested binding to update the grouping in the chart.

Use selection binding to update the measure in the chart.

Use result binding to update the measure in the chart.

Use selection binding to update the grouping in the chart.

NEW QUESTION 73
A consultant created a dashboard using Einstein Analytics for her client, a shipping company. It sources data from very large datasets. Now the client has requested that the consultant add more steps to the dashboard.
To ensure that the dashboard has acceptable performance, what two actions should the consultant take?
Choose 2 answers

Check if any steps can be reused for multiple purposes.

Replace AggregateFlex steps with SAQL steps.

Split the steps and charts into different pages in a dashboard.

Avoid using conditional formatting.

NEW QUESTION 74
What does the Division is Naval section of the waterfall graph tell you?

How combinations of factors affect the CLV for Naval customers

How individual factors separately affect the outcome for Naval customers

What the relationship is between significant and insignificant factors as they impact CLV for Naval customers

How the chosen variable is related to all other factors in the model for Naval customers

NEW QUESTION 75
When creating a story in Einstein Discovery, do all potential collinear fields need to be removed before executing the build story’5

No. Einstein Discovery is impervious to collinearity, so the story and subsequent model will be fine.

No. Although it is ideal to eliminate collinearity as soon as possible, Einstein will give a warning post-build and the ridge regression will prevent collinearity from over-fitting.

yes. If all collinear variables are not excluded, the model will over-fit and not make any sense.

Yes. If the collinear variables are not removed, the Einstein Discovery model build will fail.

NEW QUESTION 76
A dataset for building the Einstein Discovery story contains 72 fields that are potentially relevant predictors.
Which approach is considered best practice to assess the top predictors in order to get to a meaningful and robust model?

This dataset is too big and cannot be used in Einstein Discovery. Request a new dataset with fewer predictors.

Build the story with all the predictors and indicate that Einstein Discovery should show the top predictors.

Go back to the data preparation and reduce the number of fields to less than 30 in order to produce a story.

Build a story with a first set of predictors and assess which predictors are important to the story. Then drop the less important ones and add the predictors that were omitted in the first run and assess their impact.