Free Salesforce Tableau-CRM-and-Einstein-Discovery-Consultant Practice Exam with Questions & Answers | Set: 4

Name: How to Pass Tableau-CRM-and-Einstein-Discovery-Consultant Exams
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Questions 31

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

Options:

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.

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05-Jul-2025

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Questions 32

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

Options:

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.

Questions 33

In Einstein Discovery:

Options:

'What Is The Difference' insights are comparative insights that help you better understand the relationships between explanatory variables and the goal (target outcome variable) in your story. These insights, based on a statistical analysis of your dataset, help you figure out which factors contribute to the biggest changes in the outcome variable. Einstein Discovery uses waterfall charts to help you visualize comparisons in What Is The Dif

'Why It Happened' insights help you take a deeper look into the exact factors that led to an outcome. Why It Happened s/ Q insights drill deeper into the various factors that contributed to your story's goal. These insights are based on a statistical analysis of your dataset. Einstein Discovery uses waterfall charts to help you visualize Why It Happened insights.

'Predictions and Improvements' insights help you explore what might happen in the future. For example, you can interactively perform "what if analyses in your story. Einstein Discovery provides you with predictions and suggested improvements based on a statistical analysis of your dataset and predictive analytics. To help you visualize these insights, Einstein Discovery uses:

- waterfall charts for predictions

- bar charts for s

'What Happened' insights are the primary insights in your story. They are descriptive insights that help you explore, at an y/ Q overview level, what factors contributed to the outcome, based on a statistical analysis of your dataset. .Einstein Discovery uses bar charts to help you visualize What Happened insights.

Questions 34

To model customer value, a consultant decided to aggregate the amount ($) individual customers spent over a 2-year span.

With reference to the outcome variable, which action should the consultant take?

Options:

Create five bins of revenues, ranging from Very High Value, high Value, average Value, Low Value, and very Low Value in dataflow.

Select the option: Are you expecting a whole number greater than or equal to 0?

Create five bins or revenue, ranging from very high Value, High Value, Average Value, Low Value, and Very Low Value in data prep.

Select to minimize the outcome variable.

Questions 35

A consultant is tasked with creating one query that shows how many opportunities and cases there are per account.

Cases and opportunities are found in two different datasets with a reference to the related Account via the AccoundId.

What options do the consultant have in Analytics Studio to create the query?

Options:

A fill statement

A cogrouop or union statement

A union statement

A cogroup statement

Questions 36

The Universal Containers company uses a Microsoft Azure SQL Data Warehouse to gather information about sales representatives' objectives. They want to use Einstein Analytics to gain insights from this data; therefore, they need to automatically load the warehouse's data into an Einstein Analytics dataset on a daily basis. The data also needs to be transformed and merged with data from the company's org.

Which three Einstein Analytics user interface features can be used to complete these requirements? Choose 3 answers

Options:

Dataflow

Microsoft Azure SQL Data Warehouse Connector

Einstein Analytics Connector for Excel

Recipes

Analytics REST API

Questions 37

Exhibit:

Tableau-CRM-and-Einstein-Discovery-Consultant Question 37

A company wants to create a timeline chart to visualize the evolution of their Closed Won Opportunities. What are the required parameters to build a lens that displays output similar to the image shown?

Options:

2 measures, 0-2 groupings if trellis is disabled, or 0-4 groupings if trellis is enabled

1 measure, 1-2 groupings if trellis is disabled, or 1-4 groupings if trellis is enabled

1 measure, 1 grouping by a date field, and either 0-1 groupings by a dimension if trellis is disabled, or 0-2 groupings if trellis is enabled

1 measure, 0 groupings if trellis is disabled, or 0-2 groupings if trellis is enabled

Questions 38

An Einstein Analytics team created a funnel chart to show the number of opportunities in each stage. The managers who use the chart report that the funnel shows stages in alphabetical order instead of sales cycle order.

In which two ways can a consultant help them address this issue? Choose 2 answers

Options:

Use a dataflow to rename the stages with a preceding number.

Use a dashboard JSON to rename stages.

Use a dataflow to sort the stages by their internal name.

Use a dataset XMD to rename stages.

Questions 39

Why would you use the Actions menu in a chart?

Options:

To expand the time period shown in a dashboard

To rearrange widgets in dashboards

To post to Chatter

To create workout plan for you and your team

Questions 40

A large company is rolling out Einstein Analytics to their field sales. They have a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy.

An individual Sales rep should be able to view all opportunities that she/he owns or as part of the account team or opportunity team. The Sales Manager should be able to view all opportunities for the entire Sales team. Similarly, the Sales Vice President should be able to view opportunities for everyone who rolls up in that hierarchy.

The opportunity dataset has a field called 'Ownerld' which represents the opportunity owner.

Given this information, how can an Einstein Consultant implement the above requirements?

Options:

As part of the dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the

opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" && 'Ownerld' == "SUser.Id".

As part of the dataflow, use computeExpression on the Roleld field to create an attribute called 'ParentRolelDs' on the opportunity

dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || 'Ownerld' == "$User.Id".

As part of the dataflow, use computeRelative on the Roleld field to create an attribute called 'ParentRolelDs' on the opportunity

dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || 'Ownerld' == "$User.Id".

As part of the dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the

opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || TeamMember.Id' == "$User. Id" || 'Ownerld' == "SUser.Id".