Salesforce Tableau-CRM-Einstein-Discovery-Consultant Dumps - 100% Cover Real Exam Questions (Updated 210 Questions) [Q19-Q33]

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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Dumps – 100% Cover Real Exam Questions (Updated 210 Questions)

Real Tableau-CRM-Einstein-Discovery-Consultant dumps – Real Salesforce dumps PDF

NO.19 What is the test called that helps to identify categories that exhibit a pattern outside the overall average?

Null hypothesis test

Significance level test

Critical region test

Chi-square test

T-test

NO.20 An Einstein Consultant receives a new project from a client that wants to implement Einstein Analytics. They do not currently have Einstein Analytics, but want guidance around how to ensure that their users have correct access.
They have 1000 users with a small team of three people who will build datasets and dashboards. An additional 15 people should be able to create dashboards. The remaining users should only be able to view dashboards.
Which recommendation should the consultant give the client?

Create and assign Salesforce permission sets according to the three types of roles defined.

Assign the app permissions “viewer/’ “editor,” and “manager” to the three types of roles defined.

Create and assign three new Salesforce profiles according to the three types of roles defined.

Assign “Einstein Analytics Explorer” licenses to users that should only view the dashboard, and assign “Einstein Analytics Developer” licenses to users that should be able to create datasets and dashboards.

NO.21 A company uses role hierarchy to implement data security in Salesforce. They want the same role-hierarchy-based security model to apply in Einstein Analytics, but want the users in a role to see data owned by other users in the same role.
Using the “flatten” transformation, which attribute setting achieves this requirement?

Set the attribute “selfjield” to true.

Set the attribute “selfjield” to false.

Set the attribute “include_self_id” to true.

Set the attribute “include_self_id” to false.

NO.22 A new field called “CardBalance” is added to the standard object. Account. The team wants to add this new field to an Einstein Analytics dataset that sources the Account object; however, the team needs to limit the users who are able to view that field’s data in the dataset.
How can an Einstein Consultant help them implement this new requirement?

Add the new field to the existing dataset and use the XMO file parameters to hide the new field from users who should not have access to it.

Add the new field to the existing dataset and activate “Sharing inheritance” in the Account object so only users who have access to the field in Salesforce will have access in Einstein Analytics.

Create a new Account dataset containing the new field and give access to this dataset only to users who should be able to see the new field.

Add the new field to the existing dataset and use “Security Predicates’ to hide it from users who should not access it.

NO.23 An insurance company has many Einstein Analytics dashboards that show the influence of weather, such as atmospheric temperature, on customer cases. A service agent commented that it is sometimes difficult to determine, by looking at a dashboard, whether the temperature data is reported in degrees Fahrenheit or in degrees Celsius.
How can a dashboard designer ensure the temperature data is easier to interpret on the dashboards?

Add a text widget to the dashboard to indicate Fahrenheit or Celsius.

Use the XMD node in the dataflow to customize the number format of the field.

Customize the number format in the number widget properties of the dashboard.

In Explorer, go to the Fields menu and then customize the number format of the measure.

NO.24 How do you analyze data from a CSV file using Einstein Discovery?

Import the CSV file into Einstein Discovery.

Import the CSV file into the most similar Salesforce object, then run reports on that object.

You can’t import data from a CSV file

Import the CSV file into an Einstein Analytics dataset, then create a story.

NO.25 A customer wants to change the default blue color on a bar chart. What is the easiest way to change blue to another color?

Use conditional formatting under the bar chart widget properties by selecting the dimension.

Use conditional formatting under the bar chart widget properties by selecting the measure.

Use bindings to specify a color per bar.

Create a compare table formula to specify a hidden metric for coloring purposes.

NO.26 After getting approval of the dashboard layout design for a desktop, the Einstein Analytics consultant is ready to start the design process for a mobile layout.
What are three considerations that the consultant should keep in mind when developing the layout? Choose 3 answers

If no layouts are eligible for the mobile device, the first defined layout is used. (Missed)

If no layouts are eligible for the mobile device, an error message will be displayed.

If more than one layout is eligible, the one with the most device properties set is used. If there is a tie, the most recently defined layout is used. (Missed)

A layout for mobile is eligible for use when the device meets all the device properties set in the Layout panel.

There are widgets that cannot be displayed on mobile layouts.

NO.27 An Einstein Consultant receives a request from the Marketing department to help them understand lead conversion. Presently, they are unaware of the percentage of leads that get converted to sales. They hope to view results by account manager, value, and quarter. The data is there, so the consultant can add it to the marketing dashboard.
How should this metric be calculated?

Create a new step in the dashboard using a compare table and define a formula.

Create a formula field on the lead object in Salesforce and add it to the dataset.

Create a computeExpression in the dataflow.

Create a new step in the dashboard using a compare table and the running total function.

NO.28 What is another name for the type of insight that examines how one variable explains variation of the outcome variable?

First-order analysis

Second-order analysis

Third-order analysis

Spectrum analysis

Object-oriented analysis

NO.29 A company created a dataset called myExternalDataset. It contains a dimension, called UserRegion, that is populated by the standard User object’s picklist: Region.
The company has security requirements for this dataset:
1. Only a subset of users should be able to access the dataset.
2. Users who can access the dataset should see only data that belongs to their region.
In which two ways can an Einstein Analytics consultant help them implement these requirements? Choose 2 answers

Save the dataset under “My Private App” so only a subset of selected users can access the dataset.

Use a security predicate in the dataset so users can see only rows belonging to their respective regions.

Create a sharing rule in Salesforce based on the Region field in the user object and set the dataset to inherit sharing from Salesforce.

Save the dataset under a new application and give “viewer” access to a public group containing the list of users allowed to see the dataset.

NO.30 An Einstein Analytics team wants to create a dashboard using two standard Salesforce objects. The dashboard should display data from the Case object, along with related data from the Account object. Which two processes can achieve this?

Extract data from the case and account objects using “sfdcDigest” transformation, Q use “append” transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset

Extract data from the case and account objects using an ETL tool, use the ETL tool to y/ Q join account and case data, and then upload the data to Einstein Analytics. Build a dashboard using the ETL generated dataset

Extract data from the case and account objects using “sfdcDigest” transformation, y/ Q use “augment” transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset

Extract data from the case and account objects using “dataloader”, create a CSV file Q with account and case data, and then upload the CSV as a dataset to Einstein Analytics. Build a dashboard using that dataset

NO.31 Why is it important to prepare the data in a CSV file before you bring it into Analytics?

To remove column headers

To make sure the content is interesting

To add currency symbols to numeric fields

To make sure Analytics can set the field type correctly

NO.32 Before using bindings, you can try using facets to specify interactions between widgets.

False

True

NO.33 An Einstein Analytics team plans to enable data sync (replication).
Which two limits are specific to data sync (replication) and should be considered before enabling the feature because they might impact existing jobs?
Choose 2 answers

Maximum number of dataflow definitions

Maximum number of dataflow transformations

Maximum number of objects that can be enabled for data sync (replication)

Timeout for ELT (Extract Load Transform) jobs that are scheduled but not yet executed