Consult a Data Scientist for further analysis.

Determine if the pattern is a data issue or a new insight.

Filter out the data that causes an unexpected pattern and analyze the new results.

Accept the new pattern and have confidence that Einstein knows the business as accurately as the customer.

Update

Append

Overwrite

Upsert

The dataset's security predicate was set up incorrectly.

Yasmine doesn't have the Manager app role.

Yasmine wasn't assigned a permission set

Yasmine doesn't have the Create and Edit Analytics Dashboards permission.

Customize tooltip

Chart Markers

XMD

Compare Table

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.

computeExpression Transformation with SAQL Expression to calculate the duration

flatten Transformation with Offset Expressions to calculate the duration

computeRelative Transformation with offset parameter to calculate the duration

computeRelative Transformation with SAQL Expression to calculate the duration

Sales Wave

Sales Analytics Apps

Analytics Templated Apps

Security User

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.

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.

Use the dataflow transformation "delete" and set "userlD" as the deletion ID.

Use a combination of dataflow transformations: "augment" and "filter."

Use an external ETL tool to extract both datasets and delete records.

Use the recipe operation "delete" and set "userlD" as the deletion ID.

Enable Parental Control

Always Sign Me Up for Dreamforce

Sales Analytics Apps

Access Sales Cloud Analytics Templates and Apps

Selecting a Dataset in Einstein Analytics, then clicking Create Story

Copying text from company reports and pasting into Einstein Discovery

Uploading a Microsoft® PowerPoint® presentation

Entering notes about the data

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.

Assign the Manager role the user

Ensure the user has the Analytics permission

Assign the Editor role the user

Assign the view role to the user

/services/data/v##.#/wave/apps

/services/data/v##.#/analytics/wizard

/services/data/v##.#/wave/templates

/services/data/v##.#/analytics/projects

A. Wait at least 3 days after purchase.

B. Have a Customer Community Plus or Partner Community license.

C. Be nominated by your community peers.

D. Assign your community members the Analytics for Communities permission set license

E. B and D

flatten

compute Relative

compute Expression

append

Make adjustments to the story to better demonstrate that the third-party payment app is the culprit.

Use the credit card company's domain knowledge and exclude the third-party payment app from the story.

Explain to the company that the story has returned unbiased results and the initial assessment is accurate.

Ask the credit card company for a more comprehensive dataset to analyze.

An admin hasn't run a dataflow.

Danielle still needs to grant Zoe a permission set containing the Manage Analytics permission.

Danielle didn't share the Mosaic app with Zoe in Einstein Analytics.

Danielle still needs to grant Zoe a permission set containing the Use Analytics permission.

Dataflow Editor

Recipes Editor

Step Editor

Settings

A. Low-fuel notifications from your car

B. Sharing of apps with Communities

C. Access to the API

A and B

B and C

To find out what the merge icons represent in a dataset

To schedule when a dataset recipe runs

To join related data from different sources

To deal with duplicate records

Create a recipe to generate a new dataset from the "OpportunityWithAccount" and "CaseWithAccount" datasets aggregated byAccount, and use the generated dataset in a lens.

Use "Compare Table" to join the "OpportunityWithAccount" and "CaseWithAccount" datasets using the "Accountld" and thenaggregate by Account.

Set up Connect Data Sources in the UI between the "OpportunityWithAccount" and "CaseWithAccount" datasets.

Use a SAQL query to group and join the "OpportunityWithAccount" and "CaseWithAccount" datasets then generate the results.

None of the data

Only rows designated by the Salesforce administrator

All rows and fields in the datasets

Only rows designated by the App Manager

Remind them that the technology is only as good as the data.

Advise them that the use case may not be accurate.

Highlight that Einstein reduces time to insight, which is much faster than learning from experience.

Recommend using a visualization tool, like Einstein Analytics, to uncover the details.

A. You create a text-only version of an app.

B. The template will not include a configuration wizard.

C. The dataflow fails.

D. The app includes all possible dashboards by default.

B and D

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

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

Use Analytics

Manage Analytics

Create and Edit Analytics Dashboard

None of above

It's a read-only file with all the user documentation for a template.

It's the boss of the template with all the information needed to create the app.

It makes sure that the app includes all the right Salesforce data.

It's automatically populated every time you create an app from the template.

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.

Modify dataflows to exclude unused fields and include a filter to extract relevant data.

Scale down the number of datasets to help improve data sync (replication) performance.

Start over again with new dataflows that exclude unused fields with a filter to extract relevant data.

Update the existing data sync (replication) process by removing unused fields with a filter to extract relevant data.

Use the Analytics External Data API and leverage the "query" resource.

Export the dataset as an XLS file and use the Einstein Analytics Connector for Excel.

Use the Analytics REST API and leverage the -query" resource.

Export the dataset as a CSV file and load it to an external database.

Alphabetical, in ascending order

Alphabetical, in descending order

Insights that explain the most variation in the outcome variable, in ascending order

Insights that explain the most variation in the outcome variable, in descending order

append

computeExpression

argument

computeRelative

The data manager

The Analytics home page

The Create Dataset page

The Setup menu

Grant Benito access to all datasets in the org.

Assign Benito a permission set that contains the permission: Create and Edit Analytics Dashboards.

Grant Benito access to the app that contains the Seed Bank dataset and assign him a permission set that contains the Create and Edit Analytics Dashboards permission.

Assign Benito a permission set that contains the permission: Create and Manage Analytics Apps.

Organization

Records

Page Layouts

Objects

Set the attribute "self_ld" to true.

Set the attribute "self_ld" to false.

Set the attribute "include_self_id" to true.

Set the attribute "include_self_id" to false.

Click the Actions bar from a bubble chart

Hover over the case number column of the values table widget and click the arrow that appears

Double-click the case number in the Actions widget

Simply @mention the case manager for that segment

Segment the account data per region and deploy the same model to all segments.

Deploy the same model to all accounts and set the region field as an actionable variable.

Deploy the same model to all accounts and use an Apex trigger to call the appropriate prediction.

Segment the account data per region and deploy the appropriate model for each segment.

The current user

The system administrator

The Integration User

The record owner

Add the system permission "Manage Analytics Custom Maps" to the permission set used.

Enable "Custom maps with geoJSON" in the analytics settings.

Upload the geoJSON via the API because it is not a function in the UI.

Contact Salesforce support and request to get custom maps and geoJSON enabled for the org.

Share the app with the users in Einstein Analytics.

Create user accounts for the users in Einstein Analytics.

Assign the users to the permission set containing Use Analytics.

Assign the users to the permission set containing Manage Analytics.

digest transformation

flatten transformation

delta transformation

sfdcDigest transformation

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".

Create two permission sets with different system permissions.

Use a permission set license with two different levels of access.

Grant "Manage" access permission to the apps.

Create a permission set license assignment with two different levels of access-

Option A

Option B

Option C

Option D

ui.json

template-to-app-rules.json

master- info.json

template-info.json

Create two custom apps: one for marketing dashboards with marketing as "viewer" and one for sales dashboards with sales as "viewer." Add the datasets as references to both custom apps.

Create three custom apps: one for marketing dashboards with marketing as "viewer," one for sales dashboards with sales as "viewer," and one for datasets where marketing and sales are "viewer."

Create one custom app for the datasets and share it with marketing and sales as "viewer."

Duplicate the datasets and create two custom apps: one for marketing dashboards and datasets with marketing as "editor" and one for sales dashboards and datasets with sales as "editor."

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

Run and monitor

Plan and map

Extract and prepare

Build and explore

Null hypothesis test

Significance level test

Critical region test

Chi-square test

T-test

Selected variable with CLV

Selected variable average with the mean

Selected variable with a different variable

Selected variable average with the filtered average

Selected variable with all story data

Inherited security

Security predicates

Separate apps for each region

Sharing rules

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.

Answer only questions that involve custom objects

Try each option in the dropdown one at a time

Download the app and run a SAQL query on the JSON

Click "Looks good, next" and look for questions highlighted in red

Is like having a personal data scientist on staff

Replaces your team of BI experts and data analysts

Helps you hire the best data scientist for your business

Understands your business better than you do

Only provide the user with the level of detail they need to see, with the option to drill down deeper into more details.

Utilize the latest templates for the most modern look and feel.

Intentionally omit specific details so that users can do ad-hoc exploration if needed for root-cause analysis.

Implement strict security predicates to minimize the amount of information displayed to users.

Update contents in the Sales Operations app and changes will be pushed down to its generated apps.

Ensure the Sales team has the necessary permissions to customize their apps.

Create a configuration wizard for the app.

Update contents in the Sales Operations app and create new template versions of the app.

An account of imaginary or real people and events told for entertainment

A collection of graphs, statistical analysis, and text that helps you understand the relationships between multiple outcome variables and the factors that influence those variables

A collection of graphs, statistical analysis, and text that proves exactly what caused an outcome

A collection of graphs, statistical analysis, and text that helps you understand the relationships between a single outcome variable and the factors that influence that variable

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.