2022 Valid Tableau-CRM-Einstein-Discovery-Consultant Exam Updates – 2022 Study Guide [Q27-Q50]

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2022 Valid Tableau-CRM-Einstein-Discovery-Consultant Exam Updates – 2022 Study Guide

Tableau-CRM-Einstein-Discovery-Consultant Certification – The Ultimate Guide [Updated 2022]

Q27. 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.

Q28. You are asked to update and maintain your company’s Einstein Analytics dashboards.
A request comes in for one of the dashboards that contains steps from different datasets. The request is to make it possible for a table from one dataset to be filtered by the results of a chart from another dataset. Your solution is to create a results binding.
Which three steps should you implement to create the binding?

Look up the API name of the filtering field

Look up the API name of the source field

Find source and target step names

Configure the results binding on the target step in the dashboard JSON.

Q29. As part of their analysis, Yasmine, Tonya, and Hadiqa need to create and save lenses to their project app. What is the minimum app role they need to do this?

Manager

Viewer

Editor

Designer

Reference:
Save changes to existing dashboards, lenses, and datasets in the app (saving dashboards requires the appropriate permission set license and permission) available in Editor and Manager*##**##*

Q30. What are predictive insights good for?

Predicting outcomes that you don’t actually have the right data for

Exploring your existing data to see what already happened

Drilling down into the underlying reasons behind a prediction

Choosing between all possible outcomes for a single variable

Q31. Before using bindings, you can try using facets to specify interactions between widgets.

False

True

Q32. Max story creations per org per day:

40 per org

40 per org per clay

20 per org

20 per org per clay

Q33. Maximum concurrent API Analytics calls per org

200

500

100

Q34. The Einstein Analytics Plus Platform license is enabled for a Salesforce org and assigned to each user. However, these users cannot see the Einstein Analytics Studio in the App Launcher.
How can this issue be addressed?

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.

Q35. A dataset is ready for analysis in Einstein Discovery.
What is the first step a consultant should take after the data is loaded?

Identify data types and define the appropriate data as numeric.

Analyze data columns and decide which, if any, to drop.

Produce a graph of the data to analyze.

Load the data into Einstein Analytics

Q36. 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.

Q37. How do you create a regression timeseries?

In SAQL, use the timeseries function with the following arguments: Partition (the group_by piece), Seasonality (set to 12 to get yearly seasonality).

Q38. Can you share data from a widget?

No, you can’t share data from a widget.

Select the step of the widget and share data.

Select “Share” icon, click on “Download”, and select “Download in .png, .XLS, or CSV” format.

Only with the proper Einstein Analytics Platform license.

Q39. What are the 3 basic actions within a query in Analytics? Choose 3:

Aggregate by a measure

Count rows by measure you want to visualize.

Filter to narrow down your results.

Grouping by a dimesnsion

Display the results graphically

Q40. 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

Reference:
https://help.salesforce.com/articleView?id=bi_limits.htm&type=5

Q41. Which of the following are included in the template object?

A,C

ui.json

variables.json

A,B and C

app.json

Q42. An Einstein Analytics consultant is notified of a performance issue with data sync (replication). The consultant researches the issue and determines that unnecessary data is being synced.
Which solution should the consultant implement to help improve data sync (replication) performance?

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.

Q43. Which chart type is best suited to track progress of sales revenue that is realized versus the target?

Bar chart

Flat gauge

Pivot table

Pie chart

Q44. Why is it important to select the right root object when you use the dataset builder?

The root object determines who can see the dataset.

Only data from the root object can be included in the dataset.

The root object determines what related objects you can add to the dataset.

The root object determines what app the dataset is saved in.

Q45. What are the steps in the data exploration process?

View, Explore, Refine, Save, Share

View, Explore, Reduce, Save, Share

Download, View, Refine, Save, Share

Q46. Which dataflow transformation does data sync (replication) reference, in an existing dataflow, to determine which Salesforce objects and fields are currently being extracted?

edgemart

sfdcRegister

export

sfdcDigest

Q47. What happens if you first disable Analytics, and then you re-enable Analytics later? Select 2

User permissions are removed from each defined permission set if Analytics is disabled. (Missed)

User permissions are not removed from each defined permission set if Analytics is disabled.

You must define the permission sets again if Analytics is re-enabled. (Missed)

You must not define the permission sets again if Analytics is re-enabled.

Reference:
https://blog.bessereau.eu/assets/pdfs/bi_admin_guide_setup.pdf

Q48. Trending data limits: Maximum number of trended datasets per user and rows per snapshot:

5 per user, 200,000 per snapshot

10 per user, 100,000 per snapshot

10 per user, 200,000 per snapshot

5 per user, 100,000 per snapshot

Q49. Universal Containers has a Sales Manager dashboard- They have a compare table that displays the count of Customers and the Sum of Annual Revenue per year and per Account type. A consultant is asked to add more groupings to enhance details about their customers.
What is the maximum number of grouping columns that the consultant must be aware of in order to continue using a compare table versus creating the query using SAQL?

unlimited

Q50. 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.

Reference:
https://medium.com/@kshannon565/ea-certification-study-guide-part-3-einstein-discovery-story-design-70ffbe4666c2

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