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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:

Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

Question 1

In what order does Einstein Discovery present the insights that it uncovers?

A. Insights that explain the most variation in the outcome variable, in descending order
B. Alphabetical, in descending order
C. Insights that explain the most variation in the outcome variable, in ascending order
D. Alphabetical, in ascending order

Question 2

The Universal Containers company uses Einstein Analytics to build dashboards for different departments: Sales, Service, and Marketing. Users for the same department have the same role and need to have access to the same dashboards. Dashboards for different departments use some common datasets with the same row-level security.
How can an Einstein Consultant address this need?

A. Create one application for each department, put common datasets in the shared app, and use roles to share applications.
B. Create one application for each department, put common datasets in the shared app, and use profiles to share applications.
C. Create one application for each department, put common datasets in the shared app, and use permission sets to share applications.
D. Create one application for each department and use roles to share applications.

Question 3

In Einstein Analytics, which node is used in a dataflow to extract data from a registered dataset?

A. export
B. sfdcDigest
C. digest
D. edgemart

Question 4

An Einstein consultant created a dashboard that went through review. Some few charts were added and removed in the process. The dashboard is now approved for production.
Which best practice should be done before releasing the dashboard?

A. Modify the XMD so all labels and values are user-friendly.
B. Rename all the steps to correspond with the defined naming convention.
C. Remove the redundant steps to ensure dashboard performance.
D. Apply conditional formatting on the new charts.

Question 5

Why would you use a merge key in a dataset recipe?

A. To deal with duplicate records
B. To find out what the merge icons represent in a dataset
C. To schedule when a dataset recipe runs
D. To join related data from different sources

Solutions: