A company used Einstein Analytics to create two datasets:
1. "Opportunity With Account- dataset, which contains data from the Opportunity standard object augmented by the Account data.
2. "Case with Account" dataset. which contains data from the Case standard object augmented by the Account data.
The company wants to build a lens showing the total number of Opportunities and Cases per Account. How can a consultant help them build this lens'

• A.Use "Compare Table" to join the "OpportunityWithAccount" and "CaseWithAccount" datasets using the
  "Accountld" and then aggregate by Account.
• B.Use a SAQL query to group and join the "OpportunityWithAccount" and "CaseWithAccount" datasets then generate the results.
• C.Set up Connect Data Sources in the UI between the "OpportunityWithAccount" and "CaseWithAccount" datasets.
• D.Create a recipe to generate a new dataset from the "OpportunityWithAccount" and "CaseWithAccount" datasets aggregated by Account, and use the generated dataset in a lens.

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

• A.Count rows by measure you want to visualize.
• B.Grouping by a dimesnsion
• C.Aggregate by a measure
• D.Filter to narrow down your results.
• E.Display the results graphically

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A consultant built an Einstein Analytics app for the Sales Operations team. The Sales Operations team wants to share their app with other people at the company. The consultant recommends distributing the app as an Einstein Analytics template app.
What can the consultant do to give the Sales team more choices and options with future apps that are generated from the Sales Operations app'

• A.Update contents in the Sales Operations app and changes will be pushed down to its generated apps.
• B.Ensure the Sales team has the necessary permissions to customize their apps.
• C.Create a configuration wizard for the app.
• D.Update contents in the Sales Operations app and create new template versions of the app.

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The Universal Containers company used Einstein Analytics to create two datasets:
Dataset A: contains a list of activities with an "activityID" dimension and a "userID" dimension Dataset B: contains a list of users with a "userID" dimension The team wants to delete from Dataset A all activities related to users in Dataset B.
How can an Einstein Consultant help them achieve this?

• A.Use the recipe operation "delete" and set "userID" as the deletion ID
• B.Use an external ETL tool to extract both datasets and delete records
• C.Use a combination of dataflow transformations: "augment" and "filter"
• D.Use the dataflow transformation "delete" and set "userID" as the deletion ID

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What can you do with the dataflow?

• A.Build a dashboard
• B.Extract Salesforce object data into Analytics
• C.Explore a dataset
• D.Extract data from an external CSV file into Analytics

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