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NEW QUESTION 39 Refer to the graphic. Einstein found a recommendation to improve the story: apparently there are two variables that behave the same. Given there is no additional information, what is the correct action?

• A. Retain Promotion; it is an actionable variable and without it, we cannot recommend prescriptive actions.
• B. Cancel this story and redefine the dataset.
• C. Do nothing; they appear to be similar, but there might be differences from the business perspective.
• D. Retain Amount; not knowing the size of a deal makes it hard to predict if will be won.

Answer: C   NEW QUESTION 40 What is an appropriate response when a client is disappointed that Einstein Discovery only detected patterns that were already known?

• A. Advise them that the use case may not be accurate.
• B. Remind them that the technology is only as good as the data.
• C. Recommend using a visualization tool, like Einstein Analytics, to uncover the details.
• D. Highlight that Einstein reduces time to insight, which is much faster than learning from experience.

Answer: B   NEW QUESTION 41 A large company is rolling out Einstein Analytics to their field sales. They have a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy. An individual Sales rep should be able to view all opportunities that she/he owns or as part of the account team or opportunity team. The Sales Manager should be able to view all opportunities for the entire Sales team. Similarly, the Sales Vice President should be able to view opportunities for everyone who rolls up in that hierarchy. The opportunity dataset has a field called 'Ownerld' which represents the opportunity owner. Given this information, how can an Einstein Consultant implement the above requirements?

• A. 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".
• B. 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' == "$User.UserRoleId" && 'Ownerld' == "SUser.Id".
• C. As part of the dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || TeamMember.Id' == "$User. Id" || 'Ownerld' == "SUser.Id".
• D. As part of the dataflow, use computeRelative on the Roleld field to create an attribute called 'ParentRolelDs' on the opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || 'Ownerld' == "$User.Id".

Answer: C   NEW QUESTION 42 In Einstein Analytics, which node is used in a dataflow to extract data from a registered dataset?

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

Answer: D   NEW QUESTION 43 Which of these standard deviations is for a curve that has values that are the most spread out away from the average?

• A. 0
• B. 1
• C. 2
• D. 3

Answer: A   NEW QUESTION 44 ......