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 ableto 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?
- 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' == "$User.Id". - As part ofthe dataflow, use the flatten operation on the role hierarchy and create a multivalue attribute called 'ParentRolelDs' on the opportunity dataset and apply following security predicate: 'ParentRolelDs' == "$User.UserRoleId" || TeamMember.Id' == "$User. Id" || 'Ownerld' == "SUser.Id".