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?
A consultant built an Einstein Analytics dashboard for a company. The company then requested an enhancement to the dashboard and provided additional data that needs to be displayed. As a result, the consultant decides to "augment" the dataflow. Which phrase describes this transformation?
An Einstein Analytics team reports that when they start their dataflow it runs successfully with no errors or warnings, but one of the fields does not return values when it is queried. What can be the origin of this issue?
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?
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.
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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 'OwnerId' which represents the opportunity owner. Given this information, how can an Einstein Consultant implement the above requirements?
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?
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
two.)
An Einstein Analytics consultant is asked to add a new SalesTax field to a Product Sales dataset. The formula to calculate SalesTax is (SubTotal*CountyTax). Which node should the consultant use in a Dataflow to calculate and insert SalesTax to the dataset?