The Universal Containers company used Einstein Analytics to create two datasets:
Dataset A: contains a list of activities with an "activitylD" dimension and a "userlD" dimension Dataset B: contains a list of users with a "userlD" 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 consultant is working with a credit card company that needs help with ongoing fraudulent transactions. The company provides a representative sample dataset for the consultant to analyze in Einstein Discovery. The story's initial assessment shows that a third-party payment app is the source of these fraudulent transactions. However, the company rejects this assessment outcome, stating they have not had a partnership with this payment app long enough for it to be a concern.
What is the recommended next step to improve the story outcome?
A consultant has been brought in to help increase the adaption of Tableau CRM. It has been identified that account managers are struggling to get an overview of their accounts before meeting with them. Ideally they would like to have key details highlighted about active cases and opportunities, opportunity value and product whitespace.
What can the consultant do to increase adoption?