Easily Tracking Dataset Customer Economics

[ZenGround0]

From issue #1352

• Identify the customer associated with each dataset or service.
• Define the customer identity used for aggregation, including how datasets are grouped when payer, client, contract, or account identities differ.
• Calculate and expose revenue already earned by each dataset or service.
• Include settled payments and one-time payments.
• Calculate projected future revenue for each dataset or service using the applicable service rate.
• Aggregate the SP's complete relationship with the customer, including:
• Total number of active datasets or services belonging to the customer.
• Total revenue earned across those datasets or services.
• Total projected future revenue across those datasets or services.
• Aggregate recurring revenue or annualized revenue, where the service terms support that calculation.
• Clearly distinguish the economics of the dataset under review from the economics of the customer's complete portfolio with the SP.
• Define how dataset-level and customer-level projections behave when rate, duration, settlement, customer identity, or service-state information is incomplete.
• Expose both dataset-level and customer-level calculations through an API suitable for the console review workflow.
• Reuse the financial presentation foundation introduced in Style the UI to work better for PDP #1351.

Essentially this issue is tracking a UI integration that makes it very easy for operators to make dataset level decisions based on customer relationships and finances.