Revenue accounting model

01 / Judgment

The problem and the choice

The normalized operational source required repeated joins and interpretation before analysts could answer reporting questions. The proof of concept explored a more useful structure for Power BI.

Make grain and business identity explicit before defining analytical relationships and measures.

02 / Delivery responsibility

What I owned

I mapped source entities into a proposed star schema with a stated grain, fact and dimension tables, and semantic definitions. The design retained business keys for traceability and considered surrogate keys and attribute history where appropriate.

• Mapped operational entities into proposed fact and dimension structures.
• Defined grain and relationships to support the intended reporting questions.
• Considered business keys, surrogate relationships, and attribute history in the design.

03 / Working with others

How the work moved forward

My contribution was the proposed model design for Power BI reporting, translating operational entities into a structure intended for analytical use.

04 / Technical detail

The implementation decisions

Grain

The design declared a unit of analysis for each fact rather than allowing report joins to determine row meaning implicitly.

Identity

Business keys preserved source traceability; surrogate keys supported analytical relationships where appropriate.

History

The design considered attribute history where changes would affect reporting meaning.

05 / Validation

Validation evidence

This was a model design and conceptual validation exercise against the intended reporting questions. The case does not establish a production reconciliation or performance benchmark.