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I have two transactional systems that is used for the same operational business activity: purchase order transactions. One system is legacy and the other is a new modern one. They have different underlying source system data models. The finance team requires historical data (from the legacy system) and current data (from new system) to support their business analytics. I am about to build a new data warehouse. Given that both systems have different underlying data models is the first place I am stuck (i.e., stuck at the Architectural design phase). One of the business goal is to consume the data from both systems to obtain a ratio measure/metric. Data from both systems cannot be mapped directly given they have different models with different granularities, and hence it is difficult to have conformance. The business ideally wants to have both system datasets integrated.

I am considering two design approaches for two different source systems which measure the same business process:

  • Create two separate dimensional models for the two systems
  • Create a single dimensional model but represent both systems in separate fact tables

I researched and read Kimball resources. A summary:

Each business process subject area is designed using a nine-step design methodology:

  1. Choose the process.
  2. Choose the grain.
  3. Identify and conform the dimensions.
  4. Choose the facts.
  5. Store precalculations in the fact table.
  6. Round out the dimension tables.
  7. Choose the duration of the database.
  8. Determine the need to track slowly changing dimensions.
  9. Decide the physical design.

(From The Kimball group reader: relentlessly practical tools for data warehousing and business intelligence by Kimball, Ralph, and Margy Ross, John Wiley & Sons, 2010.)

The material I have come across only addresses the common situations faced by designers.

What are design considerations for this case of two systems measuring the same business process?

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