At the outset, I would like to point out that conformed dimensions is a concept and not a technical element. You will therefore have understood that you will not find tips & tricks or code examples in this article but an explanation of a business intelligence (BI) concept. In this article, I’ll define for you the concept of conformed dimensions, put your brain to the test with an exercise, and share with you a use case of conforming dimensions.
What is a conformed dimension?
Conformed dimensions are a key concept in business intelligence, especially in star data models. If we define this concept at a high level, we can summarize that conformed dimensions are dimensions that are shared by several facts (processes). In this way, the data of the different fact tables can be analyzed and compared with each other with the dimensions that conform (which are shared). Typically, conformed dimensions are defined only once in an organization. It is in collaboration with the governance teams or the business matter experts that they are defined.
Properly identifying these dimensions provides several advantages, including the following:
- Analytical consistency across datasets (a single version of the truth).
- Reduced development time (the same dimension can be reused or instead of being recreated).
