In this article, Bill Inmon compares and contrasts the Inmon and Kimball approaches to data warehousing, highlighting the pros and cons of each approach.
Occasionally someone brings up the differences between the Kimball approach to data warehousing and the Inmon approach. In years past, the subject came up almost daily. In recent vintage, the subject comes up less frequently, but it still comes up.
Four times I have invited Ralph to a public seminar or conference to discuss the differences in public. And four times – for reasons known only to Ralph – he has declined. So rather than have a single public debate where people can decide for themselves what the differences are, the next best thing is to have a debate where Ralph doesn’t show up. In this unusual format, I will argue for both the Kimball and the Inmon approach. Admittedly there may be some bias in the arguments; but if Ralph won’t show up, I will show up for him.
The Kimball approach to database design and development is typified by the star schema design of databases. There are fact tables and dimension tables. In a complex environment, there are snowflake structures, which are merely extended versions of the star schema. In order to resolve differences of granularity between fact tables, conformed dimensions are used. Staging areas are occasionally used to capture raw data before the placement of the data into a Kimball style data mart.
The Inmon approach to data warehousing centers around a relational, non redundant, granular, integrated design of detailed data. From this base of data, data marts are spun off to different departments according to their individual analytical needs. In recent vintage, with DW 2.0, the Inmon approach calls for the recognition of the life cycle of data within the data warehouse, the inclusion and integration of unstructured data within the data warehouse, and the close integration of metadata into the data warehouse infrastructure.
Those then are short statements of the highlights of the Kimball approach and the Inmon approach to data warehousing.
From an architectural standpoint, there are many arenas of agreement between the Kimball approach and the Inmon approach. But there are even more arenas of disagreement.
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