Inmon Vs Kimball

I work on data warehousing, so today I thought of brushing up my concepts. Here are few, which I came across:

1. Success of a data wareshouse depends on effectively gathering business requirements first.

2. Inmon Vs Kimbal
These two are considered to be the god of data wareshousing. But had differences in their approach to design and architecture of a data warehouse.
Inmon believed in Top down approach : Data warehouse is one part of the overall business intelligence system. An enterprise has one data warehouse, and data marts source their information from the data warehouse. In the data warehouse, information is stored in 3rd normal form at the atomic level,which is then aggregated and made accessible across the enterprise.The CIF architecture embraces the star schema design for the data marts only, NOT for the design of the data warehouse.Inmon describes the Kimball approach as "brittle" because, in his opinion, the star schema is closely aligned to end-user requirements. Therefore, it does not produce a reusable form of data for the enterprise. In the Inmon approach, star schemas are only used for dependent data marts.
Kimball believed in Bottom Up approach : Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.His approach does not require a normalized data structure prior to dimensional presentation.The presentation in the Kimball approach is only through data marts. No physical data warehouse, as required by the Inmon approach, is required. His approach is considered to be faster because the data does not have to undergo multiple ETL before it is presented to the business users.However, Kimball's point is "If you make atomic data available in dimensional structures, you can always summarize the data "any which way."
Storing the atomic data in dimensional structures provides business users with the ability to get answers to immediate and, sometimes unpredictable, problems.
According to the Kimball approach, this puts usable data in the hands of the business user making the query without requiring a data warehouse expert to drill into the different normalized structures for the data.
Mr. Kimball also points out that his approach uses the enterprise data warehouse BUS architecture "with common, conformed dimensions for integration and drill-across support. Conformed dimensions are the backbone of any enterprise approach..."

To counter the idea of storing atomic data in dimensional structures, Inmon says that this will limit the analysis of data using only mulidimensional methods. The main reason for storing the data in 3NF form in data ware house is that the analysis is not limited to multidimensional methods.

So, it all depends upon what the business requirement is , what atomicity is required, type of analytical tools being used and the time and resource available for building and maintainting the data warehouse. Inmons approach might need datawarehouse experts to build summarized datamarts and explaining users how to drill down to the atomic level where as in Kimballs approach the users them self can summarize the data as it is presented to them at atomic level.



coming up next is Conformed dimensions....