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Explain Bill Inmon's versus Ralph Kimball's Approach to Data Warehousing.
Bill Inmon vs Ralph Kimball
In the data warehousing field, we often hear about discussions on where a person / organization's philosophy falls into Bill Inmon's camp or into Ralph Kimball's camp. We describe below the difference between the two.
Bill Inmon's paradigm: 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.

Ralph Kimball's paradigm: Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model. Kimball model also proposes the data warehouse bus architecture. This architecture is comprised of:
- A staging area (which can have an E/R or relationally designed 3NF design or flat file format), which cannot be accessed by an end-user of the data warehouse bus.
-The Data Warehouse Bus itself which includes several atomic data marts, several aggregated data marts and a personal data mart but no single or centralized data warehouse component.
The Data Warehouse Bus:
- Is dimensional;
- Contains transaction and summary data;
- Includes data marts, which have single subject or fact tables; and
- Can consist of multiple data marts in a single data base.

There is no right or wrong between these two ideas, as they represent different data warehousing philosophies. In reality, the data warehouse in most enterprises are closer to Ralph Kimball's idea. This is because most data warehouses started out as a departmental effort, and hence they originated as a data mart. Only when more data marts are built later do they evolve into a data warehouse.



  
Total Answers and Comments: 2 Last Update: March 04, 2009     Asked by: Pranay 
  
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 Best Rated Answer
Submitted by: tisha24
 
Bill inmon's approach:
---------------------------
  •  Approach is "TOP DOWN approach".  ;means Emphasize the data warehouse. 
  •  Starts with designing an enterprise model for datawarehouse.
  •  Multi tier architecture - comprise of staging area,a Data warehouse and  dependent data marts. 
  • Persistant Staging area.
  • Warehouse is enterprise oriented ; and mart is functional specific.
  • Warehouse has atomic level data and marts have summary data.
  • Warehouse uses normalized enterpeise model. marts use subject specific dimensional model.
  • Can query both warehouse and marts.
Ralph Kimbal's approach:
-------------------------------
  • Approach is "BOTTOM UP approach".  ;means Emphasize the data marts. 
  • Starts with designing dimensional model for a datamart.
  • Flat architecture -  consists staging area and data marts.
  • Non Persistant staging area
  • Marts contain both atomic and summary data.
  • marts are designed for both enterprises and dimensional model.
  • marts consists single star schema.
  • marts use confirmed dimensions

 
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