Inmon Vs Kimball

Inmon Vs Kimball: Which approach for data warehousing is better?

Firstly, one should know the difference between datawarehouse and data mart.

Data warehouse or Data Mart?

Data Warehouse:

• Holds multiple subject areas
• Holds very detailed information
• Works to integrate all data sources
• Does not necessarily use a dimensional model(denormalized data model) but generally feeds dimensional models.

Data Mart

• Often holds only one subject area- for example, Finance, or Sales
• May hold more summarised data (although many hold full detail)
• Concentrates on integrating information from a given subject area or set of source systems
• Is built focused on a dimensional model using a star schema.
 

 

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. Data Marts are physical.

Data Warehouse –Normalized Data Model in 3NF

 

 

 Ralph Kimball's paradigm:

Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model. Data Marts are Logical(Views).

Data Warehouse –De-normalized Dimensional Data Model

 

Misconception:

Actually, there is no right or wrong between these two ideas, as they represent different data warehousing philosophies. In reality, the data warehouse systems 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.  

Likewise, most people working in Data Warehousing would rather skip the Data Warehouse and go straight to the Data Mart.

In Industry, people often claims to be one of these methodologies, however, often they are using a combination of parts of two or more, usually all three!