Saturday, 7 February 2009

Kimball Vs inmon


There are two major design methodologies followed in data warehousing Ralph Kimball and Bill Inmon.We will discuss about both of these in detail.

Bill Inmon Approach : According to Bill Inmon Data warehouse need to fulfill need of all category of users .In an organization there are different type of user like

· Marketing
· Supply Change Management
· Operations

Each department has its different way of interpreting data so Data warehouse should be able to answer each department queries. This can be achieved by designing tables in 3NF form. According to him data in Datawarehouse should be in 3NF and lowest granularity level. The data should be accessible at detailed atomic levels by drilling down or at summarized levels by drilling up.

He stressed that data should be organized into subject oriented, integrated, non volatile and time variant structures. According to him an organization have one Data warehouse and Data mart source there information from Data warehouse. Inmon Approach is also called Top Down approach .


In this methodology data is brought into staging area from OLTP system or ODS (Operational Data store) and then summarized and aggregated. After this process data mart will source their data from data warehouse and will apply new set of transformation and aggregation according to their need.

Key points to be noted about this approach
1.Data should be organized into subject oriented, integrated, non volatile and time variant structures
2.Data in 3rd Normalization form
3.Top to down approach
4.Data Mart source from Datawarehouse

Pro’s of Bill Inmon approach
1. Easy to maintain
2. Well integrated
Cons of Bill Inmon approach
Difficult to implement

Ralph Kimball Approach :
Kimbell views Data warehouse as combination of data marts connected to Data warehouse bus structure.Data marts are focused on delivering business objectives of different departments and Data warehouse bus consists of conformed dimension, measures defined for whole organization. User can query all data marts together using conformed dimensions.

In this approach the data warehouse is not a physical storage of the data as in the Inmon approach. It is “virtual.” It is a combination of data marts, each having a star schema design .
In this approach data is always stored in dimensional model.



Key points to be noted about this approach are
1. Data is always stored in the dimensional model.
2. Bottoms Approach
3. Data ware house is Virtual
4. Bottoms's up approach

Pro’s of Ralph Kimball approach Fast to build

Cons of Ralph Kimball approach Difficult to maintain because of redundancy of data across data marts



 

Inmon

Kimball

Source Required

ü   

ü   

Staging

ü   

ü   

ETL

ü   

ü   

Data Marts

ü   

ü   

Business Requirements

ü   

ü   

Time attribute of data

ü   

ü   

Enterprise DW

ü   

                      X

Dimensional Tools

                      X

ü   

Relational Tool

ü   

X

Process Oriented

                      X

ü   

Normalised data Model

ü   

X

Complex to Design

ü   

X

Continous and Discrete Time Frame

ü   

X

Slowly changing Time Frame

                      X

ü   


Inmon vs. Kimball: Same or different?

  

"You can catch all the minnows in the ocean and stack them together and they still do not make a whale." ~Inmon

“The data warehouse is nothing more than the union of all the data marts" ~Kimball


Conclusion : In reality there is no right or wrong between these two approaches. In reality actual methodology implemented is combination of both.

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2 comments:

  1. In Bill Inmon's approach it's imposible to keep historical data in 3nf form and large databases implemented with his philosophy is a mess of data

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