Ralph Kimball Data warehouse model

Ralph Kimball Data warehouse model and Development approach

Ralph Kimball is well known author who introduced new pattern of data storage in Data Warehouse, so called Dimensional Data Architecture; Based on Fact and Dimension tables.

Kimball’s model is much more refined and simplified, where all Subject oriented data you can store in Dimensions, and measures In fact tables; whereas all dimension tables will be connected to fact tables by foreign key relation.

Ralph Kimball introduced Star and Snowflake Schema, to store data in Data Marts/ Data Warehouse.

Implementing this model is very easy and time saving. But Kimball’s model mostly suitable for small and mid-cap industries like Automobile, Education, and Retail.

Here is I have tried to Design Kimball’s DW model

Ralph Kimball’s Model follows Bottom to Top approach, that is nothing but lowest level of detailed data is stored in Data Marts. That is the reason this approach is called Bottom Up approach.

Here Subject Oriented data is stored in Dimension tables and Measures of same data will be stored in Fact tables. 

Take an Example of Students Enrollments, Students Information and Enrollment information; will be stored in Dimension tables whereas number of Students enrolled per class, per Year, percentage will be stored in Fact tables; And dimension tables will be connected to fact table by foreign key relation.

To normalize data at maximum level Kimball introduced Snowflake Schema. One dimension is further subdivided into another dimension, connected with foreign key.

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