In this blog, I am going to
discuss about one of the most important concept of DataWarehousing – Conformed Dimensions.
Regardless of any structural
design that an organization chooses, it is impractical to organize a single
project that will incorporate the entire business. Realistic project scope is
achieved by subdividing the business into subject areas (departments) and
subject areas into projects.
So how are these projects or departments linked?
At a logical level, when a
series of stars share a set of common dimensions, the dimensions are referred
to as conformed dimensions.
Examples will give a clearer
picture. In the below example, you can see how dimensions are shared across
Inventory and Sales subject areas. The time dimension is a common conformed
dimension in an organization. If you want to drill across to Inventory fact
through Sales fact, this can be possible only if there are conformed dimensions
between them and the conformed dimensions are of the same granularity. If
granularity is not same, then conformation is not possible.
Symbiosis of multiple stars:
Dimension tables conform when
attributes in separate dimension tables have the same column names and common
attributes. Whenever two star schemas are combined based on conformed
dimensions, there are two major benefits to an organization. Firstly, the organization
receives analytical benefits as it gains valuable insights into business
activity. It also helps the process to be studied with combination with other
processes. Some of the advantages of Conforming Dimensions are listed below:
Advantages:
Ø
Independent data marts become part of a fully
integrated data warehouse.
Ø
The development time for a data warehouse is
reduced because each dimension is analyzed, designed and created only once.
Ø
Conformed
dimensions deliver a consistent view of a business, allowing you to drill from
one area of the business to another.
Ø
Information
from separate fact tables can be combined in a single report by using conformed
dimension attributes that are associated with each fact table
We will look at a new topic in
the next post!
References:
The Data Warehouse Toolkit -
Third Edition, Ralph Kimball and Margy Ross
Star Schema - The Complete
Reference
http://pic.dhe.ibm.com/infocenter/cbi/v10r1m1/index.jsp?topic=%2Fcom.ibm.swg.ba.cognos.ug_ds.10.1.1.doc%2Fc_conformeddatawarehouses.html
