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Dimensional fact modeling – modeling the data warehouse basis Facts and Metrics – The Kimball Way

Dimensional modeling is the modeling approach suggested by Ralph Kimball who advocates building an enterprise data warehouse basis the key facts of the organization and then build the analysis around the same with a strong dimensional model to support various analysis.

What is Dimensional Modeling – let us take an Example. Here our LO extractor VAITM will serve as a good example. I am not taking the VAITM extractor but the fact – Invoice Line Item as an example.

Let us assume a simple Line which basically contains the following facts:

Quantity
Unit Price
Net Amount
VAT
Total Amount
Discount

Now let us examine the possible dimensions by which this can be analyzed…..

Product

Analyze sales by Product, Product Variant, Product Brand, Product Category, and Product Type

Customer

Analyze sales by Customer, City, Zone, District, and Country. Region

Time

Analyze sales by Day, Week, Month, Quarter, and Year

This would give an idea as to how cube / model design can be approached. Here a particular fact which is Invoice Line Item can be approached. The dimensions are not final and will usually depend on customer requirement and reporting needs but just a simple example to demonstrate how a dimensional model can be arrived at. Also this does not suggest that you keep all the attributes as Navigational Attributes, which I would leave to the architect to decide depending on data volumes and analysis requirements.

This is just my interpretation of Dimensional Modeling for a simple fact but need not conform to pure dimensional modeling views.

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