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You should decide upon the dimensional model you want to create. What are your measures? What are your dimensions? How can you distinguish between a dimension and an attribute in your data? You can design a dimensional model using pencil and paper, a database design software package, or any other method that suits you.
If your source data is in a star or snowflake schema, then you have the elements of a dimensional model:
Fact tables correspond to cubes.
Data columns in the fact tables correspond to measures.
Foreign key constraints in the fact tables identify the dimension tables.
Dimension tables identify the cube dimensions.
Primary keys in the dimension tables identify the leaf-level cube dimension members.
Parent columns in the dimension tables identify the higher level cube dimension members.
Columns in the dimension tables containing descriptions and characteristics of the cube dimension members identify the attributes.
You can also get insights into the dimensional model by looking at the reports currently being generated from the source data. The reports identify the levels of aggregation that interest the report consumers and the attributes used to qualify the data.
While investigating your source data, you may decide to create relational views that more closely match the dimensional model that you plan to create.