Conformed dimentions are dimensions which are common to the cubes.(cubes are the schemas contains facts and dimension tables)
Consider Cube-1 contains F1,D1,D2,D3 and Cube-2 contains F2,D1,D2,D4 are the Facts and Dimensions
here D1,D2 are the Conformed Dimensions one dimension can share with more fact tables through primary key and foreign key relationship.
Time dimension are used to represent the datas or measures over a certain period of time.The server time dimension is the most widley used one by which we can represent the datas in hierachal manner such as quarter->year->months->week wise representations.
Since in OLTP,tables are normalised and hence query response will be slow for end user and OLTP doesnot contain years of data and hence cannot be analysed.
Conformed dimensions mean the exact same thing with every possible fact table to which they are joined
Ex:Date Dimensions is connected all facts like Sales facts,Inventory facts..etc
Granularity
The first step in designing a fact table is to
determine the granularity of the fact table. By
granularity, we mean the lowest level of information
that will be stored in the fact table. This
constitutes two steps:
Determine which dimensions will be included.
Determine where along the hierarchy of each dimension
the information will be kept.
The determining factors usually goes back to the
requirements
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