Dimension Table
Dimension Table is used to maintain Hierarchy Textual Information of business
process that integrated with Fact Table in the Data warehouse. FACT Table is
used to store measurements, metrics or facts of a business process in the Data
warehouse. Grain is the base business definition of Fact table that determine
measurement of business event.
By default, 1NF and 2NF is used to design Dimension Table and then 3NF to define
further more normalized Dimension Tables. A collection of unordered dimension
table's descriptive information is helps to generate Drill down or Roll up
Analytical Report that specify how Fact table data should be summarized.
An instance, when we buy any products in the supermarket, they sales person use
Scanner to capture data from Product Label and then stores "Sales Quantity" and
"Extended Price" in the Database through OLTP Application with relevant
information like Store, Product, Promotion, Invoice, Customer and Employee
information.
In this scenario, "Sales Quantity" and "Extended Price" are grain of Sales
event. Store, Product, Promotion, Invoice, Customer and Employee are entities of
Sales event that should define and maintain in the isolated dimension tables.
The following Sales Data Mart is designed with Sales_Fact and relevant shared
dimension tables to maintain Sales Historical Transaction information that will
help to generate Sales Analytical Reports through SQL Query.
Shared Dimensions
Data Mart is a subset of the Data Warehouse that based on Subjective of
Enterprise Business Unit or Team. Each Data Marts may or may not be dependent or
related to other Data Marts in the Data Warehouse.
Shared Dimensions are describes the core set of dimensions that shared across
the various cube perspectives in a Data Mart. These dimensions are allows the
measures in the cube to be summarized according to the different analytical
questions. Shared Dimensions are used to maintain and provide consistent
information for similar queries.
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