To design a datawarehouse one need to design dimensional data model. The dimensional data model provides a method for making databases simple and understandable by denormalizing it and removing extra join which are generally required to fetch the data. In general you can imagine dimensional database as a cube of three or more dimensions using which users can access a data in all possible way by slicing it.
Lets first understand the terms and terminology used in Dimensional Model
Dimension:
is a an data element against which data or performance is measured. A data warehouse dimension provides the means to slice and dice the data in a data warehouse.
e.g. Customer, Day, Month are dimension
Fact:
is generally a numerical value representing measurement.
e.g. Revenue, count of users
Hierarchy:
represent the navigation path of dimension which can be used to drill-up or drill-down data in reports in order to see data at different level.
e.g.
Year -> Month -> Week -> Day
As opposed to relational data model which uses ER Model, dimensional modeling uses either star schema, snowflake schema.
Did you enjoy this article? Please subscribe to Email or RSS to receive all the FREE updates!
Related posts: