Why is dimensional modeling used in data warehouse?
Dimensions and Facts are the basic building blocks of a data wearhouse! All your data models would be primarily be based on only these two fields!
Dimensions or characteristics or columns all mean the same, they are descriptive fields, for example: Customer, Employee etc..
Measures or key figures are the quantitative fields, for example: Salary, Total Sales..
Data warehouse is a place where you store your data redundantly after it’s extracted, transformed and cleansed from your source! Once you get your data loaded into the DW, you need to make it more informative and readable for your end users which should provide them a better understanding of their business!
This is when you need to create Dimensional data models and all your business reports run on such data models, so if you are working on a employee report, the data model which you create should be modeled around employee i.e all the facts which are in your DW should be w.r.t sales dimension!
Dimension modeling is also know as slice and dice of data I.e measures can be viewed at any level of granularity be it employee, customer etc..