Subject Oriented:
Relevant and required data are presented as per the subject matter or area of concern, no matter the sources of data collection. Different subject matter can be treated and analyzed separately by retrieving necessary data from the collection of abundant quantity of data from the data warehouse. As an illustration, let us suppose there are departments like finance, human resource, accounting, sales and marketing departments in a company, and then each department can retrieve required data for their specific subject matter from a same storage of data …show more content…
But the basic architectural components of data warehouse are discussed below:
a. Data source layer
It is one of the components in data warehouse that serves as a supplier of data or information to be stored in a data warehouse. Data source may be any operational systems, flat files, web server logs or third party data source. Further, a data warehouse should treat any incoming information as data irrespective of data format they belong to. b. Data Extraction Layer
This layer comes after the data source layer where data gets extracted from data source into the data warehouse system. While extracting data, if there is a provision of update notification from source system then the updated data can be collected whenever notified, and this is a best approach to carry out in data extraction process. But some source systems may not have this notifying facility but can cite which data has been updated, and in this case a data warehouse can extract required data only. Some sources of data neither provides any notification nor points out the modified data, and this is the condition where full data is to be retrieved from data source. Sometimes data cleansing also occurs here but no major data transformation or modification is