Data Warehousing

Data Warehouse (DW) is a concept where in data is stored in database in summarised format and based on reporting requirements of business. The data can then be analysed using data mining techniques to gain advantages over business rivals.

DW provides a set of functionalities. DW can extract data from various data sources (e.g. flat file, tables, etc.) and stored data in its own databases. DW also provides functionalities for query and analysis.

Business Warehousing is one of the concept which is used to setup a data warehouse. DW is designed considering reporting and analytical requirements of business. SAP BW provides solution related to business warehousing where in data can be transformed, cleansed, loaded, scheduled, monitor and reported based on business reporting requirements

In Online Transaction Processing (OLTP, e.g. SAP R/3, ECC), normalization is used as database design technique where in same information is available only at one place. Objective of normalization is to avoid data redundancy and data integrity issues. Hence if an information is updated at one place, there is no need to update it at another place and updated information is available where ever it is retrieved.

Star Schema

To facilitate data retrieval from data warehouse, a special database design technique is used which is called 'Star Schema'.

Star Schema uses a Fact table and several Dimensional tables. Fact table is a central table which is surrounded by many dimensional tables. Hence the name Star Schema.

Following is an example of Star Schema:


Fact Table: At the centre
Dimensional Table: Surrounding (Customer, Product and Location)

A star schema consists of many dimensions, hence term Multidimensional Analysis is also used. One dimension can have many attributes. These attributes allows to drill up and down to analysis data.

In the example, dimension 'Location' has one of the attribute as 'Region'. Hence, reporting can be done at region level as well.