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InfoCube

Info Cube is structured as Star Schema (extended) where a fact table is surrounded by different dim table that are linked with DIM'ids. And the data wise, you will have aggregated data in the cubes.
Infocube contains maximum 16(3 are sap defines and 13 are customer defined) dimensions and minimum 4(3 Sap defined and 1 customer defined) dimensions with maximum 233 key figures and 248 characteristic.

The following InfoCube types exist in BI:
. InfoCubes
. VirtualProviders
There are two subtypes of InfoCubes: Standard, and Real-Time. Although both  have an extended star schema design, Real-Time InfoCubes (previously called Transactional InfoCubes) are optimized for direct update, and do not need to use the ETL process. Real-Time InfoCubes are almost exclusively used in the BI Integrated Planning tool set. All BI InfoCubes consists of a quantity of relational tables arranged together in a star schema.

Star Schema
In Star Schema model, Fact table is surrounded by dimensional tables. Fact table is usually very large, that means it contains millions to billions of records. On the other hand dimensional tables are very small. Hence they contain a few thousands to few million records. In practice, Fact table holds transactional data and dimensional table holds master data.
The dimensional tables are specific to a fact table. This means that dimensional tables are not shared to across other fact tables. When other fact table such as a product needs the same product dimension data another dimension table that is specific to a new fact table is needed.
This situation creates data management problems such as master data redundancy because the very same product is duplicated in several dimensional tables instead of sharing from one single master data table. This problem can be solved in extended star schema.
 



Extended star schema
In Extended Star Schema, under the BW star schema model, the dimension table does not contain master data. But it is stored externally in the master data tables (texts, attributes, hierarchies).
The characteristic in the dimensional table points to the relevant master data by the use of SID table. The SID table points to characteristics attribute texts and hierarchies.
This multistep navigational task adds extra overhead when executing a query. However the benefit of this model is that all fact tables (info cubes) share common master data tables between several info cubes.
Moreover the SID table concept allows users to implement multi languages and multi hierarchy OLAP environments. And also it supports slowly changing dimension.


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