Lineitem setting in cubes

star scema:

foCubes are made up of a number of InfoObjects. All InfoObjects (characteristics and key figures) are available independent of the InfoCube. Characteristics refer to master data with their attributes and text descriptions.

An InfoCube consists of several InfoObjects and is structured according to the star schema. This means there is a (large) fact table that contains the key figures for the InfoCube, as well as several (smaller) dimension tables which surround it. The characteristics of the InfoCube are stored in these dimensions.

An InfoCube fact table only contains key figures, in contrast to a DataStore object, whose data part can also contain characteristics. The characteristics of an InfoCube are stored in its dimensions.

The and the fact table are linked to one another using abstract identification numbers (dimension IDs) which are contained in the key part of the particular database table. As a result, the key figures of the InfoCube relate to the characteristics of the dimension. The characteristics determine the granularity (the degree of detail) at which the key figures are stored in the InfoCube.

Characteristics that logically belong together (for example, district and area belong to the regional dimension) are grouped together in a dimension. By adhering to this design criterion, dimensions are to a large extent independent of each other, and dimension tables remain small with regards to data volume. This is beneficial in terms of performance. This InfoCube structure is optimized for data analysis.

The fact table and dimension tables are both relational database tables.

lineitem using in cubes:

Line item: This means the dimension contains precisely one characteristic. This means that the system does not create a dimension table. Instead, the SID table of the characteristic takes on the role of dimension table. Removing the dimension table has the following advantages:

○       When loading transaction data, no IDs are generated for the entries in the dimension table. This number range operation can compromise performance precisely in the case where a degenerated dimension is involved.

○       A table- having a very large cardinality- is removed from the star schema. As a result, the SQL-based queries are simpler. In many cases, the database optimizer can choose better execution plans.

Nevertheless, it also has a disadvantage: A dimension marked as a line item cannot subsequently include additional characteristics. This is only possible with normal dimensions.