The set of info cubes delivered by SAP as a part of SAP BIW which are useful in measuring the performance of how quickly a query is calculated, or how quickly data in loaded into BW and so on. BW statistics are the name suggest are useful in showing data about the costs associated with BW queries, aggregative data, OLAP, SAP business warehouse management.

In order to improve the performance SAP is using the fact table. It can be partitioned only on 0CAlMONTH or 0FISCPER.

1. Identify Dimension Tables.
2. Identify Attributes of entities.
3. Define granularity of the fact table.
4. Pre Calculated Key figures.
5. Slowly changing dimensions.
6. Define attributes of entities.
7. How long data will be kept.
8. Aggregates.
9. How often data is extracted.

When ABAP code is required during the transfer rule the important variables that can be used are by assigning info objects, assigning a constant, ABAP routine or a formula.

There are 16 out of which 3 are predefined time, unit and request, customer is left with 13 dimensions.

It system can be used as many as possible for performance, for instance it may be assumed that 100 products and 200 customers; if one dimension for both, the size of the dimension will be 20000; if it was made individual dimensions then the total number of rows will be 300. Even if they are taken more than one characteristic per dimension, the math considering worst case and decide which characteristics may be combined in a dimension.

As per the update rule, the Time dimensions are automatically converted for example if the cube contains calendar month and the transfer structure contains date, the to calendar month is converted automatically.

1. Uses Numeric as indexes for faster access.
2. Master Data independent of info cubes.
3. Language support.
4. Slowly changing dimension support.

When the report on characteristics or master data, it can make them as info provided for example make 0CUSTOMER as info provided and do Bex reporting on 0CUSTOMER, right click on the info area and select “Insert Characteristic as data target”

1. M view – Combines P and Q tables.
2. P table – Time independent master data attributes.
3. Q table – Time Dependent master data attributes.
4. X table – Interface between master data SID and time independent navigational attributes SID where P is linked to the X table.
5. Y table – Interface between master data SID and time dependent navigational attributes SID where Q is linked to the Y table