SAP BW Interview Questions and Answers: 3

Q) What are the extra fields does PSA contain?

A) (4) Record id, Data packet …

Q) Partitioning possible for ODS?

A) No, It's possible only for Cube.

Q) Why partitioning?

A) For performance tuning.

Q) Different types of Attributes?

A) Navigational attribute, Display attributes, Time dependent attributes, Compounding attributes, Transitive attributes, Currency attributes.

Q. CAN U ADD A NEW FIELD AT THE ODS LEVEL?

Sure you can. ODS is nothing but a table.

Q) Why we delete the setup tables (LBWG) & fill them (OLI*BW)?

A) Initially we don't delete the setup tables but when we do change in extract structure we go for it. We r changing the extract structure right, that means there are some newly added fields in that which r not before. So to get the required data (i.e.; the data which is required is taken and to avoid redundancy) we delete n then fill the setup tables. To refresh the statistical data. The extraction set up reads the dataset that you want to process such as, customers orders with the tables like VBAK, VBAP) & fills the relevant communication structure with the data. The data is stored in cluster tables from where it is read when the initialization is run. It is important that during initialization phase, no one generates or modifies application data, at least until the tables can be set up.

Q) Different types of INFOCUBES.

  

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
• . VirtualProvider

• 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.