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This is a TRANSFER routine (ABAP) DEFINED at the INFO object level; this is common for all SOURCE systems.

This is a transfer routine (ABAP) defined at the info object level; this is common for all source systems.

YES, either GLOBALLY or USING query debug tool RSRT.

Yes, either globally or using query debug tool RSRT.

Any SYSTEM that is sending data to BW LIKE R/3, LAT file, oracle database or EXTERNAL systems.

Any system that is sending data to BW like R/3, lat file, oracle database or external systems.

These CUBES are USED for both read and write; STANDARD cubes are optimized for reading. The TRANSACTIONAL cubes are used in SEM.

These cubes are used for both read and write; standard cubes are optimized for reading. The transactional cubes are used in SEM.

• INITIALIZE opening balance in R/3 (S278)
• activate extract structure MCO3BFO for data source 2LIS_03_BF
• SET up historical material documents in R/3 
• LOAD opening balance using data source 2LIS_40_S278 
• load historical movements and compress WITHOUT marker update. 
• set up V3 update
• load deltas using 2LIS_03_BF.

A structure consisting of INFOOBJECTS WITHOUT persistence for CONNECTING two TRANSFORMATIONS.

A structure consisting of InfoObjects without persistence for connecting two transformations.

DIM ID: are USED to connect fact tables and DIMENSION tables.

DIM ID: are used to connect fact tables and dimension tables.

• With availability of Multi-Core CPUs, higher CPU execution speeds can be achieved. 
• Also, HANA Column-based storage makes it easy to EXECUTE operations in PARALLEL using multiple processor cores. 
• In a column store data is already vertically partitioned. This means that operations on different columns can easily be processed in parallel. If multiple columns NEED to be SEARCHED or aggregated, each of these operations can be assigned to a different processor core. 
• In addition, operations on ONE column can be parallelized by partitioning the column into multiple sections that can be processed by different processor cores. With the SAP HANA database, queries can be executed rapidly and in parallel.

No; the cube must be empty to do this; one work around is to make a copy of the cube A to cube B; export data from A to B USING export data SOURCE; empty cube A; CREATE partition on A; re-import data from B; delete cube B.

No; the cube must be empty to do this; one work around is to make a copy of the cube A to cube B; export data from A to B using export data source; empty cube A; create partition on A; re-import data from B; delete cube B.

Row based tables:

• It is the traditional Relational Database approach
• It store a table in a sequence of ROWS

Column based tables:

• It store a table in a sequence of columns i.e. the ENTRIES of a column is stored in CONTIGUOUS MEMORY locations.
• SAP HANA is PARTICULARLY optimized for column-order storage.
• SAP HANA supports both row-based and column-based approach.

Row based tables:

Column based tables:

In traditional data warehouses, such as SAP BW, a lot of pre-aggregation is DONE for quick RESULTS. That is the administrator (IT department) decides which information might be needed for ANALYSIS and prepares the result for the END users. This results in fast performance but the end user does not have flexibility. 

The performance REDUCES dramatically if the user wants to do analysis on some data that is not already pre-aggregated. With SAP HANA and its speedy engine, no pre-aggregation is required. The user can perform any kind of operations in their reports and does not have to wait hours to get the data ready for analysis.

In traditional data warehouses, such as SAP BW, a lot of pre-aggregation is done for quick results. That is the administrator (IT department) decides which information might be needed for analysis and prepares the result for the end users. This results in fast performance but the end user does not have flexibility. 

The performance reduces dramatically if the user wants to do analysis on some data that is not already pre-aggregated. With SAP HANA and its speedy engine, no pre-aggregation is required. The user can perform any kind of operations in their reports and does not have to wait hours to get the data ready for analysis.

The SAP HANA DATABASE is DEVELOPED in C++.

The SAP HANA database is developed in C++.

This is to DISTRIBUTE data PER TIME; for example, if the source contains calendar week and the target contains calendar day, the data is SPIT for each calendar day. you can select EITHER the normal calendar or the factory calendar.

This is to distribute data per time; for example, if the source contains calendar week and the target contains calendar day, the data is spit for each calendar day. you can select either the normal calendar or the factory calendar.