✒️SAP BI / BW BO Data Store Objects (ODS o DSO)
SAP BI / BW BO Data Store Objects (ODS o DSO)
Difference between Persistent Staging area and Operational Data Store to get to info cubes and reports? Persistant Staging area is used as a temporary space to hold data before it is loaded to the SAP BI system. As the operational system OLTP cannot be kept out of service for long, we use the PSA.
All the data in the source system is copied as it is to the PSA. Transformations are then carried out on PSA data before it gets loaded in the SAP BI system.
Operational Data Stores or DSO objects are used to store very detailed data or highly granular data.
This data is not suited for analysis or reporting unless the report requires detail data. DSOs can be used to take data from different sources and then combine them in a single DSO object. This data can then be transformed and sent to an InfoCube.
From SAP BI 7.0 onwards, it is mandatory to use PSA for loading data in the BI system.
So, these two perform different roles. PSA acts as a temporary buffer and ODS used to store granular data.
The Persistent Staging Area (PSA) is the inbound storage area for data from the source systems in the SAP Business Information Warehouse.The requested data is saved, unchanged from the source system. Request data is stored in the transfer structure format in transparent, relational database tables in the Business Information Warehouse. The data format remains unchanged, meaning that no summarization or transformations take place, as is the case with InfoCubes. When loading flat files, the data does not remain completely unchanged, since it is adjusted by conversion routines if necessary (for example, the date format 31.21.1999 is converted to 19991231 in order to ensure uniformity of data)
DataStore Object Definition
A DataStore object serves as a storage location for consolidated and cleansed transaction data or master data on a document (atomic) level.
This data can be evaluated using a BEx query.
A DataStore object contains key fields (such as document number, document item) and data fields that, in addition to key figures, can also contain character fields (such as order status, customer). The data from a DataStore object can be updated with a delta update into InfoCubes (standard) and/or other DataStore objects or master data tables (attributes or texts) in the same system or across different systems.
Unlike multidimensional data storage using InfoCubes, the data in DataStore objects is stored in transparent, flat database tables. The system does not create fact tables or dimension tables.
UseOverview of DataStore Object Types
Type |
Structure |
Data Supply |
SID Generation |
Details |
Example |
Standard DataStore Object |
Consists of three tables: activation queue, table of active data, change log |
From data transfer process |
Yes |
Standard DataStore Object |
Operational Scenario for Standard DataStore Objects |
Write-Optimized DataStore Objects |
Consists of the table of active data only |
From data transfer process |
No |
Write-Optimized DataStore Object |
Operational Scenario for Write-Optimized DataStore Objects |
DataStore Objects for Direct Update |
Consists of the table of active data only |
From APIs |
No |
DataStore Objects for Direct Update |
Operational Scenario for DataStore Objects for Direct Update. |
You can find more information about management and further processing of DataStore objects under:
Managing DataStore Objects
Further Processing of Data in DataStore Objects
IntegrationYou can find out more about integration under Integration into the Data Flow.
 
 
 
Sobre el autor
Publicación académica de Mary Galicia, en su ámbito de estudios para la Carrera Consultor en SAP BI / BW BO.
Mary Galicia
Profesión: Ingeniero en Informatica - Venezuela - Legajo: JZ82V
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