Chapter 2 Flashcards
Data Modeling Process
- Create the necessary InfoObjects (characteristics and key figures)
- Create the entrance layer with DSOs
- Create data targets
- Create data sources (source systems and DataSources)
- Create extractors
- Create transfer rules
- Use process chains to schedule data load processes
- Create analyses
Semantic Layer
This semantic layer allows you to join different data sources and to create shared definitions. It forms a middleware layer for reporting

Data Warehousing Workbench
- Modeling
- Administration
- Transport Connection
- Documents
- BI Content
- Translation of BW Objects
- Metadata Repository
Characteristic types
- Characteristics with texts
- Characteristics with master data (attributes)
- Characteristics with time dependency (master data and/or texts)
- Characteristics with hierarchies
- Characteristics without texts/master data
Characteristics with Texts
Characteristics with texts are surely the most frequent instance of InfoObjects. This type is used whenever there is descriptive text in addition to a key value. The plant key and corresponding text are shown as an example (see Table 2.2).

Characteristics with Master Data (Attributes)
The most important element for data modeling is the characteristics (InfoObjects) with attributes (other referencing characteristics). These additional attributes are called master data for the characteristic.
Customer Class
Characteristic with text that explains the key and makes it language-dependent
City
Characteristic without text, which saves a value that is not explained further
Country
Characteristic with text that explains the key and makes it language-dependent

Characteristics with Time Dependency (Master Data and/or Texts)
This type of characteristic represents a peculiarity within the group of characteristics described above. It is often necessary to allow certain attributes for a characteristic
to change over time. For example, a customer can belong to different customer classifications over the course of several years. If you need to map these changes in the analyses, it’s often necessary to save these changes in the InfoObject.
Therefore, each attribute provides an option of setting it time-dependently
for the InfoObject. When this option is active, all combinations of characteristic
and attribute are assigned time stamps for Valid from and Valid to.
Characteristics with Hierarchies
The most frequently used method is creating hierarchies
directly for the respective InfoObjects. SAP provides several example hierarchies of
InfoObjects: You can use the cost centers and organization hierarchy from SAP ERP,
for example.
Characteristics without Texts/Master Data
This is a special kind of characteristic. Only texts or key values for an InfoObject are loaded, for example, but the keys are not translated or elaborated in any more detail. They are usually used to model city and street names. The special InfoObjects
Calendar day and Calendar year do not require supporting texts either.
Key Figures
used whenever numbers are given a specific correlation and will be used for calculation in some way later. Key figures can be created either with or without units. A key figure such as number, for example, which counts the
number of records, is created without a unit. In contrast, weights and revenues are usually assigned units. Revenues always have a currency unit as specification.
Weights and other key figures need units so they can be set in relation.
Therefore, the most important factor when modeling key figures is to define the units correctly.
DataStore Objects
While InfoObjects represent the central modeling elements in the BW system, the DataStore objects (DSOs) are the main level in EDW.
These DSOs not only save the data in the form of transparent tables but also calculate necessary items, such as deltas between the old and new datasets. It’s possible, for example, for a DSO to calculate current stock levels. To do so, the respective stock changes are written to a DSO and the new stock levels are calculated there. These figures can then be updated in InfoObjects (to see a minimum stock notification, for example) or in InfoCubes for reporting.
DSO Types
- Standard DSOs
- Write-optimized DSOs
- DSOs for direct writing
- Semantic DSOs
Standard DSOs
They consist of three logical units:
- New data
- Active data
- Delta
The new data collects all new data from the respective source system at the request level. When this data is transferred to the active data, it is merged. If the stock of a stock material has dropped from 250 pieces to 150, for example, the value 250 is overwritten with 150 in the active data. At the same time, a delta record is generated that contains -100 pieces. This record can then be updated in the respective data targets. We therefore recommend using the standard DSO as the inbound data store for all data sources in EDW.
Write-optimized DSOs
A write-optimized DSO is a standard DSO that only consists of one table: the active data. As a result, all data is still aggregated there, and a special key combination
is used to ensure that data is overwritten. This DSO is used whenever the data from the data source is already delivered in a logical, sensible form. Data from this DSO can also be updated in the data targets using deltas.
DSOs for direct writing
This DSO is not filled with transfer rules using a data flow, but instead with ABAP programs. As a result, it can be used as a data target for Integrated Planning or for results from the Analysis Process Designer (APD). It can also be used for custom applications, because it can be called through various defined BAPIs.