Storing the Data SAP/Business Warehouse InfoProviders in Microsoft Office

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Storing the Data SAP/Business Warehouse InfoProviders
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Therefore, any of the basic requests for information you use to run your business, the InfoCube can answer. Just remember, the InfoCube can answer any question about events that have happened, not events that have not happened. For example, suppose you are interested in knowing the product orders that have run during the month that have not had any variance between standard costs and actual costs. The InfoCube doesn t hold information about any event that has not happened and the production orders that don t have a variance have not happened. You will learn later that another InfoProvider is used for this situation. An InfoCube describes (from an analysis point of view) a self-contained dataset (for example, for a business-orientated area). You analyze this dataset in a BEx query. Here s another way to describe an SAP BI InfoCube: It is a set of relational tables arranged according to the extended star schema. InfoCubes are filled with data from one or more datasources or other InfoProviders. As you can see from Figure 2-5, the Fact table is the central table of the InfoCube and stores the combinations of dimension IDs and key figures that make up the transactional data.
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NOTE An extended star schema is an enhancement of the classic star schema. In the extended star
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schema, the InfoCube itself doesn t hold any master data of the characteristics. The master data information is stored in separate tables in the InfoObjects, called master data tables. Thus, the master data tables extend the star schema hence the name extended star schema. Figure 2-5 shows a diagram of an extended star schema. The dimension IDs hold groups of characteristics. In the case of the Cost Center dimension table, you can see that Cost Center, Controlling Area, and Person Responsible are all held in one dimension. Review the other dimensions Cost Element and Time to see what characteristics are being held in those. You can see that the grouping of characteristics within
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External Hierarchy Attribute Table
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COST_CTR# CO_Area Company_Code Profit_Ctr Pers_Resp.
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Attribute Table
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COST_ELEMENT
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COST_CTR# SID_COST_CTR
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Cost Center Dimension Table
COST_CTR_DIM SID_COST_CENTER SID_CO_AREA* SID_PERS_RESP*
Specific Cost Element Fact Table
DIM_ID_COST_ ELEMENT DIM_ID_TIME DIM_ID_COST_CENTER
Cost Element Dimension Table
DIM_ID_COST_ ELEMENT SAP_COST_ELEMENT SAP_SENDER_REC
Cost Element Group
SID Table
COST_ELEMENT SID_COST_ELEMN
External Hierarchy
Text Table
COST_ELEMENT
Text Table
COST_CENTER# SID
Amount Quality
Short Text
Specific Cost Element
Time Dimension Time Dimension Table
DIM_ID_TIME SID_FISCAL_PERIOD SID_FISCAL_ YEAR
The Pers-Resp. InfoObject is on both the master data and the DIM table
SID Table
FISCAL YEAR SID_FISC_YEAR
SID Table
FISC PERIOD SID_FISC_PER
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FIGURE 2-5
BI InfoCube: extended star schema
SAP Business Information Warehouse Reporting
a dimension is important for the performance of the query because having the appropriate characteristics grouped together allows the query to reduce the amount of data processing needed as well as to organize the data for the queries. But that s a data modeling concern, and even though the data model of the InfoCube is of great importance, it is more of a configuration discussion and therefore beyond the scope of this book. Data modeling for data warehousing has been well documented in other books such as The Data Warehouse Toolkit by Ralph Kimball. A number of key data modeling concepts are of importance and specific to SAP BI InfoCubes, but again this is a configuration issue and therefore not directly discussed in this book.
Standard InfoCubes The preceding is an overview of InfoCubes, but really this discussion is
consistent with the structure of Standard InfoCubes. In Figure 2-6, you can see a view of the configuration of an SBC Standard InfoCube, 0FIGL_C01. Object Information and Settings are closed in order to view the additional information for Key Figures and Characteristics. The three dimensions Data Package, Time, and Unit are always delivered with an InfoCube. The other dimensions are in this case delivered by SAP, but you can create additional dimensions (a total of 13 dimensions) that group characteristics. In this figure, one dimension Organizational Units groups together the characteristics Company Code and Business due to the consistency of the information that is delivered by the combination of these two characteristics. Notice the icon for the dimensions the grouped green triangles. You will see these shortly in the querying process. Characteristics that logically
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FIGURE 2-6
Data model display for a Standard InfoCube
2:
Storing the Data SAP/Business Warehouse InfoProviders
belong together are grouped in a dimension. By adhering to this design criterion, dimensions are to a large extent independent of each other, and dimension tables remain small with regard to data volume. This is beneficial in terms of performance. In Figure 2-7, you can see the Standard InfoCube in the Query Designer as it is viewed by the Power User in the process of creating the query definition. As you can see, the Dimension icon groups the different characteristics for use. In this case, the Material dimension holds just one characteristic, Material, whereas the Sales Area Data dimension has three characteristics Distribution Channel, Division, and Sales Organization grouped together. Again, one of the factors in defining the Dimension structure (characteristics that are grouped together) and the data modeling process would be the reporting process of the Business User. Also notice the folder identified as Key Figures; this is where all the key figures that are listed and available to use in a query definition. We will be discussing and defining all the different areas in the Query Designer in 4 and therefore will not dwell on the actual structure here.
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