Business evaluation-objects (customer, sales revenue, and so on) are called InfoObjects in BW. They are subdivided into characteristics, key figures, units, and time characteristics.InfoObjects have three significant functions:
ŸThey are components of an InfoSource. InfoObjects function like the fields in a structure, but they also have additional meta-information.They are similar in design to an InfoCube in that they display characteristics and key figures.They complete an InfoSource by adding master data, text, and hierarchies.You can use InfoObjects in as many different InfoSources and InfoCubes as you need. SAP InfoObjects start with 0. InfoObjects that customers define themselves start with a letter from A to Z.
You select the characteristics for a new InfoObject from a series of tabstrips.These settings have a big influence on the capabilities of the InfoObject and how it is used in BW.These settings also form the metadata for the InfoObjects. They are stored in the metadata repository.
Defining exception aggregation:
Key figure maintenance -> Aggregation -> Exception aggregation .For the key figure “Monthly Headcount”, the last headcount number in the period would need to be chosen instead of adding together all the daily headcounts. So the exception aggregation type would be LAST and the exception aggregation characteristic would be the appropriate time characeristic.
BW InfoCube Components
The fact table and the dimension tables of an InfoCube that belong to the fact table are connected to one another relationally using the dimension keys. Dimension keys are provided by the system, one dimension key for each combination of characteristics in the dimension table.When you execute a query, the OLAP processor searches in the dimension tables of the InfoCube that you want to evaluate for the combinations of characteristics that have been requested in the selection.The dimension keys that are generated in this way point to the information in the fact table.
Multidimensional Analysis
In the BEx Analyzer, the user creates a query by selecting several characteristics from the list of all the characteristics that are available in the InfoCube. In this case, the user has chosen the characteristics customer group, division and region.When the query is executed, the OLAP processor evaluates the query definition and retrieves a subset of the InfoCube data known as the query cache. This process runs in the main memory for performance reasons. The only data in the query cache is the data that corresponds with the query definition.Depending on the values that are requested for each characteristic, the OLAP processor selects the appropriate rows of data from the query cache and passes this data on to the tool whose task it is to display the data.
As soon as the appropriate rows of data for the selected characteristic values have been passed on to the tool that displays the data, the key figures for these rows are also made available.If you change the filter values of the characteristics, the system selects a new set of rows of data. If this happens, the values of the key figures change accordingly.
From Data Model to Database
Depending on the context, the terms InfoCube, dimensional analysis, star schema, and data mart, refer essentially to the same thing, namely how data is structured within BW tables.The term star schema refers to the general concept of the table structure or the table structure from a data modeling perspective. InfoCube usually refers to the actual tables containing data. In BW,queries are related to an InfoCube or an ODS object.
Creating a New InfoCube
When you create a new InfoCube, the data model must deliver all the required information.In the data targets tab in the data modeling area of the Administrator Workbench, you select the InfoArea to which you want to assign the InfoCube. With the right mouse-button you click on this InfoArea and choose the Create InfoCube function.
You give the InfoCube a name from the customer name range (beginning with any letter from A to Z).You select the appropriate characteristic InfoObjects based on your data model.You create the dimensions that you need in addition to the standard dimensions of time, unit, and InfoPackage.You assign the chosen characteristics to the appropriate user-defined dimensions. The unit and InfoPackage dimensions are populated by the system. The time dimension is populated in the next step.On the time characteristics tab, you choose the time characteristics that you want to use. These are assigned to the time dimension.You choose the key figures specified in the data model. You check that your InfoCube design is complete. If it is, you activate the InfoCube.
Multilingual descriptions for attributes in the dimension tables are not supported.Secondary indexes for the data are stored as alphanumeric fields in comprehensive tables. This makes it more difficult to access the data.If attributes of the dimensions change over time, there is no way of maintaining the old and new values for the attribute.Even if the majority of a company’s master data is used across the different business processes, each star schema must duplicate all of the data that is required for all of the possible user-reports that might be generated.All hierarchy relationships for the data must be modeled as attributes (characteristics) of a dimension table. It is not possible to generate user-defined hierarchy types.
Although many data warehouse solutions are based on designs similar to the standard star schema,there are many restrictions and problems associated with this basic design. This is why the SAP BW has an extended star schema.
A basic star schema has the following restrictions:
Only characteristics from the dimension tables can be used to access the facts.
No structured drilldowns can be generated.
Supporting a large number of languages is difficult.
No structured drilldowns can be generated.
Supporting a large number of languages is difficult.
In BW the extended star schema enables you to access:
Master data tables and their associated fields (attributes)
Text tables with extensive multilingual descriptions
External hierarchy tables for structured access to the data
Text tables with extensive multilingual descriptions
External hierarchy tables for structured access to the data
Master Data Outside the Dimension
You can use master data attributes across various InfoCubes. Attributes are fields that describe a master data element. These attributes display additional information within a workbook to make the results more meaningful.For example, you can define navigation attributes. This means that, as far as navigation is concerned, the attributes behave like characteristics, even though they are not included in the dimension table.
Attributes that you have defined as display attributes in a master data table can be displayed as additional information only in combination with the characteristic belonging to the attributes. You are not able to use a display attribute to navigate in a query. A single attribute table can be shared between several InfoCubes. The fact that data is shared increases its transparency for the user and guarantees that the data is consistent across different queries.
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