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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FIGURE 2-9 Real-Time InfoCube request ID
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InfoCubes. Therefore, we use a Standard InfoCube for actual data and a Real-Time InfoCube for planned data. Data integration is achieved using a MultiProvider that contains both of the InfoCubes. Access to the two different InfoCubes for planning purposes is controlled by the aggregation level that is created with the MultiProvider as the basis. Access to the specific InfoCube is controlled by the use of the unique characteristic 0INFOPROV (contains a list of the InfoProviders used), which is created upon the activation of a MultiProvider.
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DataStore Objects
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A DataStore object serves as a storage location for consolidated and cleansed transaction data on a document (operational) data level, or it can be used for the storage of master data for analysis. A DataStore object contains key fields (for example, document number/item) and data fields that contain both character fields (for example, order status, customer) as well as key figures. Another task that the DataStore object can be used for is the update of the current data in another object. This uses the delta updating functionality and can update data into an InfoCubes 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 for the DataStore object. The cumulative update of key figures is supported for DataStore objects, just as it is with InfoCubes, but with DataStore objects it is also possible to overwrite data fields. This is
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FIGURE 2-10 Query Designer view of a Real-Time InfoCube de nition
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particularly important with document-related structures. If documents (for example, sales orders transactions) are changed in the source system, these changes include both numeric fields, such as the order quantity, and nonnumeric fields, such as the ship-to party, status, and delivery date, can be updated into the DataStore object and the change statuses can be tracked by the change log in the DataStore object. To reproduce these changes in the DataStore objects in the BI system, you have to overwrite the relevant fields in the DataStore objects and set them to the current value. Furthermore, you can use an overwrite of the existing change log to render a source delta enabled. This means that the delta that is further updated to the InfoCubes, for example, is calculated from a delta process. This is a very basic outline of the back-end functionality of the DataStore object. As for the use and functionality in relationship to reporting, the DataStore object plays a very important role. Because it is structured to be able to store and manage line item detail and operational data, we can use it to do report-to-report interfacing for ease of access to detailed data.
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NOTE Report-to-report interfacing (RRI) is the process of using one query to filter information for
another query. You access one query from the executed query and identify a characteristic value that you drill down against for more detailed data. For example, suppose you are looking to review the details of a division. You execute a report that shows information for the division at a summary level; you then execute a query jump (RRI) to another query with the detailed data around the division.
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Storing the Data SAP/Business Warehouse InfoProviders
This approach eliminates the need to do an RRI back to the source system data and then effectively push additional query effort back onto the source systems tables. We can also use the DataStore object to execute and store precalculated information or enhance the transactional data as it is moved through the table structures in the DataStore object. Due to the flat table structures, if you query against the DataStore objects, you will see that query performance suffers a bit. The different types of DataStore object are Standard, For Direct Update, and WriteOptimized. In Table 2-3, you can see the differences in the structures, data supply, and BEx querying of the three DataStore objects. Figure 2-11 shows the architecture of a Standard DataStore object with the combination of three tables, as described in Table 2-3. An InfoCube fact table only contains key figures, in contrast to a DataStore object, whose data part can also contain characteristics. The characteristics of an InfoCube are stored in its dimensions. The dimensions of a DataStore object are the key fields and the data fields. The key fields are the combinations of characteristics that make up the critical key fields that identify whether a transaction that is being uploaded is either a new record or a changed record. The data fields are the combinations of characteristics and key figures being tracked in the DataStore object. Figure 2-12 shows the format of the DataStore object s key and data fields. Within the structure of the DataStore object, you can also create secondary indexes for use during the query process to increase the performance of the DataStore object during reporting.
Standard DataStore Objects The Standard DataStore object is filled with data during the extraction and load process in the BI system. As shown, the Standard DataStore object has three tables: The Active Table, the Activation Queue, and the Change Log. Each has a responsibility in the upload and query process. The Activation Queue is used for the processing of the initial data that comes in the DataStore object. This offers the ability to run serialization against the transactional data. As Figure 2-11 shows, the Activation Queue receives the data and passes it along to the Active Table and the Change Log for final storage. The Active Table is used for supplying the queries with information at a summary level.
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