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Function documentation InfoProviders  Locate the document in its SAP Library structure

Use

The data source This graphic is explained in the accompanying text Read Data from InfoProvider allows you to use data from a BI InfoProvider as a data source in the analysis process. InfoCubes, DataStore objects, InfoObjects, MultiProviders and InfoSets are InfoProviders. See InfoProviders.

The data is provided as a basic table. The selection of characteristics and key figures determine which columns the table contains. If fields are omitted when the characteristics are selected, the key figures are aggregated using the characteristics that are excluded. Aggregation is performed using the standard aggregation behavior for the selected key figure. If available, aggregates for InfoCubes are used.

Features

Reading data from an InfoProvider is comparable to direct selection of data according to the schema:

SELECT              <selected characteristics and key figures>

FROM       <InfoProvider>

GROUP BY <selected characteristics>

Some basic functions of the query are not supported and must be represented, as required, using downstream transformations.

Active Data

The system only reads data that is available for analysis and reporting from the data source InfoProviders. With InfoCubes, the data is available immediately, assuming the requests loaded successfully. You can see this by checking the This graphic is explained in the accompanying text Request is Available for Reporting icon in InfoCube administration. With master data, the attribute change run has to be complete. With DataStore objects, the data has to be activated first. With DataStore objects of type direct update the data can be seen immediately.

Compound Characteristics

All characteristics are considered independent fields. If, for example, the characteristic Fiscal Year / Period (0FISCPER) is selected and the compound characteristic Fiscal Year Variant (0FISCVARNT) is not selected, the data is aggregated using all fiscal year variants.

Units/Currencies

Units of key figures are considered independent fields. No currency translation takes place. If, for example, you aggregate using the key figure Sales (0REVENUE), the currency is not included during aggregation. If necessary, include the relevant currency or unit field in the list of selected characteristics.

InfoObjects That Are “Attributes Only“

InfoObjects that are defined as Attributes Only are not offered as fields for selection if they are used in InfoProviders, especially with DataStore objects and master data tables.

Exception Aggregation

Key figures are only aggregated according to their standard aggregation. If the selected key figures include a key figure with exception aggregation, the associated reference characteristic for the exception aggregation must also be selected as a characteristic. This is to prevent a situation where a key figure Number of Employees with exception aggregation LAST is also totaled using periods; this would be a redundant situation.

The exception aggregation can be reproduced using a downstream grouping step:

      If the exception aggregation type is SUM, MIN, MAX, AVG, AV0 or NOP, you can use the Aggregate Data transformation. See Aggregating Datas.

      If the aggregation type is different to those listed above, you have to use the ABAP Routine transformation and program the aggregation yourself. See ABAP Routiness.

Non-Cumulative Key Figures

Non-cumulatives can be modeled in the BI system using a non-cumulative key figure with the corresponding fields for changing the non-cumulative or the corresponding fields for receipts or issues. The current non-cumulative is then saved on a marker.

If a non-cumulative key figure is selected, the period end non-cumulative is provided for each period within the selected timeframe. This value is determined when data is read from the marker and the non-cumulative changes. If the selected period is outside of the area of validity, no non-cumulative is returned.

For more information see Modeling Non-Cumulatives with Non-Cumulative Key Figures.

Features of non-cumulative key figures:

      The reference characteristic for time-based aggregation (time-reference characteristic) must always be selected as a characteristic. If additional validity-determining characteristics were selected in the maintenance for non-cumulative parameters, these must also be added to the selected characteristics.

      Since non-cumulatives are returned for all periods in the selected timeframe, a restriction for the time-reference characteristic must be defined in a downstream filter. Only one interval or a list of single values is supported here. Other restrictions for the time-reference characteristic lead to errors during execution.

Activities

       1.      On the Data Source tab page, select an InfoProvider.

       2.      On the Field Selection tab page, select the individual fields from which the system is to read data during the analysis process.

On the right side of the dialog box, all the fields for the InfoProvider are listed, separated according to characteristics (top list) and key figures (bottom list). You must select at least one key figure and one characteristic from those listed.

Example

You have selected the following characteristics and key figures from the DataStore object RFM Response Rates (0CRM_OFCV):

      RFM Response rate model (0CRM_RFMFCV)

      RFM Segmentation model (0CRM_RFMSGV)

      RFM R Segment (0CRM_RFM_R)

      RFM F Segment (0CRM_RFM_F)

      RFM Number of responses (0CRM_RFM_RE)

Characteristic RFM M Segment (0CRM_RFM_M) for the InfoProvider is not selected.

When the data is read, the data passed on to the subsequent nodes (the next step of the analysis process) is grouped together with the standard aggregation behavior of the key figure on the level of the selected characteristics. The aggregation for the key figure is SUM; the system totals all records with the same combination of characteristics.

Example data:

      RFM Response rate model (0CRM_RFMFCV) = test

      RFM Segmentation model (0CRM_RFMSGV) = test

R Segment

F Segment

M Segment

Number of Responses

1

1

1

17

1

2

2

16

2

1

1

15

2

1

2

14

2

1

3

13

3

1

1

12

The data at the node in this example is as follows:

R Segment

F Segment

Number of Responses

1

1

17

1

2

16

2

1

42

3

1

12

 

 

 

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