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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 Structure linkInfoProviders.

Data is provided in the form of a simple table. You can determine which columns the table contains by selecting characteristics and key figures. If you omit fields when you select characteristics, key figures are aggregated using the excluded characteristics. Aggregation is performed using the standard aggregation behavior for the selected key figure. Aggregates for InfoCubes are used if they are available.

Features

Reading data from an InfoProvider is comparable to the 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 possible here and have to be reproduced, as required, using subsequent transformations.

Active Data

Only data available for reporting is read from the data source InfoProviders. With InfoCubes, the data is available immediately as long as the requests are 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 have finished. With DataStore objects, the data has to have been activated. 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 / Periods (0FISCPER) is selected and the compound characteristic Fiscal Year Variant (0FISCVARNT) is not selected as well, 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 Revenue (0REVENUE), the currency is not considered when aggregation takes place. 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 a key figure with exception aggregation is present among the selected key figures, the associated reference characteristic for the exception aggregation has to be selected as a characteristic. This is to prevent a situation where a key figure Number of Employees with exception aggregation LAST VALUE is also totaled using periods. This is not worthwhile.

Exception aggregation can be reproduced using a subsequent grouping step:

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

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

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 closing stock balance for the month 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 Values.

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 have been selected in non-cumulative parameter maintenance, these also have to 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 has to be defined in a subsequent filter. Only one interval or a list of single values is supported here. Other restrictions for the time-reference characteristic will lead to errors during execution.

Activities

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

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

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

Example

The following characteristics and key figures are selected from 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) of 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; all records with the same combination of characteristics are added together.

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 output for the nodes in this example is:

R segment

F segment

Number of responses

1

1

17

1

2

16

2

1

42

3

1

12

 

 

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