Configuring Aggregation by Common Dimension

Objective

After completing this lesson, you will be able to aggregate report fields by common dimension

Aggregation by Common Dimension

Multi-fact reports with aggregation by common dimension are helpful to compare common fields across facts, manipulate the data cube, and drill down to examine aggregated data in different areas. Creating a multi-fact report with aggregation by common dimension is similar to creating a basic multi-fact report but includes extra steps for mapping the fields from different facts to common report fields.

You can add an unlimited number of facts to a multi-fact report with aggregation by common dimension, but you can only add fields from dimensions all the reporting facts have in common. In the Common Dimension Example image, Commodity is a dimension common to the Purchase Order and Invoice facts, so a Commodity field can be added to the report. The resulting report can display PO Spend and Invoice Spend broken down by Commodity.

Comparison of Multi-Fact Reporting Types

The following table describes the differences between the two types of available SAP Ariba multi-fact reporting:

BehaviorBasic Multi-Fact ReportingMulti-Fact Reporting with Aggregation by Common Dimension
Maximum number of factsYou can add a maximum of three facts to the report.You can add an unlimited number of facts to the report.
Fact selectionYou can only add facts to the report if they have pre-defined relationships to each other.You can add any combination of facts to the report. There is no requirement for pre-defined relationships.
Field selectionYou can add any field from the underlying facts to the report.You can only add fields to the report if they are a dimension common to all of the underlying facts.
Field mappingEach field you add to the report is an individual field that contains data only for its fact.Each field you add to the report is common to all facts, and you map individual fact fields to the common field. It shows data for all underlying facts.
Data aggregationIn some cases, subtotals do not roll up to totals.Since the fields are mapped, all subtotals roll up to totals.
Data matchingData options allow you to include only matching data, or all data, for different fact combinations in the report.The report includes all fact data within filter parameters.
Initial date filteringThe initial date filter is always on a date field from the main fact. This filter then determines what data in the second and third facts match the main fact. This matching second and third fact data can fall outside of the main fact date filter’s time period.The initial date filter is a mapped field for date fields in all underlying facts. The report includes only data for the time period specified in the filter for all facts.
PerformanceCan run more slowly, but provide better detail-level data.Usually the faster option if you are focusing on aggregate data.

Create an Example Multi-Fact Report with Aggregation by Common Dimension

To build a multi-fact report with aggregation by common dimension example, follow these steps:

  1. On the dashboard, choose Create → Analytical Report.
  2. On the Source Data page, enter a title and optional description for the report.
  3. Open the Main Fact list and select Create multi-fact report (aggregation by common dimensions).
  4. Select the Invoice, Purchase Order, and Receipt facts.​
  5. Choose OK.
  6. Add the PO Spend, Amount Accepted - Receipt, and Amount Invoiced - Invoice measure fields into the Data area of the pivot table.
  7. Choose Next.
  8. On the Pivot Layout page, add Common Supplier and Requester (User)to the Row Fields area of the pivot table.
  9. Choose Next.
  10. On the Refine Data page, set Relative date range to the most recent 1 year.
  11. Choose Run Report.

​​The resulting report is displayed in the Example Multi-fact by Common Dimension image.

How to Create a Multi-Fact Report with Aggregation by Common Dimension

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