If the source data is inconsistent by Time (some years may have been recorded in the wrong department) as an example, composite When mapping needs to vary by Time period.ДЄ Data Source may require unique mappings based upon the source Time Year. For Texas, it is mapped to 518, while Houston is mapped to In this example, the composite mapping for account 8033 and department 750 are being mapped to 2 different UD2 targets, based upon the Entity. The following example shows how composite mapping can be used: If the source data is inconsistent by Entity (accounts or departments вЂњUD2вЂќ) as an example, composite mappings will need to be used. System like OneStream, the implementation team will have to вЂњfashionвЂќ the mappings to ensure consistent reporting year over year.ДЄ Data Source may require unique mappings based upon the source Entity. As that data is being imported into a more robust reporting

When loading multiple years of historical data, there may be times when the source system(s) had allowed data to be recorded inconsistently. When challenged to map inconsistent historical data. This blog will show how they can be utilized in the following ways:ДЄ) When challenged to map inconsistent historical data.Д¬) When mapping needs to vary by Time period.Д) Where Account and Department drive the Target Account.Д®) Where Account and Entity drive the I/C partner. There are multiple reasons why an implementation would require the use of Composite Transformation Rules. Why would a client need to use Composite Transformation Rules?

This article will focus on the Composite type of Mapping, which provides for multiple source dimensions, to work in tandem, to define the target OneStream reporting intersection. OneStream transformations are comprised of 5 different The OneStream Transformation Rules provide the ability to transform or вЂњMapвЂќ source data to the desired target OneStream reporting intersection. Some Usages of OneStream Composite Transformation Rules

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