Finance Computing Framework: Transformation





Transformation is one of software modules within Finance Computing Framework which play a key role to support configuration of data transformation methods in order to address the measurement and recognition requirements applied to collected data for particular finance computing. Following are three main homogeneous groupings of data transformation methods:-


Basic and re-measurement assumptions

Basic and other adjustments

Basic and tagged dimensions


You can have a gap analysis between collected data and required consolidation reports in order to select most suitable transformation methods within each of above homogeneous groupings.


Configuring processing rules can facilitate customization of data transformation for different user groups efficiently. In addition, the use of user-defined lookup tables can empower end-users to innovate the automation of detail transformation rules whenever there are increasing volume and complexity of data sources.


An implementation of effective date of change can be relevant for selected transformation methods whenever end-users demand for transforming data on prospective basis rather than retroactive basis.


Finance Computing Framework


Finance Computing Framework is built over the FESA Application Server which specializes in finance computing throughout recording to reporting. To support the solving of different scenarios of AVESTA computing issues the Finance Computing Framework has been developed and maintains a portfolio of software building blocks which are classified as follows:-

 System Control