Calculation engines often get the focus (and the lion’s share of the budget) but the data coming in needs just as much attention.

Data is often transformed as it moves between systems, prefixes and suffixes may be added (or removed); aggregations lose data granularity or conversely version numbers or additional timestamps increase the number of data rows.

This means that a single data source, after flowing through the systems of two business units (eg finance and operations) can be incomparable at the end.

So reconciliations, root cause analysis of errors, system migrations; data lineage and accurate reporting fall over and data duplicates and holes abound.

CPRA has ample experience of using modern data tools to solve these issues.

There is no getting away from reconciliations: they happen whenever two related data sets are joined.  But keeping up with the layers of business rules, exceptions, input variations and formats makes this hard.

CPRA’s modern data analytic tools allow us to unravel the logic and rebase data at the most granular level, whether in numerical or text form.

So much time is spent creating slightly different flavours of the same data for different consumers.  Even worse is if the end output is in pdf or powerpoint.  The report generation often requires manual intervention, or excel as a bridge between systems or as the method of consolidation.

It does not have to be this way: our tools can sit and connect to a myriad of existing systems, consolidate the data, perform the calculations and mould it into the different output formats.

All scheduled, whether on premises or in the cloud.