Data Cleansing

Your customer databases are key business assets and in order to retain thier value you need to regularly cleanse the data.  Data analysis (profiling) will highlight data that needs to be corrected from the data migration. Legacy data often does not meet the criteria set out by new systems, and on occasions it must be modified/cleansed prior to a migration.

Our data cleansing processes only manipulate the legacy data so it conforms to the new system's requirements. This is done off the back of a data analysis (profiling) so that all the issues are considered (i.e. factors which can render the data unfit for migration in its present state).You need to see all of the issues that the data analysis has identified before you consider how best to rectify them.

Typically we would run workshops with business users to discuss our findings, following on from this we would produce a report which would provide details of each issue along with our recommendations as to how best to rectify the issues i.e. through an automated script or it may be better for business users to rectify the data manually.

Common issues found include inconsistencies, duplication, and inaccurate or invalid data (such as postcodes), data that doesn’t make sense within its own set of records, i.e. a policy which begins in 2001, but the client wasn’t put on until 2004, data that fails business rules, i.e. a 14 year old driver or a 21 year old that passed his test ten years ago.

Our detailed knowledge of insurance data ensures that these common issues are found and rectified quickly and easily.  During Extract, transform and load stages data correction / cleansing  usually takes place alongside the Mapping stages. Filters are also used to ensure the required level of quality.