Cooper Data Integration Workbench

We use probabilistic and deterministic matching approaches which calculates a probability of a match between two similar records about a person, place or business. For example, is ‘John Smith’ the same as ‘Jon Smith’ when the records have a matching address. Probably – maybe 90%, say. What if here is a slight difference in address though – so the street name on one record is ‘Acacia Avenue’, but another record it’s ‘Acacia Street’? Probably yes again, but maybe 80% this time.

Some use cases require a very high degree of confidence in matching – and 90% is just not good enough. In this case ‘John Smith’ is not the same as ‘Jon Smith’. Others need a lower threshold – say 85%, while others can be very loose – say 75%.

We provide a simple interface to enable data scientists and data engineers to choose the probability thresholds on a case by case basis, so they can tune data linkage results.

Minimum Viable Product We have standardised processes to bring data together. Our MVP provides a simple web interface to set matching thresholds for two datasets and create an extract of data for a cohort that matches agreed selection criteria, following the 5 Safes Framework.

The diagram below shows the high level process that the Cooper product follows for matching or linking data together. The red dots indicate the process controls matched to the 5 Safes Framework

We will follow with an enhanced automated secure file transfer capability, alternative industry standard linkage keys and finally the ability to geo-standardise input data to improve match results. Availability for these four areas is shown in our roadmap. [https://datajps.com/data-superconductor-roadmap/]

Back to our offers [https://datajps.com/data-superconductor-offers-and-mvp]

Note that Data SuperConductor and all the related content for it is not real – including this page. It’s just a hypothetical university project.”,