Problem
ETL (Extract, Transform, Load) systems form the backbone of most data integration. These systems are quite mature and perform all their basic services well, but their ‘Transform’ capability is generally little more than data mapping and doesn’t deal well with unstructured, unpredictable product data. Normally the workaround would be to write custom code or scripts to extend the ‘Transform’ capability. However, this becomes a time consuming, expensive and unreliable exercise unless the data is very simple.
Solution
The DataLens System creates Data Service Applications (DSAs) that interpret any product data and delivers it in any required format with a known level of quality — assuring that it can be used properly in the destination system. In fact, most Silver Creek Systems customers already have ETL systems which they use to call a DSA to ‘clean’ their data as an in-line process.
