Service Oriented Architecture (SOA) has been a buzzword for some years.
In my opinion SOA is a golden opportunity for getting the benefits from data quality tools that we haven’t been able to achieve so much with the technology and approaches seen until now (besides the other SOA benefits being independent to technology).
Many data quality implementations until now have been batch cleansing operations suffering from very little sustainability. I have seen lots of well cleansed data never making it back to the sources or only being partially updated in operational databases. And even then a great deal of those updated cleansed data wasn’t maintained and prevented from there.
Embedded data quality functionality in different ERP, CRM, ETL solutions has been around for a long time. These solutions may serve their purpose very well when implemented. But often they are not implemented due to bundling of distinct ERP, CRM, ETL solutions and consultancies with specific advantages and data quality tools with specific advantages, which may not always be a perfect match. Also having different ERP, CRM, ETL solutions then often means different data quality tools and functionality probably not doing the same thing the same way.
Data Quality functionality deployed as SOA components have a lot to offer:
• Reuse is one of the core principles of SOA. Having the same data quality rules applied to every entry point of the same sort of data will help with consistency.
• Interoperability will make it possible to deploy data quality prevention as close to the root as possible.
• Composability makes it possible to combine functionality with different advantages – e.g. combining internal checks with external reference data.
During the last years I have been on projects implementing data quality as SOA components. The results seem to be very promising so far, but I think we just started.