Stone Bond Technologies’ Enterprise Enabler Eliminates the Need for Data Modeling
HOUSTON – September 12, 2012 – Stone Bond Technologies has enabled IT departments to eliminate the need to build canonical data models for complex data integrations. With legacy integration tools, a multi-step process is used wherein a data source is mapped to the canonical model which historically was the staging database’s model. Data is then mapped from the canonical model to the destination’s schema. This legacy process is expensive and cumbersome leading to long term tech debt and maintenance demands.
While the canonical model approach is supported by Enterprise Enabler where desired, it is never necessary, because mapping can always be done directly from multiple source schemas to the destination. This enables direct mapping, which is much simpler to define. Federation across the sources is now handled within the solution by Enterprise Enabler and without the need for additional work.
A practical example would be when you would use a solution such as Biztalk, every set of data that is transformed needs to first be converted to a canonical XML format before it can go through the XSLT transformation and then from XML to the destination format. So what would be three transformations in Pervasive, Biztalk, Composite or other similar legacy tool will be a single transformation in Enterprise Enabler. Pamela Szabo, CTO of Stone Bond comments that, “with this method of integration you get the added benefits that performance is inherently much better coupled with not needing to define or maintain a canonical model.”
The elimination of the traditional data modeling required with legacy solutions is another advantage within Enterprise Enabler. Others include a comprehensive metadata monitoring tool ensuring complete integration governance, the Active Integration Interface for seamless integrations, the robust Integration Workflow Designer for automated integration execution and the AppComm technology for seamless, out of the box integration to thousands of data sources.