Abstract: In accordance with an exemplary embodiment of the present invention, a DataBus data management architecture is presented for the NewWave service platform. It presents an architecture for creating a consistent, enterprise-wide data persistence layer which allows clients to access shared enterprise data. The DataBus achieves this enterprise-wide look by decoupling shared enterprise data from specific applications (breaking down the stovepipes) and opening up the data layer to across-the-enterprise access (given proper authorization). The DataBus architecture is designed from the ground up for global scalability and accommodation of evolving business data models in a highly-distributed physical deployment. Scaling is realized predominantly through the partitioning, while individual partitions are mapped to logical data domains that are defined along more relevant dimensions than entity-type dimensions (e.g., geography, line of business, etc.) and cut across traditional entity boundaries.

Abstract: In accordance with an exemplary embodiment of the present invention, a DataBus data management architecture is presented for the NewWave service platform. It presents an architecture for creating a consistent, enterprise-wide data persistence layer which allows clients to access shared enterprise data. The DataBus achieves this enterprise-wide look by decoupling shared enterprise data from specific applications (breaking down the stovepipes) and opening up the data layer to across-the-enterprise access (given proper authorization). The DataBus architecture is designed from the ground up for global scalability and accommodation of evolving business data models in a highly-distributed physical deployment. Scaling is realized predominantly through the partitioning, while individual partitions are mapped to logical data domains that are defined along more relevant dimensions than entity-type dimensions (e.g., geography, line of business, etc.) and cut across traditional entity boundaries.