Shared Data Services
Problem – Shared Data Services Require a Different Approach
Service-oriented development approaches have seen increasing levels of adoption in recent years in order to help enterprises gain agility and reuse. Early use cases were typically driven by business process optimization objectives. ESBs, the enabling middleware for mediating transactions, were key to this initial phase, providing applications developers with a rich tool set, while easing learning curves and simplifying adoption.
However wider informational uses of services, in support of business intelligence for example, have come to the forefront. Meeting these needs requires data services development and runtime middleware that enables a more detailed understanding of data structures, more powerful data modeling and query mechanisms, the ability to transparently interact with transaction services and middleware, as well as agility and reuse.
Solution – Use Data Virtualization to Build Sharable Data Services
Composite data virtualization provides a complete set of development and runtime tools to build and deploy sharable data services that meet a variety of information needs. Delivered via SOAP, JMS and REST, Composite data services can be applied to multiple projects, so you can achieve your agility and reuse objectives. Composite even lets you repurpose “non-SOA” code such as relational views into sharable data service in just a few clicks. And because Composite works in conjunction with other SOA tools such as Enterprise Services Buses (ESBs), Registries, and Application Servers, you can leverage your existing technology investments.
Shared Data Services
Selected Examples
- Improving Control with a Shared Counter-Party Data– With key reference data, such as counterparty accounts, duplicated across applications, this investment bank developed and deployed a common counterparty master reference data service using Composite data virtualization that provided and replaced point to point integrations. Not only did this save cost and accelerate application changes, it also provided a single point of control over risky counter-party trades.
- Reducing Costs with a Shared Location Data Service– With hundreds of locations and thousands of property assets, this global bank used Composite data virtualization to provide a shared location data service that federated multiple property management repositories and abstracted the data for easier consumption. This saved new development time and costs, helping IT become more responsive to the business.
