MetaMatrix Inc

Description

Why Data Services? Service-oriented architectures are all about loose coupling among application components. Loose coupling promises to isolate the impact of changes, promote interoperability, and enable straightforward development and maintenance. One area that stands to benefit substantially from this loose coupling is the applications’ interaction with data. Over the years, application developers and architects have adopted the best practice of isolating interactions with application data in a specific tier of application services, in order to minimize the impact of change to a data source. But this practice assumes a relatively straightforward interaction with physical data stores. As the number of data stores grows and the complexity of integration needs increases, these “data tiers” begin to swallow up way too much development time.Whether or not an application is constructed using Web services, creating an architecture that loosely couples applications and data sources is a great way to avoid a heavy maintenance burden. This loose coupling can be achieved using data services—services that respond to requests for data interaction (such as data retrieval or updating), hiding the complexity of physical data sources from the rest of the application. Data services simplify applications’ interaction with data by presenting an abstracted view of the data that is appropriate for that application and the business processes it is supporting.The process of designing data services is the process of mapping from 1) the structures of existing data sources to 2) the data views the applications need—bridging the gap between the two views of data. The process of bridging this gap can include configuring data access; resolving semantic and vocabulary differences between multiple data sources or between sources and targets; transforming, integrating, or aggregating data from one or many sources; or simply providing data in a different form (from relational to XML, for example). MetaMatrix provides productivity tools to support this mapping process, taking a graphical, model-driven approach and eliminating the need to write custom code. Because data services are created efficiently, project schedules and budgets can be streamlined.

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