Data services are software services that summarize tasks on key data units of relevance to the enterprise. Enterprise data is kept in various systems and requires several interfaces or mechanisms to interact with them. There are variable channels (branch, Online, call center) and mechanisms (event-driven, on-demand, batch process) that need to be served as well as adding additional tasks to data services. Without an intellection layer for data consumers that protects them from this problem, the enterprise will end up with a spaghetti of point-to-point additions between data sources and data consumers.
Data services abstract the customer from having to access or update several data sources and are critical in aiding the maintenance of data integrity when a consumer needs to work with multiple data sources. Additionally, they help build eco-friendly data services that can be leveraged for multiple projects and initiatives. Data services also perform a critical governance function - they help collect metrics, monitor, version management, reuse data types, and enforce data visibility and access rules.
Data services provide several additional benefits - data source abstraction, a combination of data providers, reuse (generic, flexible consumption patterns, interoperable), alignment with logical data models, support for multiple service versions, provide value-added features, and a single point of interaction. Therefore, they serve as the base on which an enterprise can meet developing business requirements on a continual basis.
