Data Integration Models
To better understand the process of data integration, it’s helpful to consider integration models. Identifying the data integration model that suits your company, enables you to match up your requirements with data integration tools and technologies you need.
Simple information transformation: transforming one schema to another, without the ability to leverage logical operators, just moving and changing the data.
Transformation with logical operators (e.g., “If—then”): these data integration solutions deal with transformations in your data based upon content, lookup, or external information, such as time and date.
Complex transformation: data integration solutions that deal with complex schemas and semantic management. The software may include nested transformations and complex logic, like entire programs that are attached to a transformation.
Schemas with transformation bound to processes: the data integration solution with the ability to bind information flow, transformation, and logic to a process.
Transformations with information bound to services: this model includes integration with Web services. This data integration model also includes the solutions that can abstract services and data in many physical databases.
Your data integration requirements may not be limited to these models. That is why you have to carefully select the data integration technology that can get you from simple data integration solution to more sophisticated concepts.