This integration pattern has a close relation with the parallel integration, however there is an extra layer introduced for the virtualisation and standardisation of data extraction to consumers of the data.

Characteristics

• Virtualisation layer encapsulate the internal confuguration of the two platforms


• The virtualisation layer requires a standardized data or objectmodel for the extraction by the consumers


• The virtualisation can become a bottleneck in a number of qualities like performance, integratability e.g.

Description of the data sources in general. Is an aggregation of specific data source types. This generic datasource is added to the model to make associations possible with generic requirements and principles

This is the logical application of a data warehouse not the component. It describes the functionality of storing, modeling updating and retrieving enterprise data based on relational data including the history of the data

Logical application composite for implementation of Big Data functionalities

Consumer of data, in most situation the consumer gets access to processed data (cleaning, filtering, transforming) based on a standardized model

Implementation of EDWH and Big Data functionality extracted via a virtualisation function. This virtualization acts as an encapsulation layer and API for the consumer applications

Logical application for virtualization of data implemented in a standardized object or data model