Using Data Fabric Architecture to Create Personalized Visual Analytics Systems in the Field of Digital Medicine

Abstract

The paper describes an innovative approach of applying data factory technologies, which have found their successful practical application to create new generations of corporate data warehouses, are proposed to be used to develop personalized visual analytics environments. The approach provides access to digital data of a particular person from both heterogeneous distributed external and local sources not on the principles of their consolidation, but on the principles of virtual integration. The application of the described approach is demonstrated by the example of the development of visual analytics tools in the field of digital medicine. The emphasis is on the technological aspects of applying the concept of data factories for the development of personalized visual analytics services, means of semantic integration of heterogeneous data sources and their adaptation not only to heterogeneous structured and unstructured data sources, but also to the semantic content of various subject areas.