A dynamic data integration system that presents multiple (syntactically or semantically) heterogeneous datasets as a unified, homogeneous virtual dataset. The service comprises configuring and deploying the system, and, if required, adaptation and customization.
Semagrow is a versatile federated query processing system that presents client application with a unified querying end-point. Semagrow offers application developers an abstraction over heterogeneous data sources where the application does not need to be aware of syntac and semantic heterogeneity of the underlying data sources. Web APIs, relational databases, GIS, document stores, and graph stores are dynamically and seamlessly combined into a unified virtual dataset, without copying and reduplicating data.
Access to Cloud computational resources
Kubernetes cluster preferred.
Semagrow has been used to integrate diverse datasets in multiple domains and applications. Among others, meteorological, land-usage, water availablity, and crops data for food security; meteorological, GIS, and dispersion modelling data for risk estimation, biology and pharmacology datasets for pharmacological research.
Can be combined with AI Training & Consulting for data-driven strategy offered by ahedd
Successfully demonstrated in a demanding, data-intensive application for estimating the impact of dangerous substance dispersion where metereological data was combined with GIS data about population and infrastructres and with dispersion modelling results.